Noometry

Model comparison

Claude Opus 4.8 vs Mistral Large

Claude Opus 4.8 is the stronger model overall, scoring 60.7 to 31.9 on the Noometry Index. Mistral Large costs 3.3× less per token, which makes it the better buy when Claude Opus 4.8's lead doesn't matter for your workload.

Last verified . 29 shared benchmarks.

Claude Opus 4.8 Anthropic

60.7

Rank #13 Confirmed

Mistral Large Mistral AI

31.9

Rank #263 Confirmed

Summary

  • They share 29 benchmarks with published results for both. Claude Opus 4.8 scores higher in 9 categories and Mistral Large in 0 categories; 9 gaps are clear of the uncertainty.
  • The widest gap is in math, where Claude Opus 4.8 leads 78.4 to 18.2.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 98.3% for Claude Opus 4.8 and 8.5% for Mistral Large.
  • Mistral Large is cheaper at $2 / $6 per million input/output tokens, against $5 / $25 for Claude Opus 4.8.
  • Claude Opus 4.8 accepts more context: 1M tokens versus 131K.
  • Mistral Large has downloadable open weights; the other is API-only.

Side by side

Claude Opus 4.8Mistral Large
ProviderAnthropicMistral AI
Noometry Index60.731.9
Released2026-05-282024-02-26
WeightsProprietaryOpen
Context window1M131K
Max output128K16K
Input $ / M tokens$5$2
Output $ / M tokens$25$6
Results tracked6551

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Category by category

Coding Claude Opus 4.8 leads

Claude Opus 4.8: 59.9 (#12), Mistral Large: 34.3 (#240)

BenchmarkClaude Opus 4.8Mistral Large
SciCode53.5%36.2%
LMArena Coding14901277
ALE-Bench1,564264.7
DeepSWE59%—
FrontierCode46.5%—
LMArena WebDev1556—
GSO47.1%—
WeirdML82.9%—
BigCodeBench Instruct—30%
LiveBench Coding—47.1%
BigCodeBench Complete—38.3%
HumanEval+—62.2%
MBPP+—59.5%

Agentic & Tool Use Claude Opus 4.8 leads

Claude Opus 4.8: 47.6 (#11), Mistral Large: 28.6 (#89)

BenchmarkClaude Opus 4.8Mistral Large
APEX-Agents48.9%—
Berkeley Function Calling Leaderboard—38.4%
OSWorld 2.020.6%—
Remote Labor Index8.3%—
τ²-bench Banking39.7%—
DeepResearch Bench50.2%—
PostTrainBench33.8%—
GBAEval70.9%—
GDP.pdf24%—
LMArena Search1204—
Vending-Bench 25,787—

Reasoning Claude Opus 4.8 leads

Claude Opus 4.8: 64.7 (#16), Mistral Large: 15.8 (#310)

BenchmarkClaude Opus 4.8Mistral Large
SimpleBench64.8%22.5%
CritPt20.9%0%
LMArena Hard Prompts14821257
DTBench94.9%65.1%
LMCA57.5%16.7%
Epoch Capabilities Index158.21128.52
ForecastBench59.957.1
ARC-AGI-272.1%—
Kagi LLM Benchmark88.8%—
NYT Connections (extended)91.1%—
ARC-AGI-192.5%—
Chess Puzzles34%—
EnigmaEval23.5%—
EBR-Bench28.6%—
LiveBench Reasoning—43.5%
Mystery Game Puzzles36%—
LiveBench Data Analysis—50.1%
Surface Evolver Bench87.5%—
Bench to the Future 30.14—
LiveBench—48.4%

Math Claude Opus 4.8 leads

Claude Opus 4.8: 78.4 (#13), Mistral Large: 18.2 (#291)

BenchmarkClaude Opus 4.8Mistral Large
OTIS Mock AIME 2024-202598.3%8.5%
LMArena Math14871262
FrontierMath (Feb 2025 set)47.2%0.3%
FrontierMath (Tiers 1-3)80%—
FrontierMath Tier 456.1%—
MathArena Final-Answer Competitions91.8%—
ProofBench69%—
Omni-MATH—28.1%
LiveBench Math—42.5%
MATH Level 5—50.3%
FrontierMath Tier 4 (v1)31.3%—

Knowledge Claude Opus 4.8 leads

Claude Opus 4.8: 61.3 (#29), Mistral Large: 30.1 (#230)

BenchmarkClaude Opus 4.8Mistral Large
GPQA Diamond91%51.3%
LMArena Expert15021232
SimpleQA Verified53%—
MMLU-Pro—59.9%
Confabulations—21.4%
Vectara Hallucination Rate—4.5%
GPQA (HELM)—43.5%
MMLU—80%

Multimodal Not comparable

Claude Opus 4.8: 42.9 (#26), Mistral Large: —

BenchmarkClaude Opus 4.8Mistral Large
LMArena Vision1294—
Blueprint-Bench 214.5%—
Furniture Assembly42.5%—
LMArena Document1475—

Multilingual Claude Opus 4.8 leads

Claude Opus 4.8: 55.2 (#33), Mistral Large: 40.0 (#219)

BenchmarkClaude Opus 4.8Mistral Large
LMArena Non-English14501237
LMArena Chinese15071240
LMArena French14811325
LMArena German14721254
LMArena Japanese14401188
LMArena Korean14321202
LMArena Russian14741257
LMArena Spanish14661268

Instruction Following Claude Opus 4.8 leads

Claude Opus 4.8: 77.4 (#24), Mistral Large: 67.9 (#191)

BenchmarkClaude Opus 4.8Mistral Large
LMArena Instruction Following14761249
LiveBench Instruction Following—67.9%
IFEval—87.7%

Long Context Claude Opus 4.8 leads

Claude Opus 4.8: 45.4 (#35), Mistral Large: 38.3 (#199)

BenchmarkClaude Opus 4.8Mistral Large
LMArena Longer Query14831261

Writing & Preference Claude Opus 4.8 leads

Claude Opus 4.8: 72.0 (#16), Mistral Large: 40.7 (#242)

BenchmarkClaude Opus 4.8Mistral Large
LMArena Text14611266
LMArena Creative Writing14541243
EQ-Bench Creative Writing1840985
LMArena Multi-Turn14761260
Short-Story Creative Writing—69%
WildBench—80.1%
EQ-Bench 41281—
LiveBench Language—39.4%

Frequently asked questions

Is Claude Opus 4.8 better than Mistral Large?

Claude Opus 4.8 is the stronger model overall, scoring 60.7 to 31.9 on the Noometry Index. Mistral Large costs 3.3× less per token, which makes it the better buy when Claude Opus 4.8's lead doesn't matter for your workload.

Which is cheaper, Claude Opus 4.8 or Mistral Large?

Mistral Large is cheaper. It lists at $2 per million input tokens and $6 per million output tokens; Claude Opus 4.8 lists at $5 and $25.

Is Claude Opus 4.8 or Mistral Large better for coding?

Claude Opus 4.8 scores higher on coding benchmarks: 59.9 versus 34.3 in the Noometry coding category.

Which has the bigger context window?

Claude Opus 4.8 does, with 1M tokens against 131K.

How many benchmarks do Claude Opus 4.8 and Mistral Large share?

29 benchmarks have published results for both models. Claude Opus 4.8 has 65 scored results on Noometry and Mistral Large has 51.

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