Model comparison

MiniMax-M2 vs Mixtral 8x22B

MiniMax-M2 is the stronger model overall, scoring 37.4 to 27.1 on the Noometry Index.

Last verified . 15 shared benchmarks.

MiniMax-M2 MiniMax

37.4

Rank #204 Confirmed

Mixtral 8x22B Mistral AI

27.1

Rank #333 Confirmed

Summary

  • They share 15 benchmarks with published results for both. MiniMax-M2 scores higher in 8 categories and Mixtral 8x22B in 1 category; 8 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where MiniMax-M2 leads 37.0 to 15.1.
  • MiniMax-M2 is cheaper at $0.30 / $1.20 per million input/output tokens, against $2 / $6 for Mixtral 8x22B.
  • MiniMax-M2 accepts more context: 205K tokens versus 64K.

Side by side

MiniMax-M2 and Mixtral 8x22B specifications
MiniMax-M2Mixtral 8x22B
ProviderMiniMaxMistral AI
Noometry Index37.427.1
Released2025-10-272024-04-17
WeightsOpenOpen
Context window205K64K
Max output131K64K
Input $ / M tokens$0.30$2
Output $ / M tokens$1.20$6
Results tracked2134

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Category by category

Coding MiniMax-M2 leads

MiniMax-M2: 39.3 (#159), Mixtral 8x22B: 24.2 (#329)

Coding benchmarks
BenchmarkMiniMax-M2Mixtral 8x22B
LMArena Coding13701166
SWE-bench Verified (bash only)61%—
LMArena WebDev1297—
WeirdML—3.2%
BigCodeBench Instruct—40.6%
BigCodeBench Complete—50.2%
HumanEval+—72%
MBPP+—64.3%

Agentic & Tool Use MiniMax-M2 leads

MiniMax-M2: 25.1 (#109), Mixtral 8x22B: 23.1 (#127)

Agentic & Tool Use benchmarks
BenchmarkMiniMax-M2Mixtral 8x22B
Terminal-Bench30%—
Cybench—7.5%
Vending-Bench 2160.6—

Reasoning Too close to call

MiniMax-M2: 19.4 (#258), Mixtral 8x22B: 19.9 (#248)

Reasoning benchmarks
BenchmarkMiniMax-M2Mixtral 8x22B
LMArena Hard Prompts13571150
Kagi LLM Benchmark57.8%—
NYT Connections (extended)14.8%—
DTBench—55.1%
Epoch Capabilities Index—122.03
ForecastBench—56.3

Math MiniMax-M2 leads

MiniMax-M2: 37.3 (#160), Mixtral 8x22B: 22.9 (#275)

Math benchmarks
BenchmarkMiniMax-M2Mixtral 8x22B
LMArena Math13521184
Omni-MATH—16.3%
MATH Level 5—24.2%

Knowledge MiniMax-M2 leads

MiniMax-M2: 37.0 (#163), Mixtral 8x22B: 15.1 (#293)

Knowledge benchmarks
BenchmarkMiniMax-M2Mixtral 8x22B
LMArena Expert13371113
GPQA Diamond—34.1%
MMLU-Pro—46%
GPQA (HELM)—33.4%
MMLU—77.8%

Multilingual MiniMax-M2 leads

MiniMax-M2: 45.3 (#171), Mixtral 8x22B: 32.8 (#255)

Multilingual benchmarks
BenchmarkMiniMax-M2Mixtral 8x22B
LMArena Non-English13131128
LMArena Chinese13661116
LMArena French13351166
LMArena German13551141
LMArena Russian13311158
LMArena Spanish13261151
LMArena Japanese—1037
LMArena Korean—1057

Instruction Following MiniMax-M2 leads

MiniMax-M2: 70.2 (#166), Mixtral 8x22B: 57.7 (#266)

Instruction Following benchmarks
BenchmarkMiniMax-M2Mixtral 8x22B
LMArena Instruction Following13281147
IFEval—72.4%

Long Context MiniMax-M2 leads

MiniMax-M2: 40.5 (#153), Mixtral 8x22B: 34.7 (#247)

Long Context benchmarks
BenchmarkMiniMax-M2Mixtral 8x22B
LMArena Longer Query13311144

Writing & Preference MiniMax-M2 leads

MiniMax-M2: 53.0 (#162), Mixtral 8x22B: 36.9 (#262)

Writing & Preference benchmarks
BenchmarkMiniMax-M2Mixtral 8x22B
LMArena Text13401162
LMArena Creative Writing12861141
LMArena Multi-Turn13611130
WildBench—71.1%

Frequently asked questions

Is MiniMax-M2 better than Mixtral 8x22B?

MiniMax-M2 is the stronger model overall, scoring 37.4 to 27.1 on the Noometry Index.

Which is cheaper, MiniMax-M2 or Mixtral 8x22B?

MiniMax-M2 is cheaper. It lists at $0.30 per million input tokens and $1.20 per million output tokens; Mixtral 8x22B lists at $2 and $6.

Is MiniMax-M2 or Mixtral 8x22B better for coding?

MiniMax-M2 scores higher on coding benchmarks: 39.3 versus 24.2 in the Noometry coding category.

Which has the bigger context window?

MiniMax-M2 does, with 205K tokens against 64K.

How many benchmarks do MiniMax-M2 and Mixtral 8x22B share?

15 benchmarks have published results for both models. MiniMax-M2 has 21 scored results on Noometry and Mixtral 8x22B has 34.

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