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Claude Opus 4.1 vs Mistral Large 2407

Claude Opus 4.1 leads Mistral Large 2407 on the Artificial Analysis Intelligence Index, 22.8 to 7.6, and Mistral Large 2407 costs 12.5x less per output token ($6.00 vs $75.00 per million). Updated October 21, 2026; 6 benchmarks have a result for both.

Claude Opus 4.1Anthropic
Coding
No data
Overall
50.2
Output $/M
$75.00
6
Mistral Large 2407Mistral AI
Coding
No data
Overall
No data
Output $/M
$6.00
0
vs boards won of 6 shared

Claude Opus 4.1 or Mistral Large 2407: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick Claude Opus 4.1 for a larger context window (200K against 131K tokens).

Shared results
6
Claude Opus 4.1 only
67
Mistral Large 2407 only
11
Like-for-like categories
4 of 9

Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.

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.

At a glance

Coding index
Claude Opus 4.1 not benchmarked, Mistral Large 2407 not benchmarked.
Widest category
Math, 60.4 points apart on average over 1 shared benchmark.
Widest single gap
OTIS Mock AIME: Claude Opus 4.1 68.9% against Mistral Large 2407 8.5%, 60.4 points apart on a 0 to 100 scale.
Output price
Claude Opus 4.1 $75.00 against Mistral Large 2407 $6.00 per million output tokens, 12.5x apart.
Context window
Claude Opus 4.1 takes 200K tokens, Mistral Large 2407 131K.

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.

Boards won, where both have a result
CategoryClaude Opus 4.1BarsMistral Large 2407Ties
Intelligence10
Reasoning20
Math10
General20
All shared boards60
CodingDirectional onlySix of these boards feed the Vibe Coding Index10 boards, none shared
Coding benchmarks for Claude Opus 4.1 and Mistral Large 2407
BenchmarkClaude Opus 4.1Mistral Large 2407Leader
LMArena WebDev1390Not measuredOnly Claude Opus 4.1 measured
LiveCodeBench (Vals AI)66.5%Not measuredOnly Claude Opus 4.1 measured
LiveCodeBench (Artificial Analysis run)Not measured26.7%Only Mistral Large 2407 measured
Terminal-Bench38.0%Not measuredOnly Claude Opus 4.1 measured
WeirdML45.9%Not measuredOnly Claude Opus 4.1 measured
Cybench42.0%Not measuredOnly Claude Opus 4.1 measured
LMArena Text: coding1479Not measuredOnly Claude Opus 4.1 measured
LMArena Text: software and IT1456Not measuredOnly Claude Opus 4.1 measured
LMArena WebDev: HTML1399Not measuredOnly Claude Opus 4.1 measured
SciCode4.6%Not measuredOnly Claude Opus 4.1 measured
Neither model has a result on the other 29 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Claude Opus 4.1 and Mistral Large 2407
BenchmarkClaude Opus 4.1Mistral Large 2407Leader
AA Intelligence Index22.87.6Claude Opus 4.1
Epoch Capabilities Index144.1Not measuredOnly Claude Opus 4.1 measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Agentic work benchmarks for Claude Opus 4.1 and Mistral Large 2407
BenchmarkClaude Opus 4.1Mistral Large 2407Leader
τ²-Bench TelecomNot measured33.0%Only Mistral Large 2407 measured
METR time horizons66.8%Not measuredOnly Claude Opus 4.1 measured
GDPval43.6%Not measuredOnly Claude Opus 4.1 measured
DeepResearch Bench48.3%Not measuredOnly Claude Opus 4.1 measured
Neither model has a result on the other 37 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
Reasoning benchmarks for Claude Opus 4.1 and Mistral Large 2407
BenchmarkClaude Opus 4.1Mistral Large 2407Leader
GPQA Diamond76.3%Not measuredOnly Claude Opus 4.1 measured
MMMU Pro (Vals AI)77.5%Not measuredOnly Claude Opus 4.1 measured
GPQA Diamond (Artificial Analysis run)Not measured47.2%Only Mistral Large 2407 measured
Humanity's Last Exam (Artificial Analysis run)Not measured2.9%Only Mistral Large 2407 measured
GPQA Diamond (Epoch AI run)77.3%49.0%Claude Opus 4.1
SimpleBench60.0%22.5%Claude Opus 4.1
Mystery game puzzles21.0%Not measuredOnly Claude Opus 4.1 measured
EBR-bench7.9%Not measuredOnly Claude Opus 4.1 measured
VPCT35.0%Not measuredOnly Claude Opus 4.1 measured
LMArena Text: hard prompts1442Not measuredOnly Claude Opus 4.1 measured
LMArena Text: expert1438Not measuredOnly Claude Opus 4.1 measured
LMArena Text: hard prompts in English1451Not measuredOnly Claude Opus 4.1 measured
Neither model has a result on the other 10 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index10
Math benchmarks for Claude Opus 4.1 and Mistral Large 2407
BenchmarkClaude Opus 4.1Mistral Large 2407Leader
AIME78.2%Not measuredOnly Claude Opus 4.1 measured
MATH 500 (Vals AI)95.4%Not measuredOnly Claude Opus 4.1 measured
MGSM (Vals AI)94.4%Not measuredOnly Claude Opus 4.1 measured
AA Math IndexNot measured0.0Only Mistral Large 2407 measured
AIME 2025 (Artificial Analysis run)Not measured0.0%Only Mistral Large 2407 measured
OTIS Mock AIME68.9%8.5%Claude Opus 4.1
FrontierMath, tiers 1 to 312.6%Not measuredOnly Claude Opus 4.1 measured
FrontierMath, tier 42.4%Not measuredOnly Claude Opus 4.1 measured
MATH level 5Not measured44.8%Only Mistral Large 2407 measured
LMArena Text: math1431Not measuredOnly Claude Opus 4.1 measured
LMArena Text: mathematical work1434Not measuredOnly Claude Opus 4.1 measured
Neither model has a result on the other 2 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index13 boards, none shared
Knowledge benchmarks for Claude Opus 4.1 and Mistral Large 2407
BenchmarkClaude Opus 4.1Mistral Large 2407Leader
MMLU Pro87.9%Not measuredOnly Claude Opus 4.1 measured
LegalBench (Vals AI)83.5%Not measuredOnly Claude Opus 4.1 measured
TaxEval (Vals AI)73.7%Not measuredOnly Claude Opus 4.1 measured
MortgageTax (Vals AI)61.1%Not measuredOnly Claude Opus 4.1 measured
MedQA (Vals AI)93.6%Not measuredOnly Claude Opus 4.1 measured
MedCode (Vals AI)47.2%Not measuredOnly Claude Opus 4.1 measured
MMLU Pro (Artificial Analysis run)Not measured68.3%Only Mistral Large 2407 measured
MMLUNot measured80.0%Only Mistral Large 2407 measured
LMArena Text: science1422Not measuredOnly Claude Opus 4.1 measured
LMArena Text: medicine and healthcare1416Not measuredOnly Claude Opus 4.1 measured
LMArena Text: legal and government1421Not measuredOnly Claude Opus 4.1 measured
LMArena Text: business and finance1406Not measuredOnly Claude Opus 4.1 measured
FACTS Benchmark Suite40.4%Not measuredOnly Claude Opus 4.1 measured
Neither model has a result on the other 5 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for Claude Opus 4.1 and Mistral Large 2407
BenchmarkClaude Opus 4.1Mistral Large 2407Leader
Design Arena: websites1177Not measuredOnly Claude Opus 4.1 measured
Design Arena: UI components1165Not measuredOnly Claude Opus 4.1 measured
Design Arena: game dev1171Not measuredOnly Claude Opus 4.1 measured
Design Arena: data viz1166Not measuredOnly Claude Opus 4.1 measured
Design Arena: 3D1153Not measuredOnly Claude Opus 4.1 measured
Design Arena: all code categories1171Not measuredOnly Claude Opus 4.1 measured
Design Arena: SVG1152Not measuredOnly Claude Opus 4.1 measured
Design Arena: ASCII art1167Not measuredOnly Claude Opus 4.1 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
General benchmarks for Claude Opus 4.1 and Mistral Large 2407
BenchmarkClaude Opus 4.1Mistral Large 2407Leader
SAGE (Vals AI)31.4%Not measuredOnly Claude Opus 4.1 measured
MedScribe (Vals AI)73.9%Not measuredOnly Claude Opus 4.1 measured
IFBenchNot measured31.6%Only Mistral Large 2407 measured
Long context reasoning (AA-LCR)Not measured2.0%Only Mistral Large 2407 measured
DTBench80.0%61.2%Claude Opus 4.1
LMCA37.1%Not measuredOnly Claude Opus 4.1 measured
Creative writing (Lech Mazur)84.7%69.0%Claude Opus 4.1
LMArena Text1419Not measuredOnly Claude Opus 4.1 measured
LMArena Text: instruction following1435Not measuredOnly Claude Opus 4.1 measured
LMArena Text: creative writing1412Not measuredOnly Claude Opus 4.1 measured
LMArena Text: English1433Not measuredOnly Claude Opus 4.1 measured
LMArena Text: non-English1405Not measuredOnly Claude Opus 4.1 measured
LMArena Text: Chinese1427Not measuredOnly Claude Opus 4.1 measured
LMArena Text: German1413Not measuredOnly Claude Opus 4.1 measured
LMArena Text: Japanese1377Not measuredOnly Claude Opus 4.1 measured
LMArena Text: Korean1381Not measuredOnly Claude Opus 4.1 measured
LMArena Text: French1433Not measuredOnly Claude Opus 4.1 measured
LMArena Text: Spanish1448Not measuredOnly Claude Opus 4.1 measured
LMArena Text: Russian1422Not measuredOnly Claude Opus 4.1 measured
LMArena Text: Polish1413Not measuredOnly Claude Opus 4.1 measured
LMArena Text: multi-turn1444Not measuredOnly Claude Opus 4.1 measured
LMArena Text: longer queries1455Not measuredOnly Claude Opus 4.1 measured
LMArena Text: writing and language1418Not measuredOnly Claude Opus 4.1 measured
LMArena Text: entertainment and media1398Not measuredOnly Claude Opus 4.1 measured
Neither model has a result on the other 22 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Opus 4.1 and Mistral Large 2407
BenchmarkClaude Opus 4.1Mistral Large 2407Leader
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

Claude Opus 4.1$0.052Fits in one request
Mistral Large 2407$0.0050Fits in one request

Mistral Large 2407 costs less

Repository review

50K input + 3K output tokens

Claude Opus 4.1$0.975Fits in one request
Mistral Large 2407$0.118Fits in one request

Mistral Large 2407 costs less

Agent loop

200K input + 10K output tokens

Claude Opus 4.1$3.75Exceeds the context window
Mistral Large 2407$0.460Exceeds the context window

Mistral Large 2407 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.

Specifications of Claude Opus 4.1 and Mistral Large 2407
SpecificationAnthropic Claude Opus 4.1Mistral Large 2407
MakerAnthropicMistral AI
WeightsNo public weights listedNo public weights listed
ReleasedAugust 5, 2025November 19, 2024
Context window200K131K
Input $/Mtok$15.00$2.00
Output $/Mtok$75.00$6.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it10
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Opus 4.1 better than Mistral Large 2407 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Claude Opus 4.1 for a larger context window (200K against 131K tokens).

Which is cheaper, Claude Opus 4.1 or Mistral Large 2407?

Claude Opus 4.1 costs $15.00 per million input tokens and $75.00 per million output tokens; Mistral Large 2407 costs $2.00 and $6.00. Cost per solved task is known for neither of them.

Which has the bigger context window, Claude Opus 4.1 or Mistral Large 2407?

Claude Opus 4.1, with 200K tokens against 131K.

How many benchmarks is the Claude Opus 4.1 vs Mistral Large 2407 comparison based on?

6 benchmarks have a result for both models as of October 21, 2026. Claude Opus 4.1's coding index rests on 1 independent benchmark and Mistral Large 2407's on 0. Where only one model has a result, the page says so instead of naming a winner.

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