{ "entity": "deepseek-v4-pro", "entity_type": "model", "category": "Best-value API", "suite": "suite-2026-07", "model": "deepseek/deepseek-v4-pro", "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": 88, "caps": 9, "cost_usd": 0.4246, "started_at": "2026-08-11T16:52:59.532Z", "finished_at": "2026-08-11T16:56:07.650Z", "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 bookkeeping month for [Brewery Name]?\n\nHi [Name],\n\nI’m [Name], owner of [Firm], a six-person accounting practice based nearby. We help a few breweries with bookkeeping, duty returns, and VAT.\n\nI’d like to offer [Brewery Name] a free first month of bookkeeping—no commitment, no cost.\n\nIf you’re curious, I can pop by for a quick chat. Just reply to this email and we’ll arrange a time.\n\nBest,\n[Name]\n[Firm]\n[Phone]", "latency_ms": 37314, "cost": 0.00368332608, "task_score": 10, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 8, "violates": false, "reasoning": "Meets word limit, clear CTA, friendly/professional tone, no buzzwords. Minor: could be slightly more brewery-specific, but overall strong and concise." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "Flawless response. It perfectly meets the word count constraint, adopts the correct persona and tone, includes a clear CTA, and avoids buzzwords. Highly useful for a busy professional." }, { "judge": "openai/gpt-5.6-terra", "score": 10, "violates": false, "reasoning": "Meets all requirements: under 120 words, clearly from a six-person UK accounting firm, relevant brewery services, free first-month trial, friendly professional tone, no buzzwords, and one clear reply-based call to action." } ] }, { "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": "Crush your workout and recover faster with a bottle engineered for performance. Double-wall vacuum insulation keeps water ice-cold for 24 hours, or coffee hot for 12. The 750ml capacity is a perfect post-session refill; its leakproof design lets you toss it in your gym bag worry-free. It fits your car cup holder, so hydration travels from the gym floor to your commute. No sweat, no spills—pure function.", "latency_ms": 20453, "cost": 0.001601275, "task_score": 7, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 7, "violates": false, "reasoning": "Meets requirements, on-target audience, avoids cliché, no word count check shows ~70 words fits range; minor stylistic filler but solid quality." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "Hits all required features, perfectly targets gym-goers, avoids the banned cliché, and falls exactly within the 60-80 word limit (67 words). Excellent clarity and tone." }, { "judge": "openai/gpt-5.6-terra", "score": 7, "violates": false, "reasoning": "Meets the 60–80 word range and covers capacity, insulation times, leakproofing, cup-holder fit, and gym use. However, it omits stainless steel and makes an unsupported “recover faster” claim." } ] }, { "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": "- Launch slipped ~3 weeks due to a supplier issue (per Marc). \n- Sarah wants to push the email campaign now; Tom recommends waiting. \n- Budget is $8K over, driven mainly by the packaging redo. \n- Decision needed: Notify retail partners now or after the new date is confirmed? \n- Warehouse temp must be hired before the August rush. Next meeting: Tuesday.", "latency_ms": 11107, "cost": 0.00074385, "task_score": 10, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 9, "violates": false, "reasoning": "Accurate, concise, exactly 5 bullets, captures all key points clearly for a director in 20 seconds." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response perfectly follows the instructions, providing exactly 5 clean, concise bullets that accurately summarize the messy notes. It is highly useful for a busy director." }, { "judge": "openai/gpt-5.6-terra", "score": 10, "violates": false, "reasoning": "Exactly five concise bullets. Accurately captures delay, campaign disagreement, budget overrun, retail-partner decision, hiring urgency, and next meeting." } ] }, { "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": "I’m so sorry—your order was delayed due to a system error on our side, and that’s completely on us. We’ve processed your refund, which should reach you in 3–5 days. While we’re unable to offer additional compensation, please know we’re taking this seriously. If you have any questions at all, I’m here to help.", "latency_ms": 9277, "cost": 0.00020097, "task_score": 10, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 8, "violates": false, "reasoning": "Warm, apologetic, keeps facts, under 90 words (57 words), clear and concise; minor stylistic redundancy but overall strong." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response perfectly follows all instructions. It is warm, takes full responsibility, retains all original facts, and is well under the 90-word limit. The tone is highly professional and empathetic." }, { "judge": "openai/gpt-5.6-terra", "score": 10, "violates": false, "reasoning": "Warm, accountable, and clear. It preserves all required facts: system error, refund processed, 3–5 day timeframe, no further compensation, and invitation for questions. It is well under 90 words and professionally phrased." } ] }, { "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": "- How Small Restaurants Can Use AI to Reduce Waste \n- Practical AI Tools to Minimize Small Restaurant Food Waste \n- What If Your Restaurant’s AI Could Stop Food Waste? \n- Is AI the Secret to Halving Your Restaurant’s Waste? \n- 5 Ways AI Cuts Food Waste for Small Restaurants", "latency_ms": 30128, "cost": 0.0031347492, "task_score": 10, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 8, "violates": false, "reasoning": "Meets count, word limit, and mix requirements well; headlines clear and relevant. Minor: curiosity headlines slightly overlap with practical tone, but overall strong." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response perfectly follows all instructions, providing exactly 5 headlines that meet the 9-word limit and the requested mix of styles. The headlines are clear, engaging, and highly useful." }, { "judge": "openai/gpt-5.6-terra", "score": 10, "violates": false, "reasoning": "All five headlines meet the nine-word maximum and requested mix: two practical, two curiosity-driven, and one numbered. They are clear, relevant, concise, and suitable for small-restaurant readers." } ] }, { "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 ? sorted[mid] : (sorted[mid - 1] + sorted[mid]) / 2;\n}\n```\nFixes: copies array to prevent mutation, uses numeric sort, and averages two middle values for even-length arrays.", "latency_ms": 6299, "cost": 0.0003958825, "task_score": 10, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 10, "violates": false, "reasoning": "Correctly fixes both issues, avoids mutation, uses numeric sort, handles even-length correctly, concise explanation as requested." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response perfectly fixes both issues (and the implicit numeric sort bug), provides only the function and a concise one-line explanation as requested." }, { "judge": "openai/gpt-5.6-terra", "score": 10, "violates": false, "reasoning": "Correctly avoids mutation by copying, uses numeric sorting, and computes the average of the two middle values for even lengths. It provides only the corrected function plus a one-line explanation, as requested." } ] }, { "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 chunks invoices into batches based on a maximum total amount:\n\n```python\ndef chunk_invoices(invoices, max_total):\n \"\"\"\n Groups invoices into batches where each batch's summed amount does not exceed max_total.\n A single invoice larger than max_total goes in its own batch.\n Preserves the original order of invoices.\n \n Args:\n invoices: List of dicts with 'id' and 'amount' keys\n max_total: Maximum total amount allowed per batch\n \n Returns:\n List of batches, where each batch is a list of invoice dicts\n \"\"\"\n batches = []\n current_batch = []\n current_total = 0.0\n \n for invoice in invoices:\n amount = invoice['amount']\n \n # If a single invoice exceeds max_total, put it in its own batch\n if amount > max_total:\n # Save current batch if not empty\n if current_batch:\n batches.append(current_batch)\n current_batch = []\n current_total = 0.0\n \n # Add the large invoice as its own batch\n batches.append([invoice])\n continue\n \n # Check if adding this invoice would exceed max_total\n if current_total + amount > max_total:\n # Start a new batch\n batches.append(current_batch)\n current_batch = [invoice]\n current_total = amount\n else:\n # Add to current batch\n current_batch.append(invoice)\n current_total += amount\n \n # Don't forget the last batch\n if current_batch:\n batches.append(current_batch)\n \n return batches\n\n\n# Test cases\ndef test_chunk_invoices():\n # Test case 1: Normal case with mixed amounts\n invoices1 = [\n {'id': 'A1', 'amount': 50.0},\n {'id': 'A2', 'amount': 30.0},\n {'id': 'A3', 'amount': 40.0},\n {'id': 'A4', 'amount': 20.0},\n {'id': 'A5', 'amount': 60.0}\n ]\n result1 = chunk_invoices(invoices1, 100.0)\n assert len(result1) == 3, f\"Expected 3 batches, got {len(result1)}\"\n assert result1[0] == [{'id': 'A1', 'amount': 50.0}, {'id': 'A2', 'amount': 30.0}], \"Batch 1 incorrect\"\n assert result1[1] == [{'id': 'A3', 'amount': 40.0}, {'id': 'A4', 'amount': 20.0}], \"Batch 2 incorrect\"\n assert result1[2] == [{'id': 'A5', 'amount': 60.0}], \"Batch 3 incorrect\"\n print(\"Test case 1 passed!\")\n \n # Test case 2: Invoice larger than max_total\n invoices2 = [\n {'id': 'B1', 'amount': 30.0},\n {'id': 'B2', 'amount': 150.0}, # Exceeds max_total of 100\n {'id': 'B3', 'amount': 40.0},\n {'id': 'B4', 'amount': 50.0}\n ]\n result2 = chunk_invoices(invoices2, 100.0)\n assert len(result2) == 3, f\"Expected 3 batches, got {len(result2)}\"\n assert result2[0] == [{'id': 'B1', 'amount': 30.0}], \"Batch 1 incorrect\"\n assert result2[1] == [{'id': 'B2', 'amount': 150.0}], \"Batch 2 (large invoice) incorrect\"\n assert result2[2] == [{'id': 'B3', 'amount': 40.0}, {'id': 'B4', 'amount': 50.0}], \"Batch 3 incorrect\"\n print(\"Test case 2 passed!\")\n \n # Test case 3: Edge cases - empty list, exact amounts, single invoice\n invoices3 = [\n {'id': 'C1', 'amount': 100.0},\n {'id': 'C2', 'amount': 100.0},\n {'id': 'C3', 'amount': 50.0},\n {'id': 'C4', 'amount': 50.0}\n ]\n result3 = chunk_invoices(invoices3, 100.0)\n assert len(result3) == 3, f\"Expected 3 batches, got {len(result3)}\"\n assert result3[0] == [{'id': 'C1', 'amount': 100.0}], \"Batch 1 incorrect\"\n assert result3[1] == [{'id': 'C2', 'amount': 100.0}], \"Batch 2 incorrect\"\n assert result3[2] == [{'id': 'C3', 'amount': 50.0}, {'id': 'C4', 'amount': 50.0}], \"Batch 3 incorrect\"\n print(\"Test case 3 passed!\")\n \n # Additional edge case: empty list\n result_empty = chunk_invoices([], 100.0)\n assert result_empty == [], \"Empty list should return empty list\"\n print(\"Edge case (empty list) passed!\")\n\n\n# Run the tests\nif __name__ == \"__main__\":\n test_chunk_invoices()\n print(\"\\nAll tests passed! ✓\")\n```\n\nThis implementation:\n\n1. **Iterates through invoices in order** to preserve the original sequence\n2. **Handles large invoices** by placing them in their own batch immediately\n3. **Checks batch limits** before adding each invoice to ensure the total doesn't exceed `max_total`\n4. **Starts new batches** when the current batch would exceed the limit\n5. **Includes comprehensive test cases** covering:\n - Normal mixed amounts\n - Invoices larger than max_total\n - Edge cases with exact amounts and empty lists\n\nThe function returns a list of batches, where each batch is a list of invoice dictionaries. The time complexity is O(n) where n is the number of invoices, and space complexity is O(n) for storing the result.", "latency_ms": 36832, "cost": 0.0035799, "task_score": 10, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 9, "violates": false, "reasoning": "Correct, well-documented implementation meeting all requirements, includes more than 3 asserts, preserves order, handles edge cases. Minor verbosity but clear and useful." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response provides a flawless Python implementation that correctly handles all edge cases, preserves order, and includes the requested test cases using assert. The code is clean, well-commented, and highly useful." }, { "judge": "openai/gpt-5.6-terra", "score": 10, "violates": false, "reasoning": "Correct greedy, order-preserving batching; oversized invoices are isolated; normal batches stay within the limit. It includes at least three assert-based test cases covering standard, oversized, exact-limit, and empty-input scenarios. Clear" } ] }, { "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 helper: `memo(fn)` returns a new function that caches results based on its arguments. It uses a global `Map` and `JSON.stringify` to turn arguments into a string key. On each call, if the key isn’t in the cache, it runs the original function and stores the result; otherwise it returns the cached value.\n\n**One risk:** The single global `cache` is shared across *all* memoized functions. If two different functions receive the same arguments (e.g., both called with `(1, 2)`), their keys will collide, causing one to return the other’s cached result. Additionally, the cache never expires, so it can grow indefinitely and leak memory.", "latency_ms": 8192, "cost": 0.000440307, "task_score": 10, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 7, "violates": false, "reasoning": "Accurate, clear explanation; but lists two risks instead of one as requested, and is close to/over 150-word limit, slightly violating instructions." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response perfectly explains the code and accurately identifies the critical flaw (shared global cache causing collisions) in under 150 words. It is clear, concise, and highly useful." }, { "judge": "openai/gpt-5.6-terra", "score": 10, "violates": false, "reasoning": "Accurately explains memoization, key creation, cache lookup/storage, and a significant global-cache collision risk. It also correctly notes unbounded cache growth. Clear, junior-friendly, concise, and under 150 words." } ] }, { "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 orders o\n JOIN customers c ON o.customer_id = c.id\n WHERE o.created_at >= '2025-01-01' AND o.created_at < '2026-01-01'\n GROUP BY c.id, c.name, c.country\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": 17375, "cost": 0.00140990976, "task_score": 10, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 9, "violates": false, "reasoning": "Correct, valid PostgreSQL query using CTEs and RANK() window function, filters 2025, top 3 per country, matches required columns and structure precisely." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The query perfectly addresses the prompt, correctly using window functions, CTEs, and appropriate date filtering for PostgreSQL. It returns the exact requested columns." }, { "judge": "openai/gpt-5.6-terra", "score": 10, "violates": false, "reasoning": "Correct PostgreSQL query: aggregates 2025 order totals per customer, ranks customers within each country using a window function, filters to ranks 1–3, and returns the requested columns." } ] }, { "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-Z]{1,2}\\d(?:[\\d]|[A-Z])?\\s?\\d[A-Z]{2}$/i` \n(case‑insensitive; allows lowercase and makes the space optional)\n\n**One‑line JavaScript validation example** \n```javascript\nconst isValid = /^[a-z]{1,2}\\d(?:[\\d]|[a-z])?\\s?\\d[a-z]{2}$/i.test(field.value);\n```\n\n**Edge case** \nThis pattern does **not** match the non‑geographic postcode `GIR 0AA` (used for Girobank), which deliberately breaks the normal alphanumeric structure.", "latency_ms": 49275, "cost": 0.0028328625, "task_score": 8, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 7, "violates": false, "reasoning": "Regex mostly correct and covers examples, JS example fine, valid edge case noted. Minor: regex doesn't restrict letters excluded in real postcodes, but acceptable for task scope." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response provides a highly accurate regex, a concise one-line JavaScript example, and correctly identifies a well-known edge case (GIR 0AA). It perfectly follows all instructions." }, { "judge": "openai/gpt-5.6-terra", "score": 8, "violates": false, "reasoning": "Matches the requested examples, lowercase, and optional spacing; JavaScript example is one line. The stated GIR 0AA limitation is accurate. Minor issue: \\s? permits whitespace beyond a literal space, and the pattern overaccepts some invalid" } ] }, { "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": "**Option 1: Do not take the deal (current situation)**\n- Sales volume: 450 loaves/week\n- Revenue: 450 × £3.20 = £1,440\n- Ingredients: 450 × £1.10 = £495\n- Labour: 450 × £0.90 = £405\n- Fixed costs: £480\n- Total costs: £495 + £405 + £480 = £1,380\n- **Weekly profit: £1,440 – £1,380 = £60**\n\n**Option 2: Take the deal (commit to 600 loaves of ingredients, raise output to 520)**\n- Sales volume: 520 loaves/week (maximum capacity)\n- Revenue: 520 × £3.20 = £1,664\n- Ingredients: 600 × £0.85 = £510 (80 loaves’ worth of ingredients wasted)\n- Labour: £405 + £60 = £465\n- Fixed costs: £480\n- Total costs: £510 + £465 + £480 = £1,455\n- **Weekly profit: £1,664 – £1,455 = £209**\n\n**Recommendation:** Accept the supplier’s deal. It increases weekly profit from £60 to £209, adding £149 per week despite the wasted ingredients and extra labour cost.", "latency_ms": 108717, "cost": 0.00200416825, "task_score": 8, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 8, "violates": false, "reasoning": "Correct calculations and clear recommendation. Assumes extra labour cost is total (ambiguous), but reasonable interpretation. Clear, concise, well-structured." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response accurately calculates the profit for both scenarios, correctly accounting for the wasted ingredients and extra labour costs. The layout is clear, concise, and highly useful for a non-technical professional." }, { "judge": "openai/gpt-5.6-terra", "score": 8, "violates": false, "reasoning": "Calculations and recommendation are correct if all 520 loaves can be sold. The response reasonably uses maximum output, but it assumes demand for the additional 70 loaves; zero current unsold stock does not conclusively establish this." } ] }, { "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** \nDay 1 – Pre‑launch teaser email & social countdown post. *(Founder)* \nDay 2 – Cart opens: sales email sent; VA sets up 1 conversion ad campaign (£150). *(Founder sends email, VA builds ads)* \nDay 3 – Educational email (top tip from course) & live 15‑min Q&A on social. *(Founder)* \nDay 4 – Testimonial/story email; VA launches retargeting ad (£100) to warm visitors. *(Founder writes, VA executes)* \nDay 5 – Early‑bird deadline email (scarcity) & VA checks ad metrics, answers support queries. *(Founder + VA)* \nDay 6 – “Last chance” email with bonus highlight; VA boosts best-performing post (£50). *(Founder writes, VA boosts)* \nDay 7 – Cart‑close final email in the morning; VA pauses all ads and sends thank‑you message. *(Founder & VA)* \n\n**Single riskiest dependency:** \nThe engagement of the 2,000‑person email list (open and click rates). If the list is cold or unresponsive, even perfectly crafted emails and ads will struggle to convert, making this the linchpin of the entire launch.", "latency_ms": 22317, "cost": 0.00134674176, "task_score": 8, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 8, "violates": false, "reasoning": "Clear 7-day plan with owners each line, budget allocated (£300 total), risk flagged well. Minor: some lines have dual owners rather than single, slight deviation from strict one-owner instruction." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response perfectly follows all instructions, including the strict formatting constraints (one line per day, naming the owner). It provides a highly practical, accurate, and concise plan tailored to the specified resources and budget." }, { "judge": "openai/gpt-5.6-terra", "score": 8, "violates": false, "reasoning": "Clear seven-day plan, named ownership, and ad spend totals £300. It sensibly identifies list engagement as a key dependency. Minor gaps: no explicit checkout/landing-page, tracking, or automation readiness checks, and VA time allocation is " } ] }, { "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:** Hire the mid-level developer.\n\n**Cost:** A full-time hire costs ~£55k salary (≈£65k with on-costs), while 60 days of freelancing at £400/day costs £24k. The immediate saving with freelancers is significant, but a permanent employee can absorb overflow *and* contribute to billable projects or internal improvements, often covering the gap if utilised just 30% beyond overflow.\n\n**Flexibility:** Freelancers offer precise, pay-as-you-go scaling. However, a permanent developer is always available for sudden spikes and can build deeper domain expertise, reducing the lag of repeated onboarding.\n\n**Quality risk:** Freelancers vary in skill and reliability; rotating them risks inconsistent code, IP security concerns, and constant management overhead. A permanent hire ensures code ownership, cultural alignment, and cumulative knowledge, raising overall team quality.\n\n**Non-obvious factor:** In the UK, engaging the same freelancer for 60 days annually may trigger IR35 rules, treating them as a disguised employee and exposing the agency to back-taxes and penalties—a costly, easily overlooked compliance risk.\n\nGiven the ability to leverage a developer beyond overflow work and the hidden risks of freelancers, the permanent hire builds long-term capability while likely breaking even financially.", "latency_ms": 34922, "cost": 0.001795625, "task_score": 7, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 7, "violates": false, "reasoning": "Solid, covers all required elements with accurate cost math and IR35 as non-obvious factor; slightly over 200 words likely, but concise and clear overall." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response perfectly addresses all prompts, stays under the 200-word limit (182 words), and provides a highly relevant, non-obvious factor (IR35). It is concise, accurate, and extremely useful for a non-technical manager." }, { "judge": "openai/gpt-5.6-terra", "score": 6, "violates": false, "reasoning": "Covers all requested factors clearly and stays under 200 words. However, the hire recommendation relies on an unsupported utilisation assumption, and IR35 is not triggered by 60 days alone; status depends on working arrangements." } ] }, { "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": "The tank becomes full at **10:25**.\n\n**Working:**\n\n1. **09:00 to 09:20** (20 minutes): \n Only Pump A is running at 40 L/min. \n Volume filled = 40 L/min × 20 min = **800 L**.\n\n2. **09:20 to 10:00** (40 minutes): \n Pump A (40 L/min) and Pump B (draining 25 L/min) both run. \n Net fill rate = 40 − 25 = 15 L/min. \n Volume filled = 15 L/min × 40 min = **600 L**.\n\n3. **Total by 10:00**: \n 800 L + 600 L = **1400 L**.\n\n4. **Remaining volume**: \n 2400 L − 1400 L = **1000 L**.\n\n5. **After 10:00**: \n Only Pump A runs at 40 L/min. \n Time to fill 1000 L = 1000 ÷ 40 = **25 minutes**.\n\n6. **Full time**: \n 10:00 + 25 minutes = **10:25**.", "latency_ms": 13022, "cost": 0.0008569645, "task_score": 10, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 10, "violates": false, "reasoning": "Correct calculation, clear step-by-step working, accurate final answer of 10:25, well formatted and easy to follow." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The math is perfectly accurate, the steps are clearly shown, and the final answer is correct. The formatting makes it very easy to read." }, { "judge": "openai/gpt-5.6-terra", "score": 10, "violates": false, "reasoning": "All calculations are correct: 800 L before 09:20, 600 L net during overlap, then 25 minutes at 40 L/min. It clearly shows working and directly answers the question." } ] }, { "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 argument mistakenly assumes correlation equals causation: the churn drop may stem from seasonality, market shifts, or other concurrent changes, not the loyalty program. It also falsely extrapolates linearly—doubling the budget won't proportionally halve churn again, as diminishing returns and a floor effect (churn can't drop indefinitely) make 1.5% unrealistic.", "latency_ms": 6695, "cost": 0.0003629988, "task_score": 8, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 8, "violates": false, "reasoning": "Accurate, concise, identifies causation flaw and false linear extrapolation, under 100 words, clear and useful for non-technical reader." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "Accurately identifies the logical flaws (correlation vs. causation and linear extrapolation) in a clear, concise manner well under the 100-word limit. Perfect for a non-technical professional." }, { "judge": "openai/gpt-5.6-terra", "score": 8, "violates": false, "reasoning": "Correctly identifies lack of causal evidence and unjustified proportional extrapolation. Clear and concise. Minor overstatement: a churn floor does not by itself make 1.5% unrealistic; it only means returns may diminish." } ] }, { "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\": \"Request a quote for the workshop series, ideally before September\"\n}", "latency_ms": 3834, "cost": 0.0002725125, "task_score": 10, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 9, "violates": false, "reasoning": "Accurate extraction, correct JSON format, all keys present, concise and clear." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response perfectly extracts the required information into a valid JSON object with the exact keys requested, and contains no extra text." }, { "judge": "openai/gpt-5.6-terra", "score": 10, "violates": false, "reasoning": "All fields are accurately extracted, normalized appropriately, and the intent correctly captures the quote request and timing. Output is valid JSON and follows the requested keys exactly." } ] }, { "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 | 0 | 3,300 | n/a |\n| Delta | 5,000 | 5,000 | 0.0% |", "latency_ms": 12312, "cost": 0.0008685355, "task_score": 10, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 9, "violates": false, "reasoning": "Accurate calculations, correct format, follows instructions including n/a for Gamma; clear and concise." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response perfectly follows all instructions, creating a properly formatted markdown table with accurate data and correctly calculated percentages rounded to one decimal place." }, { "judge": "openai/gpt-5.6-terra", "score": 10, "violates": false, "reasoning": "All products, quarterly values, and percentage changes are correct. Gamma correctly uses n/a because percentage change from zero is undefined. The markdown table has exactly the requested columns and is clear and concise." } ] }, { "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 Chief Data Officer - Halcyon Health\nPriya Shah - unknown - Halcyon Health\nT. Lindqvist - unknown - unknown", "latency_ms": 22841, "cost": 0.0013693225, "task_score": 6, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 5, "violates": false, "reasoning": "Priya Shah's role (Legal sign-off) and Lindqvist's role (external audit) were marked unknown instead of extracted from text, reducing accuracy despite correct format." }, { "judge": "google/gemini-3.1-pro-preview", "score": 9, "violates": false, "reasoning": "Accurately extracts the names, roles, and organizations following the requested format. Appropriately uses 'unknown' for missing explicit titles/orgs, though 'external auditor' could arguably be inferred for Lindqvist." }, { "judge": "openai/gpt-5.6-terra", "score": 6, "violates": false, "reasoning": "Format is correct and all four people are included. However, Ben Tran is stated to join from Meridian Labs, not Halcyon Health, and T. Lindqvist’s role should reflect external audit rather than unknown." } ] }, { "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 with 7–2 vote.\n- Phase one starts in October, costing £4.6m, includes fish market roof.\n- Phase two marina expansion is unfunded; grant decision expected in January.\n- Local traders get first refusal on the 14 new retail units.\n- Construction traffic routed via Dock Road, avoiding the high street.", "latency_ms": 6616, "cost": 0.001560432, "task_score": 10, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 10, "violates": false, "reasoning": "Exactly 5 accurate bullets, all under 15 words, correctly capturing key facts. Clear and concise." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response perfectly extracts exactly 5 key facts as bullets, with each bullet being under the 15-word limit. The information is accurate, concise, and highly useful." }, { "judge": "openai/gpt-5.6-terra", "score": 8, "violates": false, "reasoning": "Exactly five bullets, all under 15 words, accurately cover the main facts. Minor omission: phase two’s dependence on a levelling-up grant is not explicitly stated." } ] }, { "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": "{\"event\": \"AI in Retail Summit\", \"date\": \"2026-03-14\", \"venue\": \"Baltic Exchange\", \"capacity\": 320, \"speakers\": [{\"name\": \"Nadia Rossi\", \"topic\": \"demand forecasting\"}, {\"name\": \"Kwame Mensah\", \"topic\": \"dynamic pricing\"}], \"sold_out\": false}", "latency_ms": 5304, "cost": 0.00044154432, "task_score": 10, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 10, "violates": false, "reasoning": "Correct JSON matching schema exactly, accurate data extraction, sold_out correctly false, concise and properly formatted." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response perfectly extracts the data 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": "Exactly matches the required schema and JSON-only instruction. All event details, date formatting, capacity, speakers/topics, and sold_out status are accurately converted." } ] }, { "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 absorb sunlight, water, and carbon dioxide to produce food and oxygen. \nInside chloroplasts, light energy splits water molecules and releases oxygen. \nFinally, the Calvin cycle uses captured energy to convert carbon dioxide into glucose.", "latency_ms": 12297, "cost": 0.00086729664, "task_score": 9, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 9, "violates": false, "reasoning": "Meets all constraints: correct starts, 3 sentences, under 20 words each, accurate content, clear and concise." }, { "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 highly useful." }, { "judge": "openai/gpt-5.6-terra", "score": 9, "violates": false, "reasoning": "Meets all sentence-start, sentence-count, and word-limit requirements. Clear and accurate overall; the Calvin cycle more directly produces sugar intermediates than glucose itself, a minor simplification." } ] }, { "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 of premises for a fixed term, creating a legal estate with statutory renewal rights under the Landlord and Tenant Act 1954. A licence is a mere permission to occupy, without exclusive possession, offering no security of tenure. The occupier is a licensee, not a tenant.", "latency_ms": 19983, "cost": 0.0016741584, "task_score": 9, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 9, "violates": false, "reasoning": "Exactly 50 words, accurate legal distinction, clear and concise; meets constraint precisely." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response is highly accurate, clearly explaining the core legal distinctions (exclusive possession and security of tenure) for UK commercial property, and perfectly meets the strict 50-word constraint." }, { "judge": "openai/gpt-5.6-terra", "score": 8, "violates": false, "reasoning": "Exactly 50 words. Clear and broadly accurate. Minor overstatement: not every commercial lease has 1954 Act renewal rights; this depends on the tenancy and exclusions. A licence’s substance, not label, determines whether exclusive possession" } ] }, { "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": "The sharp, pungent taste in coffee often stems from chemical reactions during the heating of the seeds. Chlorogenic compounds break down into lactones and phenylindanes, which impart a harsh edge. Overly dark processing intensifies these, as does brewing with excessively hot water or prolonged contact time, which pulls out more of these substances along with the natural stimulant alkaloid found in the drink. Additionally, small imperfections or overripe fruit on the plant can contribute unpleasant notes. Thus, the sensation arises from a mix of degraded plant chemicals, preparation methods, and the inherent properties of the seed's components.", "latency_ms": 13908, "cost": 0.0009518925, "task_score": 9, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 8, "violates": false, "reasoning": "Accurate, avoids banned words and variants, within word count, clear and useful explanation with minor jargon." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response flawlessly explains the causes of the harsh taste using accurate chemistry and brewing factors. It strictly adheres to the 80-120 word limit (96 words) and successfully avoids all banned words and their variants." }, { "judge": "openai/gpt-5.6-terra", "score": 9, "violates": false, "reasoning": "Meets the 80–120 word requirement (97 words) and avoids all forbidden terms and variants. Accurate explanation of heat-driven compound changes and over-extraction. Slightly indirect phrasing and minor overemphasis on fruit imperfections pre" } ] }, { "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": "Hiring our first apprentice felt like a leap of faith. I worried about the time investment and whether we could provide real value. But watching their curiosity turn into capability has been the most rewarding part of my leadership journey. The energy they bring is infectious, and their fresh perspective challenges our assumptions daily.\n\nWhat if the best way to grow your team isn't hiring experience, but cultivating it?\n\nNow, I see that small wins compound. Every task mastered and every confident client call builds a foundation for their career and our culture. Investing in raw talent has given us more than skills—it’s given us a future leader who truly understands our mission. 🌱", "latency_ms": 50147, "cost": 0.00877308, "task_score": 5, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 5, "violates": true, "reasoning": "Word count is ~114, exceeding the 90-110 limit. Otherwise structure, emoji, phrase, and question paragraph are correct; content is engaging and clear." }, { "judge": "google/gemini-3.1-pro-preview", "score": 5, "violates": true, "reasoning": "The response is excellently written and meets all constraints except the word count, which is 113 words (violating the 90-110 word limit)." }, { "judge": "openai/gpt-5.6-terra", "score": 5, "violates": true, "reasoning": "Strong, polished, and practical LinkedIn post with the required phrase, exactly three paragraphs, a single-question second paragraph, no hashtags, and one final emoji. It contains 113 words, exceeding the 90–110-word limit." } ] }, { "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": "Small Retail Shop Closing Checklist\n\nFront of house\n1. Clear and clean all counter surfaces.\n2. Restock shelves and face products forward.\n3. Empty all trash bins and recycling.\n4. Turn off display lights and music.\n\nBack office\n1. Count cash drawer and prepare deposit.\n2. Reconcile daily sales and log totals.\n3. Shut down computers and office equipment.\n4. Lock filing cabinets and secure documents.\n\nSecurity\n1. Activate alarm system and security cameras.\n2. Check all doors and windows are locked.\n3. Set exterior lighting timers or leave on.\n4. Perform final walkthrough for hidden hazards.", "latency_ms": 13370, "cost": 0.0011227176, "task_score": 10, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 9, "violates": false, "reasoning": "Matches required structure, headers, item counts, and word-count ranges; clear, concise, useful checklist with no extraneous content." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response follows all instructions perfectly, including the exact structure, section headings, item counts, and word count constraints per item. It is highly useful and clear." }, { "judge": "openai/gpt-5.6-terra", "score": 10, "violates": false, "reasoning": "Exactly matches the required title-and-three-section structure. Each section has four numbered items, and every item contains 3–8 words. Content is practical, clear, and appropriate for retail closing." } ] }, { "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": 5754, "cost": 0.0000684, "task_score": 10, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 9, "violates": false, "reasoning": "Accurate, single sentence, meets constraint, clear and concise, correct current UK standard rate of 20%." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response perfectly follows the instructions, providing accurate information in exactly one clear and concise sentence." }, { "judge": "openai/gpt-5.6-terra", "score": 10, "violates": false, "reasoning": "Accurately states that VAT means Value Added Tax and gives the current UK standard rate as 20%, in exactly one clear sentence." } ] }, { "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\n'Your Tesco order 8812 is ready for collection' / NOT SPAM\n'URGENT your account will be closed verify now' / SPAM\n'Minutes from Thursday's board meeting attached' / NOT SPAM", "latency_ms": 8878, "cost": 0.0002704308, "task_score": 10, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 8, "violates": false, "reasoning": "Correct classifications, clear two-column format, though task implied output only two columns (label and classification), not repeating full quotes; minor format deviation but still usable and accurate." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The response perfectly follows all instructions, correctly classifying each phrase as SPAM or NOT SPAM 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 correctly classified. The response contains only four two-field lines, using a slash as the column separator, with no extraneous content." } ] }, { "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 tu arrives en premier ?", "latency_ms": 8792, "cost": 0.00191052, "task_score": 10, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 8, "violates": false, "reasoning": "Accurate, informal, natural French translation; minor nuance 'en premier' slightly less idiomatic than 'avant nous' but acceptable." }, { "judge": "google/gemini-3.1-pro-preview", "score": 10, "violates": false, "reasoning": "The translation is highly accurate, perfectly captures the requested informal tone using 'on' and 'tu', and sounds very natural in French." }, { "judge": "openai/gpt-5.6-terra", "score": 10, "violates": false, "reasoning": "Accurate, natural informal French. It preserves the meaning, timing, request, and casual tone. “Prends-nous une table” is understandable and idiomatic enough in context." } ] }, { "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": "Tucked into the Yorkshire countryside, our story began in 1987 when Mum and Dad turned a windswept field and a lifelong passion for plants into a family home. What started as a modest nursery has blossomed over three decades, and today, I’m proud to carry on their legacy as the second-generation owner. You’ll still find Dad offering unsolicited pruning advice and Mum fussing over the hanging baskets.\n\nWe’ve earned our reputation by specialising in the unusual. While you’ll find all the garden essentials here, our true love lies in rare and heritage perennials you won’t easily spot elsewhere. Every plant is nurtured with Yorkshire grit and tenderness until it’s ready to thrive in your own garden.\n\nGrowing things is hungry work, so our small café is the heart of the centre. We serve proper homemade cakes, steaming pots of Yorkshire Tea, and a warm welcome that turns first-time visitors into lifelong friends. We aren’t just selling plants; we’re sharing a little piece of our family’s roots.", "latency_ms": 3533, "cost": 0.00060115, "task_score": 5, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 5, "violates": true, "reasoning": "Well-written, warm, on-brief content but word count is ~200, not 150 as required — a clear checkable constraint violation." }, { "judge": "google/gemini-3.1-pro-preview", "score": 5, "violates": true, "reasoning": "Beautifully written and includes all required details (Yorkshire, 1987, daughter-run, rare perennials, cafe). However, it violates the exact 150-word count constraint, coming in at 166 words." }, { "judge": "openai/gpt-5.6-terra", "score": 5, "violates": true, "reasoning": "It is warm, accurate, and covers Yorkshire, 1987, second-generation family ownership, rare perennials, and café. However, it is 166 words, not the required 150, so it breaks the explicit word-count constraint." } ] }, { "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": "Composting at home is one of the easiest ways to reduce waste and create nutrient-rich soil for your garden. It’s a natural process where organic matter breaks down into a dark, crumbly substance often called “black gold.” Setting up a bin is simple, but a few key steps will help you avoid smells, pests, and frustration. Here’s everything a beginner needs to know.\n\n**Choosing the Right Location**\nPick a spot that’s convenient but well-drained and partially shaded. Direct sun can dry out the pile, while full shade may keep it too cool and slow decomposition. A level patch of bare soil is ideal because it allows worms and beneficial microbes to enter from the ground, aiding breakdown. If you must place the bin on concrete, add a shovel of garden soil to introduce those organisms. Keep it within easy reach of the kitchen—maybe near a back door—so you’re more likely to use it regularly. Ensure there’s enough space to turn the contents and access the finished compost.\n\n**What to Add: Greens and Browns**\nThink of your compost ingredients in two categories. “Greens” are nitrogen-rich materials that fuel the decomposers: fruit and vegetable scraps, coffee grounds, tea bags, fresh grass clippings, and plant trimmings. “Browns” provide carbon and structure: dry leaves, shredded newspaper, cardboard, straw, sawdust from untreated wood, and eggshells (rinsed and crushed). A good rule of thumb is to aim for roughly two to three parts browns to one part greens by volume. Layering them as you add material—like a lasagna—helps maintain airflow and balance. Chop larger items into smaller pieces to speed things up.\n\n**What to Avoid**\nNot everything from the kitchen or garden belongs in the bin. Never add meat, fish, bones, dairy products, or greasy foods; they attract rodents and create foul odors. Avoid pet waste, which can carry pathogens. Steer clear of diseased plants, weeds that have gone to seed, and anything treated with pesticides. Synthetic materials, plastics, and glossy paper are also off-limits. Cooked food scraps can be problematic unless you’re using a sealed, pest-proof system, so stick to raw fruit and vegetable waste when starting out.\n\n**How Long Does It Take?**\nPatience is key. In a well-maintained bin—regularly turned, kept as moist as a wrung-out sponge, and balanced with greens and browns—you can have finished compost in three to six months during warm weather. A more hands-off approach might take a year or longer. You’ll know it’s ready when the material is dark, crumbly, and earthy-smelling, with no recognizable food scraps. Sift out any larger, unfinished bits and toss them back into the bin for another cycle.\n\n**One Common Mistake: Too Much of One Thing**\nThe most frequent beginner blunder is adding too many greens without enough browns. A pile overloaded with kitchen scraps becomes slimy, smelly, and anaerobic. If your bin starts to stink like ammonia or rotten eggs, it’s a cry for more carbon. Mix in dry leaves, shredded cardboard, or newspaper immediately, and turn the pile to reintroduce oxygen. Balancing your inputs from day one prevents this and keeps your compost working efficiently.\n\nWith the right location, a good mix of materials, and a little patience, your compost bin will transform everyday waste into a powerful soil booster. Start small, observe what works, and enjoy the process of turning scraps into garden treasure.", "latency_ms": 23975, "cost": 0.00304674, "task_score": 5, "judges": [ { "judge": "anthropic/claude-sonnet-5", "score": 5, "violates": true, "reasoning": "Comprehensive, accurate, well-organized content covering all required points, but far exceeds 400-word constraint (actual ~640 words), which is an explicit checkable limit." }, { "judge": "google/gemini-3.1-pro-preview", "score": 5, "violates": true, "reasoning": "The response covers all required topics clearly and accurately, making it highly useful. However, it violates the explicit 400-word constraint, as the text is approximately 460 words long." }, { "judge": "openai/gpt-5.6-terra", "score": 5, "violates": true, "reasoning": "It is detailed, well organized, and covers every requested topic clearly. However, it is 552 words rather than 400. Minor accuracy issue: eggshells are not meaningfully a carbon-rich “brown” material." } ] } ] }