Noometry

Model comparison

Mixtral 8x22B vs Qwen3.5-9B

Qwen3.5-9B is the stronger model overall, scoring 33.8 to 27.1 on the Noometry Index.

Last verified . 3 shared benchmarks.

Mixtral 8x22B Mistral AI

27.1

Rank #333 Confirmed

Qwen3.5-9B Alibaba (Qwen)

33.8

Rank #236 Confirmed

Summary

  • They share 3 benchmarks with published results for both. Mixtral 8x22B scores higher in 1 category and Qwen3.5-9B in 4 categories; 5 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where Qwen3.5-9B leads 46.0 to 15.1.
  • The biggest single-benchmark swing is GPQA Diamond: 34.1% for Mixtral 8x22B and 79% for Qwen3.5-9B.
  • Qwen3.5-9B is cheaper at $0.10 / $0.15 per million input/output tokens, against $2 / $6 for Mixtral 8x22B.
  • Qwen3.5-9B accepts more context: 262K tokens versus 64K.

Side by side

Mixtral 8x22BQwen3.5-9B
ProviderMistral AIAlibaba (Qwen)
Noometry Index27.133.8
Released2024-04-172026-02-23
WeightsOpenOpen
Context window64K262K
Max output64K66K
Input $ / M tokens$2$0.10
Output $ / M tokens$6$0.15
Results tracked3410

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Category by category

Coding Qwen3.5-9B leads

Mixtral 8x22B: 24.2 (#329), Qwen3.5-9B: 35.9 (#217)

BenchmarkMixtral 8x22BQwen3.5-9B
SciCode—27.5%
WeirdML3.2%—
BigCodeBench Instruct40.6%—
LMArena Coding1166—
BigCodeBench Complete50.2%—
HumanEval+72%—
MBPP+64.3%—

Agentic & Tool Use Mixtral 8x22B leads

Mixtral 8x22B: 23.1 (#127), Qwen3.5-9B: 14.5 (#151)

BenchmarkMixtral 8x22BQwen3.5-9B
Terminal-Bench—9.2%
Cybench7.5%—

Reasoning Qwen3.5-9B leads

Mixtral 8x22B: 19.9 (#248), Qwen3.5-9B: 23.1 (#182)

BenchmarkMixtral 8x22BQwen3.5-9B
DTBench55.1%71.2%
Epoch Capabilities Index122.03139.46
CritPt—0.3%
Chess Puzzles—12%
LMArena Hard Prompts1150—
LMCA—24.5%
ForecastBench56.3—

Math Qwen3.5-9B leads

Mixtral 8x22B: 22.9 (#275), Qwen3.5-9B: 34.8 (#192)

BenchmarkMixtral 8x22BQwen3.5-9B
MathArena Final-Answer Competitions—48.5%
OTIS Mock AIME 2024-2025—61.7%
Omni-MATH16.3%—
LMArena Math1184—
MATH Level 524.2%—

Knowledge Qwen3.5-9B leads

Mixtral 8x22B: 15.1 (#293), Qwen3.5-9B: 46.0 (#84)

BenchmarkMixtral 8x22BQwen3.5-9B
GPQA Diamond34.1%79%
MMLU-Pro46%—
GPQA (HELM)33.4%—
LMArena Expert1113—
MMLU77.8%—

Multilingual Not comparable

Mixtral 8x22B: 32.8 (#255), Qwen3.5-9B: —

BenchmarkMixtral 8x22BQwen3.5-9B
LMArena Non-English1128—
LMArena Chinese1116—
LMArena French1166—
LMArena German1141—
LMArena Japanese1037—
LMArena Korean1057—
LMArena Russian1158—
LMArena Spanish1151—

Instruction Following Not comparable

Mixtral 8x22B: 57.7 (#266), Qwen3.5-9B: —

BenchmarkMixtral 8x22BQwen3.5-9B
IFEval72.4%—
LMArena Instruction Following1147—

Long Context Not comparable

Mixtral 8x22B: 34.7 (#247), Qwen3.5-9B: —

BenchmarkMixtral 8x22BQwen3.5-9B
LMArena Longer Query1144—

Writing & Preference Not comparable

Mixtral 8x22B: 36.9 (#262), Qwen3.5-9B: —

BenchmarkMixtral 8x22BQwen3.5-9B
LMArena Text1162—
LMArena Creative Writing1141—
WildBench71.1%—
LMArena Multi-Turn1130—

Frequently asked questions

Is Mixtral 8x22B better than Qwen3.5-9B?

Qwen3.5-9B is the stronger model overall, scoring 33.8 to 27.1 on the Noometry Index.

Which is cheaper, Mixtral 8x22B or Qwen3.5-9B?

Qwen3.5-9B is cheaper. It lists at $0.10 per million input tokens and $0.15 per million output tokens; Mixtral 8x22B lists at $2 and $6.

Is Mixtral 8x22B or Qwen3.5-9B better for coding?

Qwen3.5-9B scores higher on coding benchmarks: 35.9 versus 24.2 in the Noometry coding category.

Which has the bigger context window?

Qwen3.5-9B does, with 262K tokens against 64K.

How many benchmarks do Mixtral 8x22B and Qwen3.5-9B share?

3 benchmarks have published results for both models. Mixtral 8x22B has 34 scored results on Noometry and Qwen3.5-9B has 10.

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