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Claude Opus 4.8 vs Mistral Large

Updated October 21, 2026. 37 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Claude Opus 4.8Anthropic
Coding
65.0
Overall
41.8
Output $/M
$25.00
37
Mistral LargeMistral AI
Coding
No data
Overall
5.8
Output $/M
$6.00
0
vs boards won of 37 shared

Decision reading

Only Claude Opus 4.8 has a coding score, 65.0 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
37
Claude Opus 4.8 only
89
Mistral Large only
7
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.

At a glance

Coding index
Claude Opus 4.8 65.0 from 6 benchmarks, Mistral Large not benchmarked.
Widest category
Reasoning, 45.0 points apart on average over 6 shared benchmarks.
Widest single gap
GPQA Diamond (Artificial Analysis run): Claude Opus 4.8 92.0% against Mistral Large 35.1%, 56.9 points apart on a 0 to 100 scale.
Output price
Claude Opus 4.8 $25.00 against Mistral Large $6.00 per million output tokens, 4.2x apart.
Context window
Claude Opus 4.8 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.

Boards won, where both have a result
CategoryClaude Opus 4.8BarsMistral LargeTies
Coding30
Intelligence20
Reasoning60
Math20
Knowledge60
General180
All shared boards370
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
Coding benchmarks for Claude Opus 4.8 and Mistral Large
BenchmarkClaude Opus 4.8Mistral LargeLeader
LiveBench coding77.3%Not measuredOnly Claude Opus 4.8 measured
LMArena WebDev1556Not measuredOnly Claude Opus 4.8 measured
AA Coding Index74.3Not measuredOnly Claude Opus 4.8 measured
LiveCodeBench (Vals AI)87.8%37.1%Claude Opus 4.8
SWE-bench Verified (Vals AI)88.6%Not measuredOnly Claude Opus 4.8 measured
Terminal-Bench 4 (Vals AI)23.2%Not measuredOnly Claude Opus 4.8 measured
Vibe Code Bench (Vals AI)82.7%Not measuredOnly Claude Opus 4.8 measured
Code migration (Vals AI)47.3%Not measuredOnly Claude Opus 4.8 measured
ProgramBench (Vals AI)1.0%Not measuredOnly Claude Opus 4.8 measured
Terminal-Bench 2.1 (Vals AI)71.9%Not measuredOnly Claude Opus 4.8 measured
SkillsBench (Vals AI)59.2%Not measuredOnly Claude Opus 4.8 measured
LiveCodeBench (Artificial Analysis run)Not measured17.8%Only Mistral Large measured
SciCode54.4%Not measuredOnly Claude Opus 4.8 measured
Terminal-Bench Hard (Artificial Analysis run)58.3%Not measuredOnly Claude Opus 4.8 measured
FrontierCode46.5%Not measuredOnly Claude Opus 4.8 measured
GSO-Bench47.1%Not measuredOnly Claude Opus 4.8 measured
WeirdML82.9%Not measuredOnly Claude Opus 4.8 measured
LMArena Text: coding14901275Claude Opus 4.8
LMArena Text: software and IT14881274Claude Opus 4.8
LMArena WebDev: React1557Not measuredOnly Claude Opus 4.8 measured
LMArena WebDev: HTML1543Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 17 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for Claude Opus 4.8 and Mistral Large
BenchmarkClaude Opus 4.8Mistral LargeLeader
AA Intelligence Index41.85.8Claude Opus 4.8
Epoch Capabilities Index159.0122.1Claude Opus 4.8
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index26 boards, none shared
Agentic work benchmarks for Claude Opus 4.8 and Mistral Large
BenchmarkClaude Opus 4.8Mistral LargeLeader
AA Agentic Index41.9Not measuredOnly Claude Opus 4.8 measured
Design Arena: agents building web apps1233Not measuredOnly Claude Opus 4.8 measured
Design Arena: agents building full-stack apps1249Not measuredOnly Claude Opus 4.8 measured
Design Arena: agents building mobile apps1223Not measuredOnly Claude Opus 4.8 measured
Design Arena: agents building Android apps1238Not measuredOnly Claude Opus 4.8 measured
Design Arena: agents building Godot games1231Not measuredOnly Claude Opus 4.8 measured
Design Arena: agents building games1238Not measuredOnly Claude Opus 4.8 measured
Design Arena: HTML slides1221Not measuredOnly Claude Opus 4.8 measured
Design Arena: PowerPoint slides1227Not measuredOnly Claude Opus 4.8 measured
LiveBench research81.8%Not measuredOnly Claude Opus 4.8 measured
LiveBench browser96.0%Not measuredOnly Claude Opus 4.8 measured
LiveBench long agentic48.3%Not measuredOnly Claude Opus 4.8 measured
Finance Agent (Vals AI)53.9%Not measuredOnly Claude Opus 4.8 measured
Tax Agent Bench (Vals AI)30.0%Not measuredOnly Claude Opus 4.8 measured
Legal Research Bench (Vals AI)43.8%Not measuredOnly Claude Opus 4.8 measured
Excel Modeling Benchmark (Vals AI)69.4%Not measuredOnly Claude Opus 4.8 measured
Terminal-Bench-Science (Vals AI)4.3%Not measuredOnly Claude Opus 4.8 measured
Time Horizon Index (Vals AI)11.8%Not measuredOnly Claude Opus 4.8 measured
τ²-Bench Telecom94.4%Not measuredOnly Claude Opus 4.8 measured
APEX-Agents48.9%Not measuredOnly Claude Opus 4.8 measured
Remote Labor Index8.3%Not measuredOnly Claude Opus 4.8 measured
OSWorld 2.020.6%Not measuredOnly Claude Opus 4.8 measured
DeepResearch Bench50.2%Not measuredOnly Claude Opus 4.8 measured
PostTrainBench33.8%Not measuredOnly Claude Opus 4.8 measured
Vending-Bench 2$5,787Not measuredOnly Claude Opus 4.8 measured
LMArena Search1204Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 13 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index60
Reasoning benchmarks for Claude Opus 4.8 and Mistral Large
BenchmarkClaude Opus 4.8Mistral LargeLeader
GPQA Diamond92.4%47.7%Claude Opus 4.8
LiveBench reasoning89.2%Not measuredOnly Claude Opus 4.8 measured
MMMU Pro (Vals AI)86.6%Not measuredOnly Claude Opus 4.8 measured
GPQA Diamond (Artificial Analysis run)92.0%35.1%Claude Opus 4.8
Humanity's Last Exam (Artificial Analysis run)48.7%3.5%Claude Opus 4.8
GPQA Diamond (Epoch AI run)91.0%Not measuredOnly Claude Opus 4.8 measured
ARC-AGI92.5%Not measuredOnly Claude Opus 4.8 measured
ARC-AGI-272.1%Not measuredOnly Claude Opus 4.8 measured
SimpleBench64.8%Not measuredOnly Claude Opus 4.8 measured
Chess puzzles52.0%Not measuredOnly Claude Opus 4.8 measured
Mystery game puzzles36.0%Not measuredOnly Claude Opus 4.8 measured
EBR-bench28.6%Not measuredOnly Claude Opus 4.8 measured
LMArena Text: hard prompts14821257Claude Opus 4.8
LMArena Text: expert15031208Claude Opus 4.8
LMArena Text: hard prompts in English14871268Claude Opus 4.8
LMArena Vision: diagrams1315Not measuredOnly Claude Opus 4.8 measured
LMArena Vision: homework1337Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 4 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for Claude Opus 4.8 and Mistral Large
BenchmarkClaude Opus 4.8Mistral LargeLeader
AIMENot measured9.2%Only Mistral Large measured
MATH 500 (Vals AI)Not measured74.4%Only Mistral Large measured
MGSM (Vals AI)Not measured87.2%Only Mistral Large measured
OTIS Mock AIME98.3%Not measuredOnly Claude Opus 4.8 measured
FrontierMath, tiers 1 to 380.0%Not measuredOnly Claude Opus 4.8 measured
FrontierMath, tier 456.1%Not measuredOnly Claude Opus 4.8 measured
ProofBench69.0%Not measuredOnly Claude Opus 4.8 measured
LMArena Text: math14861261Claude Opus 4.8
LMArena Text: mathematical work14971257Claude Opus 4.8
Neither model has a result on the other 4 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index60
Knowledge benchmarks for Claude Opus 4.8 and Mistral Large
BenchmarkClaude Opus 4.8Mistral LargeLeader
MMLU Pro89.6%69.7%Claude Opus 4.8
LegalBench (Vals AI)83.6%Not measuredOnly Claude Opus 4.8 measured
CorpFin (Vals AI)66.7%Not measuredOnly Claude Opus 4.8 measured
TaxEval (Vals AI)75.6%63.8%Claude Opus 4.8
MortgageTax (Vals AI)69.9%Not measuredOnly Claude Opus 4.8 measured
MedQA (Vals AI)Not measured76.2%Only Mistral Large measured
MedCode (Vals AI)53.2%Not measuredOnly Claude Opus 4.8 measured
MMLU Pro (Artificial Analysis run)Not measured51.5%Only Mistral Large measured
SimpleQA Verified53.0%Not measuredOnly Claude Opus 4.8 measured
MMLUNot measured68.8%Only Mistral Large measured
LMArena Text: science14771260Claude Opus 4.8
LMArena Text: medicine and healthcare14641255Claude Opus 4.8
LMArena Text: legal and government14771275Claude Opus 4.8
LMArena Text: business and finance14581238Claude Opus 4.8
Neither model has a result on the other 3 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
Web design benchmarks for Claude Opus 4.8 and Mistral Large
BenchmarkClaude Opus 4.8Mistral LargeLeader
Design Arena: websites1259Not measuredOnly Claude Opus 4.8 measured
Design Arena: UI components1257Not measuredOnly Claude Opus 4.8 measured
Design Arena: game dev1264Not measuredOnly Claude Opus 4.8 measured
Design Arena: data viz1239Not measuredOnly Claude Opus 4.8 measured
Design Arena: 3D1223Not measuredOnly Claude Opus 4.8 measured
Design Arena: all code categories1255Not measuredOnly Claude Opus 4.8 measured
Design Arena: SVG1194Not measuredOnly Claude Opus 4.8 measured
Design Arena: ASCII art1276Not measuredOnly Claude Opus 4.8 measured
LiveBench design78.8%Not measuredOnly Claude Opus 4.8 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index180
General benchmarks for Claude Opus 4.8 and Mistral Large
BenchmarkClaude Opus 4.8Mistral LargeLeader
LiveBench data analysis66.0%Not measuredOnly Claude Opus 4.8 measured
Public Benefits Bench (Vals AI)68.1%Not measuredOnly Claude Opus 4.8 measured
SAGE (Vals AI)54.8%Not measuredOnly Claude Opus 4.8 measured
MedScribe (Vals AI)85.8%Not measuredOnly Claude Opus 4.8 measured
Vals Multimodal Index70.9%Not measuredOnly Claude Opus 4.8 measured
IFBench62.2%Not measuredOnly Claude Opus 4.8 measured
Long context reasoning (AA-LCR)77.7%Not measuredOnly Claude Opus 4.8 measured
DTBench94.9%60.8%Claude Opus 4.8
LMCA57.5%Not measuredOnly Claude Opus 4.8 measured
Surface Evolver Bench87.5%Not measuredOnly Claude Opus 4.8 measured
Furniture assembly42.5%Not measuredOnly Claude Opus 4.8 measured
LMArena Text14611265Claude Opus 4.8
LMArena Text: instruction following14761249Claude Opus 4.8
LMArena Text: creative writing14541242Claude Opus 4.8
LMArena Vision1294Not measuredOnly Claude Opus 4.8 measured
LMArena Text: English14681284Claude Opus 4.8
LMArena Text: non-English14501235Claude Opus 4.8
LMArena Text: Chinese15061239Claude Opus 4.8
LMArena Text: German14721242Claude Opus 4.8
LMArena Text: Japanese14421170Claude Opus 4.8
LMArena Text: Korean14311202Claude Opus 4.8
LMArena Text: French14811325Claude Opus 4.8
LMArena Text: Spanish14651268Claude Opus 4.8
LMArena Text: Russian14741252Claude Opus 4.8
LMArena Text: Polish14591157Claude Opus 4.8
LMArena Text: multi-turn14761260Claude Opus 4.8
LMArena Text: longer queries14831261Claude Opus 4.8
LMArena Text: writing and language14611261Claude Opus 4.8
LMArena Text: entertainment and media14401230Claude Opus 4.8
LMArena Vision: English1293Not measuredOnly Claude Opus 4.8 measured
LMArena Vision: Chinese1346Not measuredOnly Claude Opus 4.8 measured
LMArena Vision: reading text1303Not measuredOnly Claude Opus 4.8 measured
LMArena Vision: humor1282Not measuredOnly Claude Opus 4.8 measured
LMArena Vision: creative writing1301Not measuredOnly Claude Opus 4.8 measured
LMArena Document1475Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 11 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Opus 4.8 and Mistral Large
BenchmarkClaude Opus 4.8Mistral LargeLeader
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 4.8$0.018Fits in one request
Mistral Large$0.0050Fits in one request

Mistral Large costs less

Repository review

50K input + 3K output tokens

Claude Opus 4.8$0.325Fits in one request
Mistral Large$0.118Fits in one request

Mistral Large costs less

Agent loop

200K input + 10K output tokens

Claude Opus 4.8$1.25Fits in one request
Mistral Large$0.460Exceeds the context window

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.

Specifications of Claude Opus 4.8 and Mistral Large
SpecificationAnthropic Claude Opus 4.8Mistral Large
MakerAnthropicMistral AI
WeightsNo public weights listedNo public weights listed
ReleasedMay 27, 2026February 26, 2024
Context window1M128K
Input $/Mtok$5.00$2.00
Output $/Mtok$25.00$6.00
Coding index65.0Not benchmarked
Independent measurements behind it60
Cost per solved task$2.17Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Opus 4.8 better than Mistral Large for coding?

Only Claude Opus 4.8 has a coding score, 65.0 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 4.8 or Mistral Large?

Claude Opus 4.8 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 4.8 only.

Which has the bigger context window, Claude Opus 4.8 or Mistral Large?

Claude Opus 4.8, with 1M tokens against 128K.

How many benchmarks is the Claude Opus 4.8 vs Mistral Large comparison based on?

37 benchmarks have a result for both models as of October 21, 2026. Claude Opus 4.8's coding index rests on 6 independent benchmarks and Mistral Large's on 0. Where only one model has a result, the page says so instead of naming a winner.

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