Noometry

Model comparison

Mixtral 8x22B vs Qwen3 14B

Qwen3 14B is the stronger model overall, scoring 35.5 to 27.1 on the Noometry Index.

Last verified . 3 shared benchmarks.

Mixtral 8x22B Mistral AI

27.1

Rank #333 Confirmed

Qwen3 14B Alibaba (Qwen)

35.5

Rank #225 Confirmed

Summary

  • They share 3 benchmarks with published results for both. Mixtral 8x22B scores higher in 1 category and Qwen3 14B in 5 categories; 6 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where Qwen3 14B leads 39.3 to 15.1.
  • The biggest single-benchmark swing is GPQA Diamond: 34.1% for Mixtral 8x22B and 63.8% for Qwen3 14B.
  • Qwen3 14B is cheaper at $0.35 / $1.40 per million input/output tokens, against $2 / $6 for Mixtral 8x22B.
  • Qwen3 14B accepts more context: 131K tokens versus 64K.

Side by side

Mixtral 8x22BQwen3 14B
ProviderMistral AIAlibaba (Qwen)
Noometry Index27.135.5
Released2024-04-172025-04
WeightsOpenOpen
Context window64K131K
Max output64K8K
Input $ / M tokens$2$0.35
Output $ / M tokens$6$1.40
Results tracked3412

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Category by category

Coding Qwen3 14B leads

Mixtral 8x22B: 24.2 (#329), Qwen3 14B: 37.3 (#195)

BenchmarkMixtral 8x22BQwen3 14B
SciCode—31.6%
WeirdML3.2%—
BigCodeBench Instruct40.6%—
LMArena Coding1166—
BigCodeBench Complete50.2%—
HumanEval+72%—
MBPP+64.3%—

Agentic & Tool Use Qwen3 14B leads

Mixtral 8x22B: 23.1 (#127), Qwen3 14B: 29.6 (#83)

BenchmarkMixtral 8x22BQwen3 14B
Berkeley Function Calling Leaderboard—41%
Cybench7.5%—

Reasoning Mixtral 8x22B leads

Mixtral 8x22B: 19.9 (#248), Qwen3 14B: 18.5 (#280)

BenchmarkMixtral 8x22BQwen3 14B
DTBench55.1%64%
Epoch Capabilities Index122.03138.23
Kagi LLM Benchmark—49.1%
CritPt—0%
Chess Puzzles—4%
LMArena Hard Prompts1150—
LMCA—18.2%
ForecastBench56.3—

Math Qwen3 14B leads

Mixtral 8x22B: 22.9 (#275), Qwen3 14B: 38.6 (#133)

BenchmarkMixtral 8x22BQwen3 14B
OTIS Mock AIME 2024-2025—66.4%
Omni-MATH16.3%—
LMArena Math1184—
MATH Level 524.2%—

Knowledge Qwen3 14B leads

Mixtral 8x22B: 15.1 (#293), Qwen3 14B: 39.3 (#134)

BenchmarkMixtral 8x22BQwen3 14B
GPQA Diamond34.1%63.8%
MMLU-Pro46%—
Vectara Hallucination Rate—5.4%
GPQA (HELM)33.4%—
LMArena Expert1113—
MMLU77.8%—

Multilingual Not comparable

Mixtral 8x22B: 32.8 (#255), Qwen3 14B: —

BenchmarkMixtral 8x22BQwen3 14B
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 14B: —

BenchmarkMixtral 8x22BQwen3 14B
IFEval72.4%—
LMArena Instruction Following1147—

Long Context Qwen3 14B leads

Mixtral 8x22B: 34.7 (#247), Qwen3 14B: 38.1 (#204)

BenchmarkMixtral 8x22BQwen3 14B
Fiction.LiveBench—62.5%
LMArena Longer Query1144—

Writing & Preference Not comparable

Mixtral 8x22B: 36.9 (#262), Qwen3 14B: —

BenchmarkMixtral 8x22BQwen3 14B
LMArena Text1162—
LMArena Creative Writing1141—
WildBench71.1%—
LMArena Multi-Turn1130—

Frequently asked questions

Is Mixtral 8x22B better than Qwen3 14B?

Qwen3 14B is the stronger model overall, scoring 35.5 to 27.1 on the Noometry Index.

Which is cheaper, Mixtral 8x22B or Qwen3 14B?

Qwen3 14B is cheaper. It lists at $0.35 per million input tokens and $1.40 per million output tokens; Mixtral 8x22B lists at $2 and $6.

Is Mixtral 8x22B or Qwen3 14B better for coding?

Qwen3 14B scores higher on coding benchmarks: 37.3 versus 24.2 in the Noometry coding category.

Which has the bigger context window?

Qwen3 14B does, with 131K tokens against 64K.

How many benchmarks do Mixtral 8x22B and Qwen3 14B share?

3 benchmarks have published results for both models. Mixtral 8x22B has 34 scored results on Noometry and Qwen3 14B has 12.

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