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Claude Opus 4.6 vs Mistral Large 4

Claude Opus 4.6 leads Mistral Large 4 on coding, 57.2 to 56.4 on the Vibe Coding Index, and Mistral Large 4 costs 6.0x less per output token ($4.18 vs $25.00 per million). Updated October 22, 2026; 59 benchmarks have a result for both.

Claude Opus 4.6Anthropic
Coding
57.2
Overall
66.0
Output $/M
$25.00
50
Mistral Large 4Mistral AI
Coding
56.4
Overall
54.6
Output $/M
$4.18
8
vs boards won of 59 shared, 1 tied

Claude Opus 4.6 or Mistral Large 4: which to pick

Claude Opus 4.6 and Mistral Large 4 are level for coding, 57.2 against 56.4 on the Vibe Coding Index, so price and context decide.

Pick Mistral Large 4 for output tokens 6.0x cheaper ($4.18 vs $25.00 per million) and a larger context window (1.05M against 1M tokens). Pick Claude Opus 4.6 for work measured by LMArena WebDev or LMArena Text: coding, where it leads.

Shared results
59
Claude Opus 4.6 only
51
Mistral Large 4 only
22
Like-for-like categories
7 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 4.6 57.2 from 4 benchmarks, Mistral Large 4 56.4 from 5 benchmarks.
Widest category
Knowledge, 13.9 points apart on average over 6 shared benchmarks.
Widest single gap
ProofBench: Claude Opus 4.6 50.0% against Mistral Large 4 10.0%, 40.0 points apart on a 0 to 100 scale.
Output price
Claude Opus 4.6 $25.00 against Mistral Large 4 $4.18 per million output tokens, 6.0x apart.
Context window
Claude Opus 4.6 takes 1M tokens, Mistral Large 4 1.05M.

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 4.6BarsMistral Large 4Ties
Coding43
Intelligence11
Reasoning71
Math411 tie
Knowledge60
Web design71
General211
All shared boards5081 tie
CodingLike-for-likeSix of these boards feed the Vibe Coding Index43
Coding benchmarks for Claude Opus 4.6 and Mistral Large 4
BenchmarkClaude Opus 4.6Mistral Large 4Leader
SWE-bench Verified75.6%Not measuredOnly Claude Opus 4.6 measured
SWE-bench Multilingual72.0%Not measuredOnly Claude Opus 4.6 measured
LiveBench codingNot measured60.0%Only Mistral Large 4 measured
LMArena WebDev15471543Claude Opus 4.6
LiveCodeBench (Vals AI)84.7%Not measuredOnly Claude Opus 4.6 measured
SWE-bench Verified (Vals AI)78.2%Not measuredOnly Claude Opus 4.6 measured
Terminal-Bench 4 (Vals AI)Not measured27.8%Only Mistral Large 4 measured
Vibe Code Bench (Vals AI)57.6%78.4%Mistral Large 4
Code migration (Vals AI)Not measured30.6%Only Mistral Large 4 measured
IOI (Vals AI)Not measured45.3%Only Mistral Large 4 measured
SWE-bench Multimodal (Vals AI)Not measured33.1%Only Mistral Large 4 measured
Vibe Code Bench 1-100 (Vals AI)Not measured14.3%Only Mistral Large 4 measured
SciCodeNot measured54.2%Only Mistral Large 4 measured
Terminal-Bench Hard (Artificial Analysis run)48.5%Not measuredOnly Claude Opus 4.6 measured
Terminal-Bench79.8%Not measuredOnly Claude Opus 4.6 measured
FrontierCode26.6%39.4%Mistral Large 4
GSO-Bench41.2%Not measuredOnly Claude Opus 4.6 measured
WeirdML78.0%Not measuredOnly Claude Opus 4.6 measured
Cybench93.0%Not measuredOnly Claude Opus 4.6 measured
ALE-BenchNot measured1213.2Only Mistral Large 4 measured
LMArena Text: coding15341478Claude Opus 4.6
LMArena Text: software and IT15271467Claude Opus 4.6
LMArena WebDev: React15391559Mistral Large 4
LMArena WebDev: HTML15591487Claude Opus 4.6
LMArena WebDev: from an image1543Not measuredOnly Claude Opus 4.6 measured
Neither model has a result on the other 14 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
Intelligence benchmarks for Claude Opus 4.6 and Mistral Large 4
BenchmarkClaude Opus 4.6Mistral Large 4Leader
AA Intelligence Index31.938.4Mistral Large 4
Epoch Capabilities Index155.7150.0Claude Opus 4.6
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index20 boards, none shared
Agentic work benchmarks for Claude Opus 4.6 and Mistral Large 4
BenchmarkClaude Opus 4.6Mistral Large 4Leader
Design Arena: agents building web apps1206Not measuredOnly Claude Opus 4.6 measured
Design Arena: agents building full-stack apps1220Not measuredOnly Claude Opus 4.6 measured
Design Arena: agents building mobile apps1207Not measuredOnly Claude Opus 4.6 measured
Design Arena: agents building Android apps1197Not measuredOnly Claude Opus 4.6 measured
Design Arena: agents building games1212Not measuredOnly Claude Opus 4.6 measured
LiveBench researchNot measured28.1%Only Mistral Large 4 measured
LiveBench browserNot measured8.0%Only Mistral Large 4 measured
LiveBench long agenticNot measured11.8%Only Mistral Large 4 measured
Finance Agent (Vals AI)Not measured54.7%Only Mistral Large 4 measured
Tax Agent Bench (Vals AI)Not measured30.4%Only Mistral Large 4 measured
Legal Research Bench (Vals AI)Not measured31.7%Only Mistral Large 4 measured
Harvey's Legal Agent Benchmark (Vals AI)Not measured17.5%Only Mistral Large 4 measured
Excel Modeling Benchmark (Vals AI)Not measured56.2%Only Mistral Large 4 measured
BioMysteryBench (Vals AI)Not measured67.0%Only Mistral Large 4 measured
τ²-Bench Telecom92.1%Not measuredOnly Claude Opus 4.6 measured
APEX-Agents46.3%Not measuredOnly Claude Opus 4.6 measured
METR time horizons78.9%Not measuredOnly Claude Opus 4.6 measured
Remote Labor Index4.2%Not measuredOnly Claude Opus 4.6 measured
DeepResearch Bench55.3%Not measuredOnly Claude Opus 4.6 measured
Vending-Bench 2$8,018Not measuredOnly Claude Opus 4.6 measured
Neither model has a result on the other 21 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index71
Reasoning benchmarks for Claude Opus 4.6 and Mistral Large 4
BenchmarkClaude Opus 4.6Mistral Large 4Leader
GPQA Diamond89.7%Not measuredOnly Claude Opus 4.6 measured
LiveBench reasoningNot measured83.9%Only Mistral Large 4 measured
MysteryMechanism (Vals AI)Not measured12.2%Only Mistral Large 4 measured
MMMU Pro (Vals AI)83.9%Not measuredOnly Claude Opus 4.6 measured
GPQA Diamond (Artificial Analysis run)89.6%Not measuredOnly Claude Opus 4.6 measured
Humanity's Last Exam (Artificial Analysis run)39.9%35.0%Claude Opus 4.6
GPQA Diamond (Epoch AI run)90.5%88.1%Claude Opus 4.6
ARC-AGI94.0%Not measuredOnly Claude Opus 4.6 measured
ARC-AGI-269.2%Not measuredOnly Claude Opus 4.6 measured
SimpleBench67.6%Not measuredOnly Claude Opus 4.6 measured
Chess puzzles21.0%33.0%Mistral Large 4
Mystery game puzzles25.0%17.0%Claude Opus 4.6
EBR-bench12.7%Not measuredOnly Claude Opus 4.6 measured
LMArena Text: hard prompts15251444Claude Opus 4.6
LMArena Text: expert15441444Claude Opus 4.6
LMArena Text: hard prompts in English15301442Claude Opus 4.6
LMArena Vision: diagrams13401288Claude Opus 4.6
LMArena Vision: homework1337Not measuredOnly Claude Opus 4.6 measured
Kagi LLM Benchmark83.6%Not measuredOnly Claude Opus 4.6 measured
Neither model has a result on the other 3 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index41
Math benchmarks for Claude Opus 4.6 and Mistral Large 4
BenchmarkClaude Opus 4.6Mistral Large 4Leader
AIME95.6%Not measuredOnly Claude Opus 4.6 measured
OTIS Mock AIME94.4%98.3%Mistral Large 4
FrontierMath, tiers 1 to 366.0%58.6%Claude Opus 4.6
FrontierMath, tier 426.8%26.8%Tie
ProofBench50.0%10.0%Claude Opus 4.6
LMArena Text: math15181469Claude Opus 4.6
LMArena Text: mathematical work15251462Claude Opus 4.6
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index60
Knowledge benchmarks for Claude Opus 4.6 and Mistral Large 4
BenchmarkClaude Opus 4.6Mistral Large 4Leader
MMLU Pro89.1%Not measuredOnly Claude Opus 4.6 measured
LegalBench (Vals AI)85.3%Not measuredOnly Claude Opus 4.6 measured
CaseLaw (Vals AI)62.1%Not measuredOnly Claude Opus 4.6 measured
CorpFin (Vals AI)67.0%Not measuredOnly Claude Opus 4.6 measured
TaxEval (Vals AI)76.0%Not measuredOnly Claude Opus 4.6 measured
MortgageTax (Vals AI)68.5%Not measuredOnly Claude Opus 4.6 measured
MedQA (Vals AI)95.4%Not measuredOnly Claude Opus 4.6 measured
MedCode (Vals AI)49.1%40.7%Claude Opus 4.6
SimpleQA Verified47.0%20.0%Claude Opus 4.6
LMArena Text: science15191448Claude Opus 4.6
LMArena Text: medicine and healthcare15041433Claude Opus 4.6
LMArena Text: legal and government15121425Claude Opus 4.6
LMArena Text: business and finance14971439Claude Opus 4.6
FACTS Benchmark Suite41.5%Not measuredOnly Claude Opus 4.6 measured
Neither model has a result on the other 4 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index71
Web design benchmarks for Claude Opus 4.6 and Mistral Large 4
BenchmarkClaude Opus 4.6Mistral Large 4Leader
Design Arena: websites12911257Claude Opus 4.6
Design Arena: UI components12811272Claude Opus 4.6
Design Arena: game dev12771225Claude Opus 4.6
Design Arena: data viz12791275Claude Opus 4.6
Design Arena: 3D12731252Claude Opus 4.6
Design Arena: all code categories12881259Claude Opus 4.6
Design Arena: SVG12271232Mistral Large 4
Design Arena: ASCII art12551202Claude Opus 4.6
LiveBench designNot measured65.6%Only Mistral Large 4 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index211
General benchmarks for Claude Opus 4.6 and Mistral Large 4
BenchmarkClaude Opus 4.6Mistral Large 4Leader
LiveBench data analysisNot measured76.5%Only Mistral Large 4 measured
SAGE (Vals AI)51.6%Not measuredOnly Claude Opus 4.6 measured
MedScribe (Vals AI)86.7%80.4%Claude Opus 4.6
IFBench53.1%Not measuredOnly Claude Opus 4.6 measured
Long context reasoning (AA-LCR)78.0%81.3%Mistral Large 4
DTBench91.2%88.2%Claude Opus 4.6
LMCA55.8%35.8%Claude Opus 4.6
CL-bench20.7%Not measuredOnly Claude Opus 4.6 measured
Surface Evolver BenchNot measured28.1%Only Mistral Large 4 measured
Furniture assembly28.3%20.8%Claude Opus 4.6
CL-bench Life17.0%Not measuredOnly Claude Opus 4.6 measured
LMArena Text15011431Claude Opus 4.6
LMArena Text: instruction following15211422Claude Opus 4.6
LMArena Text: creative writing15051363Claude Opus 4.6
LMArena Vision13161272Claude Opus 4.6
LMArena Text: English15111433Claude Opus 4.6
LMArena Text: non-English14881422Claude Opus 4.6
LMArena Text: Chinese15511492Claude Opus 4.6
LMArena Text: German1500Not measuredOnly Claude Opus 4.6 measured
LMArena Text: Japanese14881415Claude Opus 4.6
LMArena Text: Korean1464Not measuredOnly Claude Opus 4.6 measured
LMArena Text: French15121492Claude Opus 4.6
LMArena Text: Spanish15101455Claude Opus 4.6
LMArena Text: Russian14971417Claude Opus 4.6
LMArena Text: Polish1499Not measuredOnly Claude Opus 4.6 measured
LMArena Text: multi-turn15111435Claude Opus 4.6
LMArena Text: longer queries15181428Claude Opus 4.6
LMArena Text: writing and language15021386Claude Opus 4.6
LMArena Text: entertainment and media14921378Claude Opus 4.6
LMArena Vision: English13241283Claude Opus 4.6
LMArena Vision: Chinese1370Not measuredOnly Claude Opus 4.6 measured
LMArena Vision: reading text13261284Claude Opus 4.6
LMArena Vision: humor1314Not measuredOnly Claude Opus 4.6 measured
LMArena Vision: recognizing things1274Not measuredOnly Claude Opus 4.6 measured
LMArena Vision: creative writing1331Not measuredOnly Claude Opus 4.6 measured
LMArena Document1507Not measuredOnly Claude Opus 4.6 measured
Neither model has a result on the other 10 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Opus 4.6 and Mistral Large 4
BenchmarkClaude Opus 4.6Mistral Large 4Leader
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 4.6$0.018Fits in one request
Mistral Large 4$0.0034Fits in one request

Mistral Large 4 costs less

Repository review

50K input + 3K output tokens

Claude Opus 4.6$0.325Fits in one request
Mistral Large 4$0.081Fits in one request

Mistral Large 4 costs less

Agent loop

200K input + 10K output tokens

Claude Opus 4.6$1.25Fits in one request
Mistral Large 4$0.314Fits in one request

Mistral Large 4 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 4.6 and Mistral Large 4
SpecificationAnthropic Claude Opus 4.6Mistral Large 4
MakerAnthropicMistral AI
WeightsNo public weights listedNo public weights listed
ReleasedFebruary 4, 2026October 6, 2026
Context window1M1.05M
Input $/Mtok$5.00$1.36
Output $/Mtok$25.00$4.18
Coding index57.256.4
Independent measurements behind it45
Cost per solved task$1.56Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Opus 4.6 better than Mistral Large 4 for coding?

Claude Opus 4.6 and Mistral Large 4 are level for coding, 57.2 against 56.4 on the Vibe Coding Index, so price and context decide. Pick Mistral Large 4 for output tokens 6.0x cheaper ($4.18 vs $25.00 per million) and a larger context window (1.05M against 1M tokens). Pick Claude Opus 4.6 for work measured by LMArena WebDev or LMArena Text: coding, where it leads.

Which is cheaper, Claude Opus 4.6 or Mistral Large 4?

Claude Opus 4.6 costs $5.00 per million input tokens and $25.00 per million output tokens; Mistral Large 4 costs $1.36 and $4.18. Cost per solved task is known for Claude Opus 4.6 only.

Which has the bigger context window, Claude Opus 4.6 or Mistral Large 4?

Mistral Large 4, with 1.05M tokens against 1M.

How many benchmarks is the Claude Opus 4.6 vs Mistral Large 4 comparison based on?

59 benchmarks have a result for both models as of October 22, 2026. Claude Opus 4.6's coding index rests on 4 independent benchmarks and Mistral Large 4's on 5. Where only one model has a result, the page says so instead of naming a winner.

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