Noometry

Model comparison

MiniMax-M2.7 vs Mistral Small 3.2

MiniMax-M2.7 is the stronger model overall, scoring 37.7 to 31.2 on the Noometry Index. Mistral Small 3.2 costs 4.0× less per token, which makes it the better buy when MiniMax-M2.7's lead doesn't matter for your workload.

Last verified . 1 shared benchmarks.

MiniMax-M2.7 MiniMax

37.7

Rank #196 Confirmed

Mistral Small 3.2 Mistral AI

31.2

Rank #280 Confirmed

Summary

  • They share 1 benchmark with published results for both. MiniMax-M2.7 scores higher in 3 categories and Mistral Small 3.2 in 1 category; 3 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where MiniMax-M2.7 leads 58.9 to 45.0.
  • Mistral Small 3.2 is cheaper at $0.0938 / $0.25 per million input/output tokens, against $0.30 / $1.20 for MiniMax-M2.7.
  • Mistral Small 3.2 accepts more context: 256K tokens versus 205K.

Side by side

MiniMax-M2.7Mistral Small 3.2
ProviderMiniMaxMistral AI
Noometry Index37.731.2
Released2026-03-182025-06-20
WeightsOpenOpen
Context window205K256K
Max output131K16K
Input $ / M tokens$0.30$0.0938
Output $ / M tokens$1.20$0.25
Results tracked306

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Category by category

Coding Not comparable

MiniMax-M2.7: 41.8 (#120), Mistral Small 3.2: —

BenchmarkMiniMax-M2.7Mistral Small 3.2
LMArena WebDev1398—
SciCode47%—
WeirdML37%—
LMArena Coding1454—
ALE-Bench599.25—

Agentic & Tool Use Not comparable

MiniMax-M2.7: 25.1 (#111), Mistral Small 3.2: —

BenchmarkMiniMax-M2.7Mistral Small 3.2
Terminal-Bench45.1%—
ExploitBench13.3%—
GBAEval0%—

Reasoning MiniMax-M2.7 leads

MiniMax-M2.7: 19.7 (#253), Mistral Small 3.2: 18.1 (#287)

BenchmarkMiniMax-M2.7Mistral Small 3.2
Epoch Capabilities Index145.85131.74
Kagi LLM Benchmark—40.4%
NYT Connections (extended)24.7%—
CritPt0.6%—
Chess Puzzles—1%
Thematic Generalization39.3%—
LMArena Hard Prompts1422—

Math Too close to call

MiniMax-M2.7: 25.9 (#263), Mistral Small 3.2: 26.3 (#260)

BenchmarkMiniMax-M2.7Mistral Small 3.2
OTIS Mock AIME 2024-2025—30.3%
ProofBench3%—
LMArena Math1420—

Knowledge MiniMax-M2.7 leads

MiniMax-M2.7: 37.7 (#152), Mistral Small 3.2: 26.7 (#256)

BenchmarkMiniMax-M2.7Mistral Small 3.2
GPQA Diamond—49.1%
Vectara Hallucination Rate12.9%—
LMArena Expert1444—

Multilingual Not comparable

MiniMax-M2.7: 50.3 (#123), Mistral Small 3.2: —

BenchmarkMiniMax-M2.7Mistral Small 3.2
LMArena Non-English1382—
LMArena Chinese1441—
LMArena French1421—
LMArena German1398—
LMArena Japanese1262—
LMArena Korean1313—
LMArena Russian1383—
LMArena Spanish1403—

Instruction Following Not comparable

MiniMax-M2.7: 74.1 (#103), Mistral Small 3.2: —

BenchmarkMiniMax-M2.7Mistral Small 3.2
LMArena Instruction Following1405—

Long Context Not comparable

MiniMax-M2.7: 43.3 (#99), Mistral Small 3.2: —

BenchmarkMiniMax-M2.7Mistral Small 3.2
LMArena Longer Query1419—

Writing & Preference MiniMax-M2.7 leads

MiniMax-M2.7: 58.9 (#112), Mistral Small 3.2: 45.0 (#224)

BenchmarkMiniMax-M2.7Mistral Small 3.2
LMArena Text1405—
LMArena Creative Writing1354—
EQ-Bench Creative Writing—1255
LMArena Multi-Turn1412—

Frequently asked questions

Is MiniMax-M2.7 better than Mistral Small 3.2?

MiniMax-M2.7 is the stronger model overall, scoring 37.7 to 31.2 on the Noometry Index. Mistral Small 3.2 costs 4.0× less per token, which makes it the better buy when MiniMax-M2.7's lead doesn't matter for your workload.

Which is cheaper, MiniMax-M2.7 or Mistral Small 3.2?

Mistral Small 3.2 is cheaper. It lists at $0.0938 per million input tokens and $0.25 per million output tokens; MiniMax-M2.7 lists at $0.30 and $1.20.

Which has the bigger context window?

Mistral Small 3.2 does, with 256K tokens against 205K.

How many benchmarks do MiniMax-M2.7 and Mistral Small 3.2 share?

1 benchmark has published results for both models. MiniMax-M2.7 has 30 scored results on Noometry and Mistral Small 3.2 has 6.

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