Claude Opus 4.7 vs Mistral Large
Updated October 21, 2026. 38 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Only Claude Opus 4.7 has a coding score, 67.5 on the Vibe Coding Index; Mistral Large has none, so the two cannot be ranked on coding.
Mistral Large has the edge where output tokens cost 4.2x less.
- Shared results
- 38
- Claude Opus 4.7 only
- 63
- Mistral Large only
- 6
- Like-for-like categories
- 6 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Only Claude Opus 4.7 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Claude Opus 4.7
Claude Opus 4.7 leads, 40.7 against 5.8.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Claude Opus 4.7 has a AA Agentic Index result, 38.6.
Directional only
Reasoning
GPQA Diamond
Claude Opus 4.7
Claude Opus 4.7 leads, 90.2% against 47.7%.
Same board, both measured
Math
AIME
Claude Opus 4.7
Claude Opus 4.7 leads, 96.3% against 9.2%.
Same board, both measured
Knowledge
MMLU Pro
Claude Opus 4.7
Claude Opus 4.7 leads, 89.9% against 69.7%.
Same board, both measured
Long documents
Listed context window
Claude Opus 4.7
Claude Opus 4.7 takes 1M tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Large
Claude Opus 4.7 $0.018, Mistral Large $0.0050 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Claude Opus 4.7 has the number, $2.95.
Directional only
At a glance
- Coding index
- Claude Opus 4.7 67.5 from 4 benchmarks, Mistral Large not benchmarked.
- Widest category
- Math, 56.2 points apart on average over 3 shared benchmarks.
- Widest single gap
- AIME: Claude Opus 4.7 96.3% against Mistral Large 9.2%, 87.1 points apart on a 0 to 100 scale.
- Output price
- Claude Opus 4.7 $25.00 against Mistral Large $6.00 per million output tokens, 4.2x apart.
- Context window
- Claude Opus 4.7 takes 1M tokens, Mistral Large 128K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Claude Opus 4.7 | Bars | Mistral Large | Ties |
|---|---|---|---|---|
| Coding | 3 | 0 | ||
| Intelligence | 2 | 0 | ||
| Reasoning | 6 | 0 | ||
| Math | 3 | 0 | ||
| Knowledge | 6 | 0 | ||
| General | 18 | 0 | ||
| All shared boards | 38 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
| Benchmark | Claude Opus 4.7 | Mistral Large | Leader |
|---|---|---|---|
| LMArena WebDev | 1558 | Not measured | Only Claude Opus 4.7 measured |
| AA Coding Index | 73.6 | Not measured | Only Claude Opus 4.7 measured |
| LiveCodeBench (Vals AI) | 85.1% | 37.1% | Claude Opus 4.7 |
| SWE-bench Verified (Vals AI) | 82.0% | Not measured | Only Claude Opus 4.7 measured |
| Vibe Code Bench (Vals AI) | 71.0% | Not measured | Only Claude Opus 4.7 measured |
| Code migration (Vals AI) | 43.9% | Not measured | Only Claude Opus 4.7 measured |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only Claude Opus 4.7 measured |
| Terminal-Bench 2.1 (Vals AI) | 68.5% | Not measured | Only Claude Opus 4.7 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 17.8% | Only Mistral Large measured |
| Terminal-Bench Hard (Artificial Analysis run) | 54.5% | Not measured | Only Claude Opus 4.7 measured |
| Terminal-Bench | 80.2% | Not measured | Only Claude Opus 4.7 measured |
| FrontierCode | 38.5% | Not measured | Only Claude Opus 4.7 measured |
| GSO-Bench | 44.1% | Not measured | Only Claude Opus 4.7 measured |
| WeirdML | 76.4% | Not measured | Only Claude Opus 4.7 measured |
| MirrorCode | 31.1% | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: coding | 1519 | 1275 | Claude Opus 4.7 |
| LMArena Text: software and IT | 1516 | 1274 | Claude Opus 4.7 |
| LMArena WebDev: React | 1560 | Not measured | Only Claude Opus 4.7 measured |
| LMArena WebDev: HTML | 1554 | Not measured | Only Claude Opus 4.7 measured |
| LMArena WebDev: from an image | 1577 | Not measured | Only Claude Opus 4.7 measured |
| Neither model has a result on the other 18 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Claude Opus 4.7 | Mistral Large | Leader |
|---|---|---|---|
| AA Intelligence Index | 40.7 | 5.8 | Claude Opus 4.7 |
| Epoch Capabilities Index | 156.8 | 122.1 | Claude Opus 4.7 |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | Claude Opus 4.7 | Mistral Large | Leader |
|---|---|---|---|
| AA Agentic Index | 38.6 | Not measured | Only Claude Opus 4.7 measured |
| Finance Agent (Vals AI) | 51.5% | Not measured | Only Claude Opus 4.7 measured |
| Tax Agent Bench (Vals AI) | 23.7% | Not measured | Only Claude Opus 4.7 measured |
| Legal Research Bench (Vals AI) | 38.5% | Not measured | Only Claude Opus 4.7 measured |
| Excel Modeling Benchmark (Vals AI) | 63.7% | Not measured | Only Claude Opus 4.7 measured |
| τ²-Bench Telecom | 88.6% | Not measured | Only Claude Opus 4.7 measured |
| APEX-Agents | 49.2% | Not measured | Only Claude Opus 4.7 measured |
| OSWorld 2.0 | 18.2% | Not measured | Only Claude Opus 4.7 measured |
| PostTrainBench | 28.6% | Not measured | Only Claude Opus 4.7 measured |
| Vending-Bench 2 | $10,937 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Search | 1230 | Not measured | Only Claude Opus 4.7 measured |
| Neither model has a result on the other 28 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | Claude Opus 4.7 | Mistral Large | Leader |
|---|---|---|---|
| GPQA Diamond | 90.2% | 47.7% | Claude Opus 4.7 |
| MMMU Pro (Vals AI) | 85.5% | Not measured | Only Claude Opus 4.7 measured |
| GPQA Diamond (Artificial Analysis run) | 91.4% | 35.1% | Claude Opus 4.7 |
| Humanity's Last Exam (Artificial Analysis run) | 42.3% | 3.5% | Claude Opus 4.7 |
| GPQA Diamond (Epoch AI run) | 90.2% | Not measured | Only Claude Opus 4.7 measured |
| ARC-AGI | 93.5% | Not measured | Only Claude Opus 4.7 measured |
| ARC-AGI-2 | 75.8% | Not measured | Only Claude Opus 4.7 measured |
| SimpleBench | 61.7% | Not measured | Only Claude Opus 4.7 measured |
| Chess puzzles | 41.0% | Not measured | Only Claude Opus 4.7 measured |
| Mystery game puzzles | 28.0% | Not measured | Only Claude Opus 4.7 measured |
| EBR-bench | 19.0% | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: hard prompts | 1506 | 1257 | Claude Opus 4.7 |
| LMArena Text: expert | 1521 | 1208 | Claude Opus 4.7 |
| LMArena Text: hard prompts in English | 1508 | 1268 | Claude Opus 4.7 |
| LMArena Vision: diagrams | 1336 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Vision: homework | 1337 | Not measured | Only Claude Opus 4.7 measured |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Claude Opus 4.7 | Mistral Large | Leader |
|---|---|---|---|
| AIME | 96.3% | 9.2% | Claude Opus 4.7 |
| MATH 500 (Vals AI) | Not measured | 74.4% | Only Mistral Large measured |
| MGSM (Vals AI) | Not measured | 87.2% | Only Mistral Large measured |
| OTIS Mock AIME | 97.8% | Not measured | Only Claude Opus 4.7 measured |
| FrontierMath, tiers 1 to 3 | 70.2% | Not measured | Only Claude Opus 4.7 measured |
| FrontierMath, tier 4 | 31.7% | Not measured | Only Claude Opus 4.7 measured |
| ProofBench | 54.0% | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: math | 1498 | 1261 | Claude Opus 4.7 |
| LMArena Text: mathematical work | 1509 | 1257 | Claude Opus 4.7 |
| Neither model has a result on the other 4 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | Claude Opus 4.7 | Mistral Large | Leader |
|---|---|---|---|
| MMLU Pro | 89.9% | 69.7% | Claude Opus 4.7 |
| LegalBench (Vals AI) | 85.3% | Not measured | Only Claude Opus 4.7 measured |
| CaseLaw (Vals AI) | 68.4% | Not measured | Only Claude Opus 4.7 measured |
| CorpFin (Vals AI) | 66.1% | Not measured | Only Claude Opus 4.7 measured |
| TaxEval (Vals AI) | 75.3% | 63.8% | Claude Opus 4.7 |
| MortgageTax (Vals AI) | 70.3% | Not measured | Only Claude Opus 4.7 measured |
| MedQA (Vals AI) | Not measured | 76.2% | Only Mistral Large measured |
| MedCode (Vals AI) | 54.9% | Not measured | Only Claude Opus 4.7 measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 51.5% | Only Mistral Large measured |
| SimpleQA Verified | 51.7% | Not measured | Only Claude Opus 4.7 measured |
| MMLU | Not measured | 68.8% | Only Mistral Large measured |
| LMArena Text: science | 1508 | 1260 | Claude Opus 4.7 |
| LMArena Text: medicine and healthcare | 1495 | 1255 | Claude Opus 4.7 |
| LMArena Text: legal and government | 1504 | 1275 | Claude Opus 4.7 |
| LMArena Text: business and finance | 1490 | 1238 | Claude Opus 4.7 |
| Neither model has a result on the other 2 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Claude Opus 4.7 | Mistral Large | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index180
| Benchmark | Claude Opus 4.7 | Mistral Large | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 56.1% | Not measured | Only Claude Opus 4.7 measured |
| MedScribe (Vals AI) | 83.0% | Not measured | Only Claude Opus 4.7 measured |
| Vals Multimodal Index | 67.4% | Not measured | Only Claude Opus 4.7 measured |
| IFBench | 58.6% | Not measured | Only Claude Opus 4.7 measured |
| Long context reasoning (AA-LCR) | 78.7% | Not measured | Only Claude Opus 4.7 measured |
| DTBench | 94.7% | 60.8% | Claude Opus 4.7 |
| LMCA | 52.2% | Not measured | Only Claude Opus 4.7 measured |
| Furniture assembly | 33.3% | Not measured | Only Claude Opus 4.7 measured |
| ExploitBench | 26.5% | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text | 1490 | 1265 | Claude Opus 4.7 |
| LMArena Text: instruction following | 1498 | 1249 | Claude Opus 4.7 |
| LMArena Text: creative writing | 1486 | 1242 | Claude Opus 4.7 |
| LMArena Vision | 1317 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: English | 1496 | 1284 | Claude Opus 4.7 |
| LMArena Text: non-English | 1480 | 1235 | Claude Opus 4.7 |
| LMArena Text: Chinese | 1531 | 1239 | Claude Opus 4.7 |
| LMArena Text: German | 1495 | 1242 | Claude Opus 4.7 |
| LMArena Text: Japanese | 1474 | 1170 | Claude Opus 4.7 |
| LMArena Text: Korean | 1464 | 1202 | Claude Opus 4.7 |
| LMArena Text: French | 1503 | 1325 | Claude Opus 4.7 |
| LMArena Text: Spanish | 1494 | 1268 | Claude Opus 4.7 |
| LMArena Text: Russian | 1494 | 1252 | Claude Opus 4.7 |
| LMArena Text: Polish | 1489 | 1157 | Claude Opus 4.7 |
| LMArena Text: multi-turn | 1505 | 1260 | Claude Opus 4.7 |
| LMArena Text: longer queries | 1505 | 1261 | Claude Opus 4.7 |
| LMArena Text: writing and language | 1492 | 1261 | Claude Opus 4.7 |
| LMArena Text: entertainment and media | 1474 | 1230 | Claude Opus 4.7 |
| LMArena Vision: English | 1322 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Vision: Chinese | 1371 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Vision: reading text | 1327 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Vision: humor | 1309 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Vision: recognizing things | 1278 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Vision: creative writing | 1326 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Document | 1495 | Not measured | Only Claude Opus 4.7 measured |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Claude Opus 4.7 | Mistral Large | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Mistral Large costs less
Repository review
50K input + 3K output tokens
Mistral Large costs less
Agent loop
200K input + 10K output tokens
Mistral Large costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | Anthropic Claude Opus 4.7 | Mistral Large |
|---|---|---|
| Maker | Anthropic | Mistral AI |
| Weights | No public weights listed | No public weights listed |
| Released | April 16, 2026 | February 26, 2024 |
| Context window | 1M | 128K |
| Input $/Mtok | $5.00 | $2.00 |
| Output $/Mtok | $25.00 | $6.00 |
| Coding index | 67.5 | Not benchmarked |
| Independent measurements behind it | 4 | 0 |
| Cost per solved task | $2.95 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Claude Opus 4.7 better than Mistral Large for coding?
Only Claude Opus 4.7 has a coding score, 67.5 on the Vibe Coding Index; Mistral Large has none, so the two cannot be ranked on coding. Mistral Large has the edge where output tokens cost 4.2x less.
Which is cheaper, Claude Opus 4.7 or Mistral Large?
Claude Opus 4.7 costs $5.00 per million input tokens and $25.00 per million output tokens; Mistral Large costs $2.00 and $6.00. Cost per solved task is known for Claude Opus 4.7 only.
Which has the bigger context window, Claude Opus 4.7 or Mistral Large?
Claude Opus 4.7, with 1M tokens against 128K.
How many benchmarks is the Claude Opus 4.7 vs Mistral Large comparison based on?
38 benchmarks have a result for both models as of October 21, 2026. Claude Opus 4.7's coding index rests on 4 independent benchmarks and Mistral Large's on 0. Where only one model has a result, the page says so instead of naming a winner.