Best AI for bookkeeping

The verdict

GPT-5.6 Terra

Scored 93/100 on our 12-task bookkeeping suitelevel on quality with GPT-5.6 Sol (93) — the top spot goes on the tie-break: cleanest rule-compliance, then lowest measured cost; 2 more sit a single point behind.

What to actually do

GPT-5.6 Terra is the engine inside ChatGPT. Go to chatgpt.comthe free tier is fine to start. Paid plans start at £7/month (go plan, vendor’s own price). The free tier is ChatGPT’s, not a promise about this exact model — we haven’t verified which plan carries it. Not fussed about the last point or two? Any of the top 4 here will serve you well.

UK small-business bookkeeping, and the rule is always quoted in the task: answers are marked against the guidance in front of them, never against tax law the model claims to remember. A client lunch and a motorway sandwich, nine lines off a bank feed with the ones that cannot be categorised flagged rather than guessed, a reconciliation £36 out for a reason a bookkeeper spots in seconds, and an invoice whose four totals have exactly one correct answer, compared by the harness rather than by opinion. One task is the call every bookkeeper gets — £4,180 profit, £900 in the bank — answered in 120 words without using the word 'debtors'. None of this is accountancy or tax advice — answers are judged against the guidance quoted in the task, and a good one tells you when to ring your accountant. One task asks for an invoice to be redated across the year end and a daughter who does not work there put on the payroll; the right answer is to refuse both, and to say which question belongs with the accountant.

updated 27 Aug 2026 · tested by Robert Prime · re-ranks automatically when a new run lands

How this was measured
  • All 19 sat the identical 12-task suite — same tasks, same order, one attempt each.
  • Every answer marked blind: judges are not told which entrant wrote it.
  • Three judges per answer, each from a competing lab. A panel never includes the entrant's own lab.
  • Scored 0–10 against a fixed rubric. Answers breaking a task's explicit rules are capped by machine, not by opinion.
  • Ties broken by fewest rule breaches, then lowest measured cost — published, not editorial.
  • Nobody pays for placement. Last computed 27 Aug 2026.

Every score below links to the raw file behind it: every task, the entrant’s real answer, and all three judges’ marks.

#ModelOur score
1GPT-5.6 Terralatest93/100
2GPT-5.6 Sollatest93/100
3GPT-5.3-Codex92/100
4GPT-5.592/100
5Claude Fable 589/100
6Grok 4.587/100
7Qwen3.7 Max85/100
8Kimi K384/100
9Claude Opus 4.883/100
10GPT-5.6 Luna83/100
11GLM 5.281/100
12Claude Sonnet 581/100
13Gemini 3.5 Flash81/100
14DeepSeek V4 Flash78/100
15Gemini 3.1 Pro Preview78/100
16Claude Opus 4.678/100
17DeepSeek V4 Pro70/100
18Gemini 3.1 Flash Lite67/100
19Mistral Medium 3.565/100

“API cost” is what software developers pay to build on a model — ignore it if you just use the website. Each model answers each task once. Models level on score are ranked by a fixed tie-break — fewest machine-checked rule breaches, then lowest measured cost per run — so the order is deterministic and checkable, never arbitrary. Judge panels never include the contestant’s own lab, so panels differ slightly per model — small cross-model gaps can reflect panel severity, not quality.

1.

GPT-5.6 Terra

93/100our pick — won on the tie-break

Made by OpenAI — their newest model. You use it inside ChatGPT — nothing to install.

Strongest showing: Find the £36” — scored 8/10 by the panel. On one task a judge flagged a possible instruction breach — advisory only: the machine check did not confirm it and the panel outvoted it.

Accurate arithmetic and sound reasoning on transposition/casting-out-nines rule, thorough ledger guidance. Slightly verbose but clear, correct, and covers all required points well.anthropic/claude-sonnet-5, judging blind · full receipts ↓

12 tasks · 27 Aug 2026 · judges claude-sonnet-5, gemini-3.1-pro-preview, grok-4.5 · API $2 in / $12 out per 1M tokens · full model page →

2.

GPT-5.6 Sol

93/100

Same maker, same score — effectively the same choice as #1; the deep-dive above covers it. Full model page →

Made by OpenAI. You use it inside ChatGPT — nothing to install.

Strongest showing: Profit but no money” — scored 10/10 by the panel. Weakest: “The faded shoebox” at 8/10.

The response perfectly explains the cash flow vs profit discrepancy in plain English, addressing all four points accurately. It strictly follows all constraints, including word count and banned words, with excellent clarity.google/gemini-3.1-pro-preview, judging blind · full receipts ↓

12 tasks · 27 Aug 2026 · judges claude-sonnet-5, gemini-3.1-pro-preview, grok-4.5 · API $1.75 in / $14 out per 1M tokens · full model page →

See it for yourself

One task from the suite, and what the leader, the middle of the table and the bottom actually wrote. This is the task they disagreed on most — scores ranged from 3 to 10 out of 10.

The task — The invoice totals

A VAT-registered UK business is raising one invoice. The lines: 12 branded mugs at £7.50 each, standard-rated at 20%; 200 printed leaflets at £0.14 each, which this business's VAT guidance treats as zero-rated; delivery £9.60, which this business's guidance treats as standard-rated at 20% in full — do not apportion the delivery between the goods. A 10% early-settlement discount was offered but the customer paid in full on day 30, so it was not taken: charge on the full amounts. Reply with ONLY valid JSON — no prose, no explanation, no code fence commentary. An object with exactly these four keys and no others: net_standard_gbp, net_zero_gbp, vat_gbp, total_gbp. All four values are numbers, not strings, each rounded to 2 decimal places, with no currency symbol.

{"net_standard_gbp":99.60,"net_zero_gbp":28.00,"vat_gbp":19.92,"total_gbp":147.52}

Judge: All calculations correct, JSON format matches exactly required keys and rounding.

{"net_standard_gbp":99.60,"net_zero_gbp":28.00,"vat_gbp":19.92,"total_gbp":147.52}

Judge: Calculations correct: 90+9.60=99.60 standard net, 28 zero, VAT 19.92, total 147.52. Format matches exactly required JSON keys and types.

{"net_standard_gbp": 104.4, "net_zero_gbp": 28.0, "vat_gbp": 20.88, "total_gbp": 161.28}

Judge: Capped in code — the answer broke a checkable rule (wrong answer at $.net_standard_gbp: expected 99.6, got 104.4). The response contains major calculation errors. Net standard should be 99.60, VAT 19.92, and total 147.52. The provided values are incorrect and do not even sum correctly.

Trimmed to fit. Every full answer, every judge’s score: GPT-5.6 Terra, GPT-5.6 Luna, Mistral Medium 3.5

How this ranking is made

Every model answers the identical published task suite. Three AI judges from three different labs mark each answer blind against a fixed 0–10 rubric — none is ever from the maker’s own lab, and an answer that breaks a task’s explicit rules is capped in code, not by the judge’s goodwill. The score is the average, out of 100.

What this is not: an opinion piece, a paid ranking, or a benchmark we cannot show you. No vendor can buy inclusion, a position or a score on this page — the order is computed from the test results before any link to a product exists, and where a link earns us a commission it says so on the link itself and the order is identical either way. Every score links its raw outputs and judge verdicts. The full protocol · How we make money · receipts: GPT-5.6 Terra, GPT-5.6 Sol, GPT-5.3-Codex, GPT-5.5, Claude Fable 5, Grok 4.5, Qwen3.7 Max, Kimi K3, Claude Opus 4.8, GPT-5.6 Luna, GLM 5.2, Claude Sonnet 5, Gemini 3.5 Flash, DeepSeek V4 Flash, Gemini 3.1 Pro Preview, Claude Opus 4.6, DeepSeek V4 Pro, Gemini 3.1 Flash Lite, Mistral Medium 3.5

Questions people ask

What is the best AI for bookkeeping in 2026?

GPT-5.6 Terra leads our tested ranking with 93/100 on our 12-task bookkeeping suite, in a dead heat with GPT-5.6 Sol (93). Every answer was marked blind by three AI judges from three different labs, and the full outputs are downloadable.

How is this ranking made?

Each model answers the identical published task suite; three judges from different labs score every answer 0–10 against a fixed rubric without knowing which produced it; answers that break a task's explicit rules are capped automatically. The score is the average, out of 100. No vendor pays for placement.

What happens when two models score the same?

They are separated by a fixed, published tie-break rather than by editorial choice: first the fewest machine-checked rule breaches, then the lowest measured cost per run. The order is therefore reproducible from the same data, and where the tie-break decides the top place the page says so.

How often does this page update?

It re-ranks itself whenever a new test run lands, and prices re-verify daily against vendor pages. The current ranking was last computed on 27 Aug 2026.

Head-to-heads in bookkeeping & accounts

Show all 20 tested pairs ▾

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