{ "entity": "deepseek-v4-flash", "entity_type": "model", "category": "Best free", "suite": "suite-2026-07", "model": "deepseek/deepseek-v4-flash", "judges": [ "anthropic/claude-sonnet-5", "google/gemini-3.1-pro-preview", "openai/gpt-5.6-terra" ], "judge_protocol": "judge-2026-08", "anchors": "solo-2026-08-a", "score": 85, "caps": 0, "cost_usd": 0.3619, "started_at": "2026-08-11T16:44:58.746Z", "finished_at": "2026-08-11T16:47:30.056Z", "tasks": [ { "id": "w1", "name": "Cold email", "prompt": "Write a cold email (max 120 words) from the owner of a 6-person UK accounting firm to a local brewery, offering a free first-month bookkeeping trial. Friendly but professional, one clear call to action, no buzzwords.", "output": "Subject: Free first-month bookkeeping trial for [Brewery Name]\n\nHi [Name],\n\nI run a small accounting firm in [town/city] with a team of six. We work with local businesses and understand the specific financial challenges breweries face—stock management, VAT, and margin tracking.\n\nTo show what we can do, I’d like to offer you a free first-month bookkeeping trial. No commitment. You’ll see exactly how we handle your numbers, free up your time, and keep things HMRC-ready.\n\nIf that sounds useful, just reply to this email and we can arrange a quick call to set it up.\n\nBest,\n\n[Your Name]\n[Firm Name]\n[Phone number]", "latency_ms": 3256, "cost": 0.000075174, "task_score": 9, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 8, "violates": false, "reasoning": "Concise, friendly, professional, clear CTA, no buzzwords, under 120 words. Minor genericness but solid fit to task." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The email perfectly follows all instructions. It is under the 120-word limit (approx 100 words), includes all required details (6-person UK firm, brewery focus, free trial), maintains a professional tone without buzzwords, and has a clear C" }, { "judge": "openai/gpt-5.6-terra", "score": 9, "violates": false, "reasoning": "Friendly, professional, UK-relevant, and clearly offers the requested free first month. It stays under 120 words, avoids buzzwords, and has one practical reply-based call to action. “I run” implies but does not explicitly state ownership." } ], "machine_checks": { "max_words": 120 }, "machine_violation": false, "machine_reasons": [] }, { "id": "w2", "name": "Product description", "prompt": "Write a 60-80 word product description for a stainless-steel insulated water bottle (750ml, keeps drinks cold 24h/hot 12h, leakproof, fits car cup holders). Target audience: gym-goers. Avoid cliches like 'stay hydrated in style'.", "output": "Built for gym sessions, not fashion shows. This 750ml stainless steel bottle keeps water ice-cold for 24 hours or coffee hot for 12—no lukewarm sips mid-set. Leakproof lid survives bag tosses, while the tapered base fits most car cup holders for post-workout drives. Durable, double-wall insulation, zero condensation. Just fill, grab, and go.", "latency_ms": 3736, "cost": 0.00005544, "task_score": 5, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 5, "violates": true, "reasoning": "Good content, avoids cliches, but only ~53 words, below required 60-80 word range." }, { "judge": "google/gemini-3.1-pro-preview", "score": 5, "violates": true, "reasoning": "Excellent, punchy copy tailored perfectly to gym-goers while including all required specs. However, it violates the minimum word count constraint, coming in at 54 words instead of the required 60-80." }, { "judge": "openai/gpt-5.6-terra", "score": 5, "violates": true, "reasoning": "Clear, gym-focused, and accurately covers capacity, insulation, leakproofing, and cup-holder fit without clichés. It is engaging and concise, though “zero condensation” is an unsupported absolute. It contains 52 words, below the required 60" } ], "machine_checks": null, "machine_violation": false, "machine_reasons": [] }, { "id": "w3", "name": "Summarise messy notes", "prompt": "Turn these messy meeting notes into a clean 5-bullet summary a director could read in 20 seconds:\n\n'ok so launch slipped again, marc says supplier issue?? maybe 3 wks. sarah wants to push the email campaign anyway but tom thinks wait. budget - we're 8k over, mostly the packaging redo. Q: do we tell retail partners now or after new date confirmed. also NEED to hire the warehouse temp before august rush. next mtg tues.'", "output": "Here is a clean, 5-bullet summary for a director:\n\n- **Launch Delay:** New target is ~3 weeks out due to a supplier issue (per Marc).\n- **Email Campaign:** Sarah proposes proceeding; Tom advises waiting. Decision needed.\n- **Budget:** $8K overrun, driven primarily by the packaging redo.\n- **Retail Partners:** Clarify whether to notify them now or after the new date is confirmed.\n- **Urgent Hire:** Warehouse temp must be onboarded before the August rush. Next meeting: Tuesday.", "latency_ms": 20990, "cost": 0.0000262815, "task_score": 9, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 9, "violates": false, "reasoning": "Accurate, concise, exactly 5 bullets, covers all key points, director-friendly and quick to read." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response perfectly follows all instructions, providing exactly five concise, clear, and accurate bullet points that capture all key information from the notes. It is highly useful for a busy director." }, { "judge": "openai/gpt-5.6-terra", "score": 8, "violates": false, "reasoning": "Exactly five clear, director-ready bullets. Accurately captures decisions, budget, communications, staffing, and next meeting. Minor issue: it frames the possible three-week delay as a new target and changes “hire” to “onboarded.”" } ], "machine_checks": null, "machine_violation": false, "machine_reasons": [] }, { "id": "w4", "name": "Tone rewrite", "prompt": "Rewrite this complaint reply so it is warm, takes responsibility, and keeps the same facts, in under 90 words:\n\n'Your order was delayed because of a system error on our side. The refund has been processed and will arrive in 3-5 days. We cannot offer further compensation. Let us know if you have questions.'", "output": "Thank you for your patience—we’re truly sorry your order was delayed due to a system error on our end. That’s on us, and we appreciate your understanding. Your refund has been processed and should reach you within 3–5 business days. While we’re unable to offer additional compensation at this time, we’re here if you have any questions or need further help. Thank you again for giving us the chance to make this right.", "latency_ms": 15247, "cost": 0.000036001, "task_score": 8, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 8, "violates": false, "reasoning": "Warm, accountable, retains facts, under 90 words, minor slight embellishment ('chance to make this right') but factually consistent and clear." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response perfectly captures the required warm tone, takes full responsibility, includes all original facts, and stays well under the 90-word limit." }, { "judge": "openai/gpt-5.6-terra", "score": 5, "violates": true, "reasoning": "Warm, accountable, and clear, with all core information retained. However, it changes “3–5 days” to “3–5 business days,” which slightly alters the stated refund timeframe." } ], "machine_checks": { "max_words": 90 }, "machine_violation": false, "machine_reasons": [] }, { "id": "w5", "name": "Headlines", "prompt": "Write 5 headline options (max 9 words each) for a blog post about how small restaurants can use AI to reduce food waste. Mix: 2 practical, 2 curiosity-driven, 1 with a number.", "output": "Here are 5 headline options for the blog post, following the specified mix:\n\n1. **Practical:** Cut Food Waste with Simple AI Tools \n2. **Practical:** AI Helps Small Restaurants Save on Ingredients \n3. **Curiosity-driven:** Can AI Predict Your Restaurant’s Leftovers? \n4. **Curiosity-driven:** The Secret Ingredient? AI for Less Waste \n5. **Number:** 5 Ways AI Slashes Restaurant Food Waste", "latency_ms": 6612, "cost": 0.000084037, "task_score": 9, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 9, "violates": false, "reasoning": "Meets requirements: correct mix, word counts under 9, clear and useful headlines with minimal imperfections." }, { "judge": "google/gemini-3.1-pro-preview", "score": 9, "violates": false, "reasoning": "The response perfectly follows all instructions, providing exactly 5 headlines under 9 words each with the requested mix. The headlines are clear, useful, and accurate." }, { "judge": "openai/gpt-5.6-terra", "score": 10, "violates": false, "reasoning": "Provides exactly five clear headline options. The mix is correct: two practical, two curiosity-driven, and one numbered. Each headline is within nine words, relevant to small restaurants, AI, and food-waste reduction." } ], "machine_checks": null, "machine_violation": false, "machine_reasons": [] }, { "id": "c1", "name": "Bug fix", "prompt": "This JavaScript function should return the median of a numeric array but gives wrong answers for even-length arrays and mutates the input. Fix both issues, return only the corrected function with a one-line explanation:\n\nfunction median(arr) {\n arr.sort();\n const mid = Math.floor(arr.length / 2);\n return arr[mid];\n}", "output": "```javascript\nfunction median(arr) {\n const sorted = [...arr].sort((a, b) => a - b);\n const mid = Math.floor(sorted.length / 2);\n return sorted.length % 2 === 0 ? (sorted[mid - 1] + sorted[mid]) / 2 : sorted[mid];\n}\n```\n**Fix:** Create a sorted copy to avoid mutation, add numeric comparator, and handle even-length arrays by averaging the two middle elements.", "latency_ms": 14631, "cost": 0.0000211169, "task_score": 10, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 9, "violates": false, "reasoning": "Correct fix for mutation and even-length median, with concise one-line explanation as requested." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response perfectly fixes the mutation, numeric sorting, and even-length issues. It strictly follows the constraint to provide only the corrected function and a one-line explanation." }, { "judge": "openai/gpt-5.6-terra", "score": 10, "violates": false, "reasoning": "Correctly avoids mutation via a copied array, uses numeric sorting, and averages the two middle values for even lengths. It provides only the corrected function and a concise one-line explanation." } ], "machine_checks": null, "machine_violation": false, "machine_reasons": [] }, { "id": "c2", "name": "Small feature", "prompt": "Write a Python function `chunk_invoices(invoices, max_total)` that takes a list of dicts like {'id': 'A1', 'amount': 120.5} and groups them into batches where each batch's summed amount does not exceed max_total. A single invoice larger than max_total goes in its own batch. Preserve order. Include 3 test cases using assert.", "output": "Here's a Python function that groups invoices into batches under the given constraints, along with three test cases using assertions.\n\n```python\ndef chunk_invoices(invoices, max_total):\n \"\"\"\n Groups a list of invoice dicts into batches.\n Each batch's summed amount does not exceed max_total, except for individual\n invoices that already exceed max_total (they go in their own batch).\n Order of invoices is preserved.\n \"\"\"\n batches = []\n current_batch = []\n current_sum = 0.0\n\n for inv in invoices:\n amount = inv['amount']\n if amount > max_total:\n # Large invoice goes alone\n if current_batch:\n batches.append(current_batch)\n current_batch = []\n current_sum = 0.0\n batches.append([inv])\n else:\n # Normal invoice\n if current_sum + amount > max_total:\n batches.append(current_batch)\n current_batch = []\n current_sum = 0.0\n current_batch.append(inv)\n current_sum += amount\n\n if current_batch:\n batches.append(current_batch)\n\n return batches\n\n\n# ---------- Test cases ----------\nif __name__ == \"__main__\":\n # Test 1: Basic case with mixed amounts\n invoices1 = [\n {'id': 'A1', 'amount': 120.5},\n {'id': 'A2', 'amount': 80.0},\n {'id': 'A3', 'amount': 50.0},\n {'id': 'A4', 'amount': 100.0}\n ]\n result1 = chunk_invoices(invoices1, 200.0)\n # Expected: [ [A1,A2] (200.5? wait 120.5+80=200.5 >200, so A1 alone? Let's recalc)\n # Actually 120.5+80=200.5 >200 => batch1: [A1]; then A2+50=130 <=200 => [A2,A3]; then A4 alone =100 <=200 => [A4]\n # So expected: [ [A1], [A2,A3], [A4] ]\n assert result1 == [ [{'id': 'A1', 'amount': 120.5}],\n [{'id': 'A2', 'amount': 80.0}, {'id': 'A3', 'amount': 50.0}],\n [{'id': 'A4', 'amount': 100.0}] ]\n\n # Test 2: Single invoice larger than max_total\n invoices2 = [\n {'id': 'B1', 'amount': 500.0},\n {'id': 'B2', 'amount': 40.0}\n ]\n result2 = chunk_invoices(invoices2, 100.0)\n # B1 alone (500 > 100), then B2 alone (40 <= 100 but cannot combine with previous)\n # Expected: [ [B1], [B2] ]\n assert result2 == [ [{'id': 'B1', 'amount': 500.0}],\n [{'id': 'B2', 'amount': 40.0}] ]\n\n # Test 3: Empty list\n invoices3 = []\n result3 = chunk_invoices(invoices3, 100.0)\n assert result3 == []\n\n print(\"All tests passed.\")\n```", "latency_ms": 11365, "cost": 0.000369036, "task_score": 8, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 8, "violates": false, "reasoning": "Correct implementation and passing tests, though comments are messy and verbose, slightly hurting clarity for a non-technical reader." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The function correctly implements the batching logic, handles edge cases like oversized invoices and empty lists, preserves order, and includes the requested 3 assert-based test cases." }, { "judge": "openai/gpt-5.6-terra", "score": 8, "violates": false, "reasoning": "Correct greedy, order-preserving batching; oversized invoices are isolated and three asserts are included. The function meets requirements. Minor polish issue: the first test contains distracting self-correcting commentary, reducing clarity" } ], "machine_checks": null, "machine_violation": false, "machine_reasons": [] }, { "id": "c3", "name": "Explain code", "prompt": "Explain to a junior developer, in under 150 words, what this code does and one risk of using it:\n\nconst cache = new Map();\nfunction memo(fn) {\n return (...args) => {\n const k = JSON.stringify(args);\n if (!cache.has(k)) cache.set(k, fn(...args));\n return cache.get(k);\n };\n}", "output": "This code creates a **memoization** utility. It wraps a function `fn` so that when called with the same arguments, it returns the cached result instead of recomputing. The cache is a global `Map` keyed by the JSON-stringified arguments. If the key doesn’t exist, it calls `fn`, stores the result, and returns it.\n\n**Risk:** The cache is **unbounded**—it grows indefinitely with every unique argument set, potentially causing memory leaks in long-running applications. Also, `JSON.stringify` can produce collisions (e.g., `{a:1, b:2}` vs `{b:2, a:1}`) or fail on circular objects, leading to incorrect caching or runtime errors. Always consider cache eviction policies (e.g., LRU) and key serialization robustness.", "latency_ms": 2730, "cost": 0.000059492, "task_score": 8, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 8, "violates": false, "reasoning": "Accurate, clear explanation with valid risk; slightly over emphasis but concise and correct. Word count appears within limit." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response perfectly explains the code and its risks to a junior developer. It is accurate, clear, concise, and well under the 150-word limit." }, { "judge": "openai/gpt-5.6-terra", "score": 7, "violates": false, "reasoning": "Correctly explains memoization and identifies the unbounded global cache as a valid risk. However, the stated collision example is inaccurate: differing object property order produces different JSON strings, causing cache misses rather than" } ], "machine_checks": { "max_words": 150 }, "machine_violation": false, "machine_reasons": [] }, { "id": "c4", "name": "SQL query", "prompt": "Given tables orders(id, customer_id, created_at, total) and customers(id, name, country), write a single SQL query returning each country's top 3 customers by lifetime spend in 2025, with columns country, name, total_spend, rank. Use a window function. Standard PostgreSQL.", "output": "```sql\nWITH customer_spend AS (\n SELECT \n c.country,\n c.name,\n SUM(o.total) AS total_spend\n FROM customers c\n JOIN orders o ON c.id = o.customer_id\n WHERE o.created_at >= '2025-01-01' \n AND o.created_at < '2026-01-01'\n GROUP BY c.id, c.country, c.name\n),\nranked AS (\n SELECT \n country,\n name,\n total_spend,\n RANK() OVER (PARTITION BY country ORDER BY total_spend DESC) AS rank\n FROM customer_spend\n)\nSELECT country, name, total_spend, rank\nFROM ranked\nWHERE rank <= 3\nORDER BY country, rank;\n```", "latency_ms": 14555, "cost": 0.00015691284, "task_score": 10, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 9, "violates": false, "reasoning": "Correct, uses window function, filters 2025, groups by customer, top 3 per country, well-formatted and clear." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The query perfectly addresses the prompt, correctly using CTEs, a window function, and proper date filtering to find the top 3 customers per country by 2025 spend." }, { "judge": "openai/gpt-5.6-terra", "score": 10, "violates": false, "reasoning": "Correct PostgreSQL query: filters 2025 orders, aggregates spend per customer, ranks within each country using a window function, returns ranks 1–3, and includes all required columns." } ], "machine_checks": null, "machine_violation": false, "machine_reasons": [] }, { "id": "c5", "name": "Regex", "prompt": "Write a regex that matches UK postcodes like 'SW1A 1AA', 'M1 1AE', 'B33 8TH' (allow lowercase and optional space), and a one-line JavaScript example using it to validate a form field. Briefly note one edge case your regex does NOT handle.", "output": "**Regex:** \n`/^[A-Za-z]{1,2}\\d{1,2}[A-Za-z]?\\s?\\d[A-Za-z]{2}$/`\n\nThis matches:\n- 1–2 letters (the postcode area)\n- 1–2 digits (the district)\n- an optional extra letter (for postcodes like `SW1A`)\n- an optional space\n- one digit followed by exactly two letters (the inward code)\n\n**One-line JavaScript validation example (e.g., on form submit):** \n```js\ndocument.getElementById('postcode').addEventListener('input', function() { this.style.borderColor = /^[A-Za-z]{1,2}\\d{1,2}[A-Za-z]?\\s?\\d[A-Za-z]{2}$/.test(this.value) ? 'green' : 'red'; });\n```\n\n**One edge case this regex does NOT handle:** \nIt accepts `Q1 1AA`, `V1 1AA`, or `X1 1AA`, even though the letters `Q`, `V`, and `X` are never used as the first character of a valid UK postcode.", "latency_ms": 13877, "cost": 0.000427326, "task_score": 8, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 7, "violates": false, "reasoning": "Correct regex and JS example, valid edge case noted. Minor issue: JS not strictly one-line in spirit though technically one statement; overall solid and clear." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response provides a solid simplified regex for UK postcodes, a correct one-line JavaScript validation example, and accurately identifies a valid edge case (invalid starting letters). All instructions were followed perfectly." }, { "judge": "openai/gpt-5.6-terra", "score": 8, "violates": false, "reasoning": "It matches all supplied examples, lowercase, and no-space variants, with a valid one-line JavaScript example and a relevant limitation. It is slightly overpermissive for UK formats (for example, it permits invalid outward-code shapes) and \\" } ], "machine_checks": null, "machine_violation": false, "machine_reasons": [] }, { "id": "r1", "name": "Multi-step logic", "prompt": "A bakery sells loaves at £3.20. Ingredients cost £1.10/loaf, labour £0.90/loaf, fixed costs £480/week. They sell 450 loaves/week. A supplier offers ingredients at £0.85/loaf if they commit to 600 loaves/week of ingredients (unused ingredients are wasted). Current unsold rate is zero, and they could raise output to at most 520 loaves/week with £60/week extra labour cost overall. Should they take the deal? Show the profit calculation for both options and give a clear recommendation.", "output": "We need to compare **current profit** with **new profit** if they take the supplier's deal.\n\n---\n\n## Current Situation\n\n**Revenue:**\n- Price per loaf: £3.20 \n- Loaves sold: 450 \n\\[\n\\text{Revenue} = 450 \\times 3.20 = £1{,}440\n\\]\n\n**Variable costs (ingredients + labour):**\n- Ingredients: £1.10/loaf \n- Labour: £0.90/loaf \n- Total variable cost per loaf = £2.00 \n- For 450 loaves: \n\\[\n\\text{Variable cost} = 450 \\times 2.00 = £900\n\\]\n\n**Fixed costs:** £480/week \n\n**Current profit:**\n\\[\n1{,}440 - 900 - 480 = £60\n\\]\n\n---\n\n## Option: Take the deal\n\n### New conditions:\n- Ingredients cost: £0.85/loaf (but must buy for 600 loaves worth, even if only using some)\n- Maximum output: **520 loaves/week**\n- Extra labour cost: £60/week overall (not per loaf — this means total labour cost for the bakery changes)\n\nWe need to decide how many loaves to produce and sell up to 520.\n\n**Best case:** Produce and sell **520 loaves** (since demand is zero unsold now, we assume all 520 can be sold if produced).\n\n### Costs with deal (for 520 loaves):\n\n**Ingredients:**\n- Must buy for 600 loaves at £0.85/loaf \n\\[\n600 \\times 0.85 = £510\n\\]\n\n**Labour:**\n- Original labour cost for 450 loaves was \\(450 \\times 0.90 = £405\\) \n- Extra labour cost £60/week overall \n- For 520 loaves, we take original labour cost for 450 loaves plus extra £60: \n\\[\n405 + 60 = £465\n\\] \n*(Alternative: If we consider labour cost per loaf, original 450 loaves at £0.90 gives £405. Increasing to 520 likely increases labour, but problem states £60 extra fixed overall — that's the simplest interpretation.)*\n\n**Fixed costs:** £480/week (unchanged)\n\n### Revenue from 520 loaves:\n\\[\n520 \\times 3.20 = £1{,}664\n\\]\n\n### Total costs:\n\\[\n510 \\ (\\text{ingredients}) + 465 \\ (\\text{labour}) + 480 \\ (\\text{fixed}) = £1{,}455\n\\]\n\n### New profit:\n\\[\n1{,}664 - 1{,}455 = £209\n\\]\n\n---\n\n## Comparison\n\n| Option | Profit |\n|----------------|--------|\n| Current | £60 |\n| With deal (520 loaves) | £209 |\n\nProfit increases significantly.\n\n---\n\n## Recommendation\n\n**Yes, take the deal.** \nEven though you must waste ingredients for 80 loaves (600–520), the lower ingredient cost and the ability to sell 70 more loaves per week (520 vs 450) with only a small extra labour cost increase yields a much higher profit (£209 vs £60).", "latency_ms": 74343, "cost": 0.0001212834, "task_score": 8, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 8, "violates": false, "reasoning": "Correct calculations, clear structure, reasonable interpretation of ambiguous labour cost, clear recommendation. Minor ambiguity handling but well explained." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response accurately calculates the current profit and the profit under the new deal, clearly explaining assumptions made about labour costs. The recommendation is clear and well-justified." }, { "judge": "openai/gpt-5.6-terra", "score": 4, "violates": false, "reasoning": "Current profit is correct, but deal labour is miscalculated: 520 loaves require £468 normal labour plus £60 extra, not £405 plus £60. It also assumes 520 sales from zero unsold without establishing additional demand." } ], "machine_checks": null, "machine_violation": false, "machine_reasons": [] }, { "id": "r2", "name": "Planning", "prompt": "Plan the launch week for a small online course (already recorded). Resources: one founder, a part-time VA (10h), email list of 2,000, £300 ad budget. Produce a 7-day plan, one line per day, each line naming the owner. Flag the single riskiest dependency.", "output": "**7-Day Launch Plan (Owner per line)** \n- Day 1: **Founder** – Send pre-launch teaser email to list. \n- Day 2: **VA** – Schedule and post social media content to build anticipation. \n- Day 3: **Founder** – Send launch email with cart link. \n- Day 4: **VA** – Send follow-up email to non-openers (using founder’s copy). \n- Day 5: **Founder** – Send urgency email with limited-time offer. \n- Day 6: **VA** – Respond to customer inquiries and engage on social media. \n- Day 7: **Founder** – Send cart close email with final reminder. \n\n**Single Riskiest Dependency** \n**Email list open rates** – If open rates are low (<20%), the entire launch sequence fails to drive sales, and the £300 ad budget is too small to compensate. All other activities (social media, ads) are secondary to list engagement.", "latency_ms": 33923, "cost": 0.001009824, "task_score": 6, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 6, "violates": false, "reasoning": "Clear 7-day plan with owners, addresses risk, but omits ad budget usage entirely, weakening completeness given stated resources." }, { "judge": "google/gemini-3.1-pro-preview", "score": 8, "violates": false, "reasoning": "Follows all constraints perfectly. The plan is clear and concise. However, it fails to utilize the £300 ad budget within the 7-day plan, which is a minor oversight given the provided resources." }, { "judge": "openai/gpt-5.6-terra", "score": 6, "violates": false, "reasoning": "Clear seven-day schedule with an owner on every day and one flagged risk. However, it never deploys or allocates the £300 ad budget, underuses the launch resources, and identifies open rates rather than a more controllable operational depen" } ], "machine_checks": null, "machine_violation": false, "machine_reasons": [] }, { "id": "r3", "name": "Trade-off analysis", "prompt": "A 12-person agency must choose: (A) hire a mid-level developer at £55k, or (B) contract overflow work to freelancers at roughly £400/day, expected 60 days/year. Give a recommendation in under 200 words covering cost, flexibility, quality risk, and one non-obvious factor.", "output": "**Recommendation: Option B (Freelance Contractors)** is more cost-effective and agile for a 12-person agency.\n\n**Cost:** Hiring a mid-level developer costs **£55,000/year** plus employer overhead (pension, NI, training), typically £65k–£70k total. Contracting 60 days at £400/day equals only **£24,000/year**—a saving of over £40k.\n\n**Flexibility:** Freelancers allow scaling up/down without permanent commitment. If workload drops, you stop paying. A permanent hire creates fixed cost regardless of demand, risking underutilisation.\n\n**Quality Risk:** Freelancers are vetted per project and bring specialised, up-to-date skills. A mid-level hire may require ramp-up time and may not match peak-project expertise. However, reliable freelancers can be harder to secure at short notice; maintaining a bench of 2–3 trusted contacts mitigates this.\n\n**Non-obvious factor: Team morale & culture.** A 12-person agency is tight-knit. Adding a permanent employee at £55k when workload is inconsistent can breed resentment if others feel underpaid or overburdened during slow periods. Freelancers arrive as external experts, reducing internal pressure and keeping core team dynamics stable.\n\n**Recommendation: Use freelancers now; revisit hiring only if overflow exceeds 150 days/year.**", "latency_ms": 40949, "cost": 0.000052129, "task_score": 8, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 7, "violates": false, "reasoning": "Solid, clear, covers all required points with reasonable numbers, but slightly over 200 words and cost comparison ignores freelancer's lack of other work value/knowledge continuity nuance." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response perfectly follows all instructions, including the word count constraint. It accurately compares costs, addresses flexibility and quality risk, and provides a thoughtful non-obvious factor, making it highly useful and concise." }, { "judge": "openai/gpt-5.6-terra", "score": 8, "violates": false, "reasoning": "Accurately compares £24k freelance spend with likely £65k–£70k employment cost, addresses all required factors, and gives a clear recommendation. The 150-day hiring threshold is somewhat unsupported and the morale claim is speculative, but " } ], "machine_checks": { "max_words": 200 }, "machine_violation": false, "machine_reasons": [] }, { "id": "r4", "name": "Maths word problem", "prompt": "A tank holds 2,400 litres. Pump A fills at 40 L/min. Pump B drains at 25 L/min. A runs from 09:00. B accidentally switches on at 09:20. At 10:00 B is switched off. At what time is the tank full? Show your working.", "output": "We start with an empty tank of 2,400 litres.\n\n**Step 1: From 09:00 to 09:20 (only Pump A running)** \nTime = 20 minutes \nFill rate = 40 L/min \nAmount added = \\( 40 \\times 20 = 800 \\) litres\n\n**Step 2: From 09:20 to 10:00 (both pumps running)** \nFrom 09:20 to 10:00 is 40 minutes. \nPump A fills at 40 L/min, Pump B drains at 25 L/min. \nNet fill rate = \\( 40 - 25 = 15 \\) L/min \nAmount added = \\( 15 \\times 40 = 600 \\) litres\n\nTotal in tank by 10:00 = \\( 800 + 600 = 1,400 \\) litres \nRemaining to fill = \\( 2,400 - 1,400 = 1,000 \\) litres\n\n**Step 3: After 10:00 (only Pump A running again)** \nFill rate = 40 L/min \nTime needed = \\( \\frac{1,000}{40} = 25 \\) minutes\n\n**Step 4: Final time** \n10:00 + 25 minutes = **10:25**\n\n\\[\n\\boxed{10:25}\n\\]", "latency_ms": 26817, "cost": 0.0000518609, "task_score": 10, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 9, "violates": false, "reasoning": "Correct calculation, clear step-by-step working, matches expected answer 10:25, well formatted for a non-technical reader." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response perfectly calculates the time the tank is full, showing clear, accurate, and easy-to-follow step-by-step working. No constraints were violated." }, { "judge": "openai/gpt-5.6-terra", "score": 10, "violates": false, "reasoning": "All calculations and time intervals are correct, it explicitly states the necessary empty-tank assumption, shows clear working, and gives the correct filling time of 10:25." } ], "machine_checks": null, "machine_violation": false, "machine_reasons": [] }, { "id": "r5", "name": "Catch the flaw", "prompt": "Find the flaw in this argument and explain it in under 100 words: 'Our churn dropped from 6% to 3% after we introduced the loyalty programme in March, so the programme cut churn in half. We should double the loyalty budget to cut churn to 1.5%.'", "output": "The flaw is assuming a linear, proportional relationship between budget and churn reduction. Halving churn once doesn't guarantee the same effect again; diminishing returns or external factors (e.g., seasonal trends) may be at play. The initial drop could also be due to other changes, not solely the loyalty program.", "latency_ms": 2194, "cost": 0.000049446, "task_score": 10, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 7, "violates": false, "reasoning": "Correctly identifies confounding (causation vs correlation) and unwarranted extrapolation of linear scaling; concise, under 100 words. Could mention correlation/causation more explicitly, but solid coverage." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response perfectly identifies the logical flaws (assuming linear returns and correlation vs. causation) clearly and concisely, well within the 100-word limit." }, { "judge": "openai/gpt-5.6-terra", "score": 10, "violates": false, "reasoning": "Correctly identifies both unsupported causal attribution and unjustified extrapolation from one observed change to a doubled budget. It is concise, clear, useful, and well under 100 words." } ], "machine_checks": { "max_words": 100 }, "machine_violation": false, "machine_reasons": [] }, { "id": "e1", "name": "Messy to JSON", "prompt": "Extract to JSON with keys name, company, phone, email, intent:\n\n'hiya - jules moreau here from Atelier Nord (the lighting people). best number is 07700 900 457, or jules@ateliernord.fr. we're after a quote for the workshop series u mentioned, ideally b4 sept'\n\nReturn only valid JSON.", "output": "{\n \"name\": \"Jules Moreau\",\n \"company\": \"Atelier Nord\",\n \"phone\": \"07700 900 457\",\n \"email\": \"jules@ateliernord.fr\",\n \"intent\": \"Requesting a quote for the workshop series, ideally before September\"\n}", "latency_ms": 3489, "cost": 0.0000167559, "task_score": 10, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 9, "violates": false, "reasoning": "Accurate extraction, correct JSON structure, clean formatting, no extraneous text." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response perfectly extracts the requested information into a valid JSON object with the exact keys specified, and contains no extra text." }, { "judge": "openai/gpt-5.6-terra", "score": 10, "violates": false, "reasoning": "All requested fields are accurately extracted, with a clear intent summary preserving the timing preference. The response is valid JSON and contains no extra text." } ], "machine_checks": { "must_parse_json": true }, "machine_violation": false, "machine_reasons": [] }, { "id": "e2", "name": "Table from prose", "prompt": "Turn this into a markdown table with columns Product, Q1, Q2, Change:\n\n'The Alpha line did 14,200 units in Q1 and 15,800 in Q2. Beta slipped from 9,100 to 7,400. The new Gamma launched mid-Q2 with 3,300 units (no Q1 sales). Delta held flat at 5,000 both quarters.'\n\nInclude a Change column as a percentage to one decimal (write n/a where undefined).", "output": "| Product | Q1 | Q2 | Change |\n|---|---:|---:|---:|\n| Alpha | 14,200 | 15,800 | 11.3% |\n| Beta | 9,100 | 7,400 | -18.7% |\n| Gamma | n/a | 3,300 | n/a |\n| Delta | 5,000 | 5,000 | 0.0% |", "latency_ms": 3445, "cost": 0.00010359, "task_score": 10, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 9, "violates": false, "reasoning": "Accurate calculations, correct format, follows instructions precisely, clear and concise table." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response perfectly follows all instructions, accurately calculates the percentages to one decimal place, handles the undefined change correctly with 'n/a', and formats the output as a clean markdown table." }, { "judge": "openai/gpt-5.6-terra", "score": 10, "violates": false, "reasoning": "All figures match the source. Percentage changes are correctly calculated and rounded to one decimal; Gamma correctly uses n/a because Q1 sales are undefined. The markdown table has all required columns and is clear." } ], "machine_checks": null, "machine_violation": false, "machine_reasons": [] }, { "id": "e3", "name": "Contact details", "prompt": "List every person mentioned below with their role and organisation, one line each in the format Name - Role - Org. If a field is unknown write unknown:\n\n'Following the review, Dr Amara Okafor (Chief Data Officer, Halcyon Health) will hand over to Ben Tran, who joins as interim CDO from Meridian Labs. Legal sign-off sits with Priya Shah at Halcyon; the external audit remains with T. Lindqvist.'", "output": "Dr Amara Okafor - Chief Data Officer - Halcyon Health \nBen Tran - interim CDO - Meridian Labs \nPriya Shah - unknown (legal sign-off) - Halcyon \nT. Lindqvist - unknown (external audit) - unknown", "latency_ms": 5650, "cost": 0.0000158263, "task_score": 6, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 6, "violates": false, "reasoning": "Ben Tran's org likely should be Halcyon Health (joining as interim CDO there), not Meridian Labs. Priya Shah's role listed as unknown despite clear 'legal sign-off' context is imprecise. Format mostly followed." }, { "judge": "google/gemini-3.1-pro-preview", "score": 8, "violates": false, "reasoning": "The response correctly identifies all individuals and follows the format, but includes extra context in parentheses next to 'unknown', slightly deviating from the strict instruction to just write 'unknown'." }, { "judge": "openai/gpt-5.6-terra", "score": 5, "violates": true, "reasoning": "All four people, roles, and organisations are identified accurately. However, unknown role fields must be written exactly as “unknown”; adding parenthetical descriptions breaches the explicit instruction." } ], "machine_checks": null, "machine_violation": false, "machine_reasons": [] }, { "id": "e4", "name": "Key facts", "prompt": "Extract exactly 5 key facts as bullets (each under 15 words) from:\n\n'The council approved the harbour redevelopment on 12 June by 7 votes to 2. Phase one, costing £4.6m, begins in October and includes the fish market roof. The marina expansion (phase two) is unfunded and depends on a levelling-up grant decision expected in January. Local traders get first refusal on the 14 new retail units. Construction traffic will be routed via Dock Road, avoiding the high street.'", "output": "- Council approved harbour redevelopment on 12 June by 7-2 vote.\n- Phase one costs £4.6m, begins October, includes fish market roof.\n- Marina expansion (phase two) unfunded, depends on January grant decision.\n- Local traders get first refusal on 14 new retail units.\n- Construction traffic routed via Dock Road, avoiding high street.", "latency_ms": 2807, "cost": 0.0000476672, "task_score": 10, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 10, "violates": false, "reasoning": "Exactly 5 accurate bullets, each under 15 words, concise and covers all key facts correctly." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response perfectly extracts exactly 5 key facts, with each bullet accurately reflecting the text and strictly remaining under the 15-word limit." }, { "judge": "openai/gpt-5.6-terra", "score": 10, "violates": false, "reasoning": "Exactly five bullets, each under 15 words. All key facts are accurately captured, including vote, costs, timing, funding dependency, retail priority, and traffic routing." } ], "machine_checks": null, "machine_violation": false, "machine_reasons": [] }, { "id": "e5", "name": "Schema compliance", "prompt": "Convert to JSON matching exactly this schema: {\"event\": string, \"date\": \"YYYY-MM-DD\", \"venue\": string, \"capacity\": number, \"speakers\": [{\"name\": string, \"topic\": string}], \"sold_out\": boolean}\n\n'AI in Retail Summit happens March 14th 2026 at the Baltic Exchange (holds 320). Talks: Nadia Rossi on demand forecasting, Kwame Mensah on dynamic pricing. Tickets still available.'\n\nReturn only the JSON.", "output": "{\n \"event\": \"AI in Retail Summit\",\n \"date\": \"2026-03-14\",\n \"venue\": \"Baltic Exchange\",\n \"capacity\": 320,\n \"speakers\": [\n {\"name\": \"Nadia Rossi\", \"topic\": \"demand forecasting\"},\n {\"name\": \"Kwame Mensah\", \"topic\": \"dynamic pricing\"}\n ],\n \"sold_out\": false\n}", "latency_ms": 3031, "cost": 0.0000889, "task_score": 10, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 10, "violates": false, "reasoning": "Accurate, matches schema exactly, correctly formatted JSON, concise and correct." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response perfectly extracts the information into the requested JSON schema and strictly follows the constraint to return only the JSON." }, { "judge": "openai/gpt-5.6-terra", "score": 10, "violates": false, "reasoning": "Matches the required schema exactly, correctly converts the date to ISO format, preserves all event details, uses numeric capacity and boolean availability status, and returns only valid JSON." } ], "machine_checks": null, "machine_violation": false, "machine_reasons": [] }, { "id": "i1", "name": "Format constraints", "prompt": "Describe how photosynthesis works in exactly 3 sentences. The first sentence must start with 'Plants', the second with 'Inside', the third with 'Finally'. No sentence may exceed 20 words.", "output": "Plants use sunlight, water, and carbon dioxide to create glucose and oxygen. Inside chloroplasts, chlorophyll absorbs light energy to split water molecules. Finally, carbon dioxide is converted into sugar through the Calvin cycle.", "latency_ms": 2544, "cost": 0.00001143, "task_score": 10, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 9, "violates": false, "reasoning": "Meets all structural constraints, accurate content, concise, within word limits, correct starts." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response perfectly follows all constraints, including exact sentence count, specific starting words, and word limits per sentence. The explanation of photosynthesis is accurate, clear, and concise." }, { "judge": "openai/gpt-5.6-terra", "score": 10, "violates": false, "reasoning": "Exactly three sentences; required starting words are correct; each sentence is under 20 words. The explanation is accurate, clear, concise, and suitable for a non-technical reader." } ], "machine_checks": null, "machine_violation": false, "machine_reasons": [] }, { "id": "i2", "name": "Word limit", "prompt": "Explain the difference between a lease and a licence for UK commercial property in exactly 50 words. Count carefully - exactly 50.", "output": "A lease grants exclusive possession, a proprietary interest, and statutory security of tenure. A licence is a personal permission to occupy, revocable and without exclusive possession. For UK commercial property, the presence of exclusive possession is the crucial distinction that determines whether an arrangement is a lease or a licence.", "latency_ms": 68888, "cost": 0.0004465664, "task_score": 9, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 9, "violates": false, "reasoning": "Accurate, clear explanation exactly 50 words as required; concise and useful." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response perfectly explains the legal distinction between a lease and a licence in the UK, focusing accurately on exclusive possession. It strictly adheres to the 50-word constraint." }, { "judge": "openai/gpt-5.6-terra", "score": 8, "violates": false, "reasoning": "Exactly 50 words. Clear and broadly accurate, correctly emphasizing exclusive possession. However, stating that every lease grants statutory security of tenure is overbroad: commercial leases can be contracted out of the Landlord and Tenant" } ], "machine_checks": { "exact_words": 50 }, "machine_violation": false, "machine_reasons": [] }, { "id": "i3", "name": "Forbidden words", "prompt": "Explain what makes coffee taste bitter, in 80-120 words, WITHOUT using any of these words: bitter, bean, roast, caffeine, acid. Do not use hyphenated or partial variants of them either.", "output": "During heating, compounds in coffee seeds undergo chemical changes. The Maillard reaction produces molecules that contribute to a sharp, harsh flavor. Additionally, certain lactones form from chlorogenic compounds, and prolonged heating creates phenylindanes, which intensify this taste. The degree of heating influences how many of these substances develop, with darker heating yielding more. These compounds interact with taste receptors, resulting in the characteristic sharp sensation many people notice in coffee.", "latency_ms": 11443, "cost": 0.00007791966, "task_score": 5, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 8, "violates": false, "reasoning": "Accurate, avoids all banned words/roots, stays within word count, clear and informative for non-technical reader." }, { "judge": "google/gemini-3.1-pro-preview", "score": 5, "violates": true, "reasoning": "The response accurately explains the chemistry behind the harsh flavor while successfully avoiding all banned words. However, it violates the length constraint, as it is only 70 words long (minimum required was 80)." }, { "judge": "openai/gpt-5.6-terra", "score": 5, "violates": true, "reasoning": "Clear, accurate explanation of heat-driven compounds and taste receptors. It avoids all prohibited terms and variants, but contains 70 words, below the required 80–120 word range." } ], "machine_checks": null, "machine_violation": false, "machine_reasons": [] }, { "id": "i4", "name": "Multi-constraint", "prompt": "Write a LinkedIn post about hiring your first apprentice. Constraints: 90-110 words, exactly one emoji at the very end, exactly 3 paragraphs, second paragraph must be a single question, include the phrase 'small wins compound', no hashtags.", "output": "Today marks a big moment: we hired our first apprentice. It’s not just about filling a seat—it’s a commitment to mentorship and to building a culture where growth is shared. I remember being an apprentice once, and that experience shaped me.\n\nWhat if the most important thing we teach isn't a skill, but the courage to ask questions and fail forward?\n\nWe'll take it one day at a time. Each small fix, each new insight, each conversation adds up. Those small wins compound into something far greater than any single project. I'm excited to see what we build together. 🔧", "latency_ms": 29692, "cost": 0.0004948888, "task_score": 10, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 9, "violates": false, "reasoning": "Meets word count (99), exactly one emoji at end, 3 paragraphs, second is a question, phrase included, no hashtags. Well-written and engaging." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response perfectly follows all instructions, including the strict word count (100 words), paragraph structure, exact phrasing, and emoji placement constraints. It is highly professional and ready to post." }, { "judge": "openai/gpt-5.6-terra", "score": 10, "violates": false, "reasoning": "Meets all constraints: 99 words, exactly three paragraphs, a single-question second paragraph, required phrase included, no hashtags, and exactly one emoji at the end. Clear, warm, professional, and LinkedIn-appropriate." } ], "machine_checks": null, "machine_violation": false, "machine_reasons": [] }, { "id": "i5", "name": "Exact structure", "prompt": "Produce a checklist for closing a small retail shop at night with EXACTLY this structure: a title line, then 3 sections headed 'Front of house', 'Back office', 'Security', each containing exactly 4 numbered items, each item 3-8 words. Nothing else before or after.", "output": "Closing Checklist: Small Retail Shop\n\n**Front of house**\n1. Tidy shelves and racks.\n2. Remove all visible trash.\n3. Turn off all display lights.\n4. Lock front entrance door.\n\n**Back office**\n1. Count and record daily cash.\n2. Shut down computer and printer.\n3. Set alarm system to \"away.\"\n4. Lock office door securely.\n\n**Security**\n1. Check all windows are locked.\n2. Verify back door is bolted.\n3. Test motion sensor lights.\n4. Arm security system before leaving.", "latency_ms": 7385, "cost": 0.00002664, "task_score": 10, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 9, "violates": false, "reasoning": "Correct structure, three sections with exactly 4 items each, word counts within 3-8, concise and clear. Minor formatting (bold, quotes) but meets constraints well." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response perfectly follows all instructions, including the exact structure, section headings, item counts, and word count constraints per item. It is highly useful, clear, and concise." }, { "judge": "openai/gpt-5.6-terra", "score": 10, "violates": false, "reasoning": "Matches the required title and three sections. Each section has exactly four numbered items, and every item contains 3–8 words. No extraneous content appears before or after." } ], "machine_checks": null, "machine_violation": false, "machine_reasons": [] }, { "id": "s1", "name": "Quick answer (short)", "prompt": "In one sentence: what does VAT stand for and what is the current standard UK rate?", "output": "VAT stands for Value Added Tax, and the current standard UK rate is 20%.", "latency_ms": 2629, "cost": 0.000025036, "task_score": 10, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 9, "violates": false, "reasoning": "Accurate, concise, single sentence as requested, correctly states VAT meaning and current UK standard rate of 20%." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response perfectly answers the prompt in exactly one sentence, providing accurate information about what VAT stands for and the current standard UK rate." }, { "judge": "openai/gpt-5.6-terra", "score": 10, "violates": false, "reasoning": "Correctly expands VAT as Value Added Tax and states the current standard UK VAT rate as 20%, in exactly one clear sentence." } ], "machine_checks": null, "machine_violation": false, "machine_reasons": [] }, { "id": "s2", "name": "Instant classification", "prompt": "Classify each as SPAM or NOT SPAM, output only two-column lines: 'You've won a £500 voucher click here' / 'Your Tesco order 8812 is ready for collection' / 'URGENT your account will be closed verify now' / 'Minutes from Thursday's board meeting attached'.", "output": "You've won a £500 voucher click here / SPAM\nYour Tesco order 8812 is ready for collection / NOT SPAM\nURGENT your account will be closed verify now / SPAM\nMinutes from Thursday's board meeting attached / NOT SPAM", "latency_ms": 1814, "cost": 0.00002506, "task_score": 10, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 9, "violates": false, "reasoning": "Correct classifications, matches required two-column format consistently, clear and concise." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response perfectly follows all instructions, correctly classifying each phrase and formatting the output exactly as requested with only two-column lines." }, { "judge": "openai/gpt-5.6-terra", "score": 10, "violates": false, "reasoning": "All four messages are classified appropriately, and the response uses only two-column lines with no extra text." } ], "machine_checks": null, "machine_violation": false, "machine_reasons": [] }, { "id": "s3", "name": "Short translation", "prompt": "Translate to French, keeping the informal tone: 'Hey, we're running 10 minutes late - grab us a table if you get there first?'", "output": "Salut, on a 10 minutes de retard – prends-nous une table si t’arrives avant nous ?", "latency_ms": 10564, "cost": 0.00006602148, "task_score": 9, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 9, "violates": false, "reasoning": "Accurate, informal, natural French translation preserving tone and meaning; concise and correct." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "Flawless translation that perfectly captures the informal tone of the original English sentence using natural phrasing ('on', 't'arrives')." }, { "judge": "openai/gpt-5.6-terra", "score": 8, "violates": false, "reasoning": "Accurate and informal overall. “Prends-nous une table” is understandable but slightly anglicized/less natural than “trouve-nous une table” or “garde-nous une table” in French." } ], "machine_checks": null, "machine_violation": false, "machine_reasons": [] }, { "id": "s4", "name": "Medium generation", "prompt": "Write a 150-word 'About us' section for a family-run garden centre in Yorkshire founded in 1987, now run by the founders' daughter, known for rare perennials and a small cafe.", "output": "**About Us**\n\nNestled in the heart of Yorkshire, our family-run garden centre has been cultivating beauty since 1987. Founded by devoted horticulturists, it began as a humble passion project, nurtured by their love for rare and unusual plants. Today, their daughter carries the legacy forward, blending time-honoured expertise with a fresh, welcoming spirit.\n\nWe are renowned for our exceptional collection of rare perennials – treasures sourced from specialist growers and our own nursery. Whether you seek a unique cottage garden gem or a hardy specimen for challenging spots, our knowledgeable team is here to guide you.\n\nAfter exploring our beds, unwind in our small, homely café. Savour freshly brewed coffee, homemade cakes, and hearty Yorkshire fare, all served with a smile. Every plant, every cup, and every conversation reflects our family’s commitment to quality, sustainability, and community.\n\nVisit us – where Yorkshire’s heritage meets a gardener’s passion.", "latency_ms": 5172, "cost": 0.0000555296, "task_score": 5, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 5, "violates": true, "reasoning": "Well-written and covers all elements, but exceeds 150-word target (~165 words), so violates explicit word count constraint." }, { "judge": "google/gemini-3.1-pro-preview", "score": 5, "violates": true, "reasoning": "The response includes all required details and is beautifully written, but it violates the strict word count constraint, coming in at 147 words instead of exactly 150." }, { "judge": "openai/gpt-5.6-terra", "score": 5, "violates": true, "reasoning": "Strong, polished and useful copy covering all requested details. However, it contains 143 words, not the required 150. Minor unsupported embellishments include an own nursery and specific café offerings." } ], "machine_checks": null, "machine_violation": false, "machine_reasons": [] }, { "id": "s5", "name": "Long generation", "prompt": "Write a detailed 400-word beginner's guide to setting up a home compost bin: location, what to add, what to avoid, how long it takes, and one common mistake.", "output": "Here is a beginner’s guide to setting up a home compost bin, covering all your requested points.\n\n### Your First Home Compost Bin: A Beginner’s Guide\n\nComposting is one of the most rewarding habits for any gardener, turning kitchen scraps into \"black gold\" for your plants. It’s easier than you think, as long as you follow a few basic rules.\n\n**1. Location, Location, Location**\nPlace your bin on bare soil to allow beneficial worms and microbes to enter. Choose a spot that is **convenient** (close to your kitchen door) but not in full, blazing sun all day. A **partially shaded** area is ideal because direct sun can dry the pile out, while deep shade can make it too cold and slow. Ensure the area has good drainage.\n\n**2. What to Add (The Ingredients)**\nThink of your compost bin as a recipe. You need two main ingredients:\n- **Greens (Nitrogen):** These are wet materials that rot quickly. Examples: fruit and vegetable scraps, coffee grounds, tea bags, fresh grass clippings.\n- **Browns (Carbon):** These are dry, woody materials that provide structure and energy. Examples: dried leaves, straw, shredded cardboard, paper, eggshells, small twigs.\n\nThe golden rule is to aim for a ratio of roughly **2-3 parts Browns to 1 part Greens**. If it smells bad, you need more browns. If it’s not breaking down, you need more greens.\n\n**3. What to Avoid**\nNever add the following: **Meat, fish, bones, dairy products, cooking oils, or fats.** These items attract pests (rats, raccoons, flies) and create foul odors. Also avoid diseased plants, weeds that have gone to seed, and pet or human waste (can contain pathogens).\n\n**4. How Long It Takes**\nThis depends on your effort. A \"cold,\" lazy pile, where you just add scraps and wait, will take **6 months to 2 years**. A \"hot,\" actively managed pile (turned every few days, kept moist, with the correct ratio) can produce finished compost in **3 to 4 months**. You are waiting for it to look like dark, crumbly soil with a pleasant earthy smell.\n\n**5. One Common Mistake for Beginners**\n\nThe biggest mistake is **making your pile too wet or too \"green.\"**\n\nBeginners often add lots of vegetable scraps (greens) but forget the browns (leaves, cardboard). This creates a slimy, smelly, anaerobic mess that attracts flies and doesn't break down properly. **The fix is simple:** whenever you add a bucket of kitchen scraps, add a bucket or two of dry browns (like shredded paper or dry leaves) on top. If it’s already stinky, just stir in more browns to soak up the moisture.\n\nStart small, be consistent with your layers, and soon you’ll be amazed at how nature turns your waste into beautiful soil.", "latency_ms": 10149, "cost": 0.000186816, "task_score": 5, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 7, "violates": false, "reasoning": "Accurate, covers all requested points clearly, well organized. Slightly over 400 words (likely ~480) but no strict count check possible; minor length deviation, otherwise strong and useful." }, { "judge": "google/gemini-3.1-pro-preview", "score": 5, "violates": true, "reasoning": "Excellent, accurate guide covering all required points clearly and concisely. However, it violates the explicit 400-word constraint, coming in at approximately 358 words." }, { "judge": "openai/gpt-5.6-terra", "score": 5, "violates": true, "reasoning": "Clear, well-structured, and covers every requested topic accurately overall. Minor oversimplifications include classifying eggshells as browns and implying frequent turning alone enables hot compost. It exceeds the explicit 400-word require" } ], "machine_checks": null, "machine_violation": false, "machine_reasons": [] } ], "recapped_at": "2026-08-16T09:03:03.012Z", "recap_note": "Machine constraint caps applied retroactively under protocol judge-2026-08b; judge verdicts unchanged, task scores capped where a deterministic check failed." }