Noometry

Model comparison

Claude Opus 4.7 vs Mistral Large

Claude Opus 4.7 is the stronger model overall, scoring 58.3 to 31.9 on the Noometry Index. Mistral Large costs 3.3× less per token, which makes it the better buy when Claude Opus 4.7's lead doesn't matter for your workload.

Last verified . 30 shared benchmarks.

Claude Opus 4.7 Anthropic

58.3

Rank #19 Confirmed

Mistral Large Mistral AI

31.9

Rank #263 Confirmed

Summary

  • They share 30 benchmarks with published results for both. Claude Opus 4.7 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 4.7 leads 66.7 to 18.2.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 97.8% for Claude Opus 4.7 and 8.5% for Mistral Large.
  • Mistral Large is cheaper at $2 / $6 per million input/output tokens, against $5 / $25 for Claude Opus 4.7.
  • Claude Opus 4.7 accepts more context: 1M tokens versus 131K.
  • Mistral Large has downloadable open weights; the other is API-only.

Side by side

Claude Opus 4.7Mistral Large
ProviderAnthropicMistral AI
Noometry Index58.331.9
Released2026-04-142024-02-26
WeightsProprietaryOpen
Context window1M131K
Max output128K16K
Input $ / M tokens$5$2
Output $ / M tokens$25$6
Results tracked6651

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Category by category

Coding Claude Opus 4.7 leads

Claude Opus 4.7: 59.6 (#13), Mistral Large: 34.3 (#240)

BenchmarkClaude Opus 4.7Mistral Large
SciCode54.5%36.2%
LMArena Coding15181277
ALE-Bench1,323264.7
SWE-bench Verified83.5%—
FrontierCode38.5%—
LMArena WebDev1558—
GSO44.1%—
WeirdML76.4%—
BigCodeBench Instruct—30%
LiveBench Coding—47.1%
MirrorCode31.1%—
BigCodeBench Complete—38.3%
HumanEval+—62.2%
MBPP+—59.5%

Agentic & Tool Use Claude Opus 4.7 leads

Claude Opus 4.7: 47.9 (#10), Mistral Large: 28.6 (#89)

BenchmarkClaude Opus 4.7Mistral Large
Terminal-Bench80.2%—
APEX-Agents49.2%—
Berkeley Function Calling Leaderboard—38.4%
OSWorld 2.018.2%—
τ²-bench Banking40.2%—
PostTrainBench28.6%—
ExploitBench26.5%—
GBAEval43.8%—
GDP.pdf21%—
LMArena Search1233—
Vending-Bench 210,937—

Reasoning Claude Opus 4.7 leads

Claude Opus 4.7: 53.8 (#29), Mistral Large: 15.8 (#310)

BenchmarkClaude Opus 4.7Mistral Large
SimpleBench61.7%22.5%
CritPt12%0%
LMArena Hard Prompts15061257
DTBench94.7%65.1%
LMCA52.2%16.7%
Epoch Capabilities Index156.25128.52
ForecastBench60.357.1
ARC-AGI-275.8%—
Kagi LLM Benchmark80.7%—
NYT Connections (extended)39%—
ARC-AGI-193.5%—
Chess Puzzles30%—
Thematic Generalization72.8%—
EBR-Bench19%—
LiveBench Reasoning—43.5%
Mystery Game Puzzles28%—
LiveBench Data Analysis—50.1%
LiveBench—48.4%

Math Claude Opus 4.7 leads

Claude Opus 4.7: 66.7 (#26), Mistral Large: 18.2 (#291)

BenchmarkClaude Opus 4.7Mistral Large
OTIS Mock AIME 2024-202597.8%8.5%
LMArena Math14991262
FrontierMath (Feb 2025 set)43.8%0.3%
FrontierMath (Tiers 1-3)70.2%—
FrontierMath Tier 431.7%—
MathArena Final-Answer Competitions73.6%—
ProofBench54%—
Omni-MATH—28.1%
LiveBench Math—42.5%
MATH Level 5—50.3%
FrontierMath Tier 4 (v1)22.9%—

Knowledge Claude Opus 4.7 leads

Claude Opus 4.7: 62.6 (#23), Mistral Large: 30.1 (#230)

BenchmarkClaude Opus 4.7Mistral Large
GPQA Diamond90.2%51.3%
Vectara Hallucination Rate12%4.5%
LMArena Expert15211232
Humanity's Last Exam36.2%—
SimpleQA Verified51.7%—
MMLU-Pro—59.9%
Confabulations—21.4%
GPQA (HELM)—43.5%
MMLU—80%

Multimodal Not comparable

Claude Opus 4.7: 41.2 (#38), Mistral Large: —

BenchmarkClaude Opus 4.7Mistral Large
LMArena Vision1316—
Blueprint-Bench 224.5%—
Furniture Assembly33.3%—
LMArena Document1495—

Multilingual Claude Opus 4.7 leads

Claude Opus 4.7: 57.3 (#10), Mistral Large: 40.0 (#219)

BenchmarkClaude Opus 4.7Mistral Large
LMArena Non-English14801237
LMArena Chinese15311240
LMArena French15031325
LMArena German14951254
LMArena Japanese14721188
LMArena Korean14641202
LMArena Russian14941257
LMArena Spanish14951268

Instruction Following Claude Opus 4.7 leads

Claude Opus 4.7: 78.4 (#10), Mistral Large: 67.9 (#191)

BenchmarkClaude Opus 4.7Mistral Large
LMArena Instruction Following14981249
LiveBench Instruction Following—67.9%
IFEval—87.7%

Long Context Claude Opus 4.7 leads

Claude Opus 4.7: 46.2 (#25), Mistral Large: 38.3 (#199)

BenchmarkClaude Opus 4.7Mistral Large
LMArena Longer Query15051261

Writing & Preference Claude Opus 4.7 leads

Claude Opus 4.7: 75.1 (#8), Mistral Large: 40.7 (#242)

BenchmarkClaude Opus 4.7Mistral Large
LMArena Text14901266
LMArena Creative Writing14861243
EQ-Bench Creative Writing1914985
LMArena Multi-Turn15051260
Short-Story Creative Writing—69%
WildBench—80.1%
EQ-Bench 41311—
LiveBench Language—39.4%

Frequently asked questions

Is Claude Opus 4.7 better than Mistral Large?

Claude Opus 4.7 is the stronger model overall, scoring 58.3 to 31.9 on the Noometry Index. Mistral Large costs 3.3× less per token, which makes it the better buy when Claude Opus 4.7's lead doesn't matter for your workload.

Which is cheaper, Claude Opus 4.7 or Mistral Large?

Mistral Large is cheaper. It lists at $2 per million input tokens and $6 per million output tokens; Claude Opus 4.7 lists at $5 and $25.

Is Claude Opus 4.7 or Mistral Large better for coding?

Claude Opus 4.7 scores higher on coding benchmarks: 59.6 versus 34.3 in the Noometry coding category.

Which has the bigger context window?

Claude Opus 4.7 does, with 1M tokens against 131K.

How many benchmarks do Claude Opus 4.7 and Mistral Large share?

30 benchmarks have published results for both models. Claude Opus 4.7 has 66 scored results on Noometry and Mistral Large has 51.

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