Model comparison

Mixtral 8x22B vs Qwen1.5-110B

Qwen1.5-110B is the stronger model overall, scoring 34.2 to 27.1 on the Noometry Index.

Last verified . 20 shared benchmarks.

Mixtral 8x22B Mistral AI

27.1

Rank #333 Confirmed

Qwen1.5-110B Alibaba (Qwen)

34.2

Rank #234 Confirmed

Summary

  • They share 20 benchmarks with published results for both. Mixtral 8x22B scores higher in 0 categories and Qwen1.5-110B in 8 categories; 6 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where Qwen1.5-110B leads 31.2 to 15.1.
  • The biggest single-benchmark swing is BigCodeBench Complete: 50.2% for Mixtral 8x22B and 44.4% for Qwen1.5-110B.

Side by side

Mixtral 8x22B and Qwen1.5-110B specifications
Mixtral 8x22BQwen1.5-110B
ProviderMistral AIAlibaba (Qwen)
Noometry Index27.134.2
Released2024-04-172024-04-25
WeightsOpenOpen
Context window64K—
Max output64K—
Input $ / M tokens$2—
Output $ / M tokens$6—
Results tracked3420

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Category by category

Coding Qwen1.5-110B leads

Mixtral 8x22B: 24.2 (#329), Qwen1.5-110B: 33.0 (#264)

Coding benchmarks
BenchmarkMixtral 8x22BQwen1.5-110B
BigCodeBench Instruct40.6%35%
LMArena Coding11661184
BigCodeBench Complete50.2%44.4%
WeirdML3.2%—
HumanEval+72%—
MBPP+64.3%—

Agentic & Tool Use Not comparable

Mixtral 8x22B: 23.1 (#127), Qwen1.5-110B: —

Agentic & Tool Use benchmarks
BenchmarkMixtral 8x22BQwen1.5-110B
Cybench7.5%—

Reasoning Qwen1.5-110B leads

Mixtral 8x22B: 19.9 (#248), Qwen1.5-110B: 22.7 (#189)

Reasoning benchmarks
BenchmarkMixtral 8x22BQwen1.5-110B
LMArena Hard Prompts11501168
ForecastBench56.357.7
DTBench55.1%—
Epoch Capabilities Index122.03—

Math Qwen1.5-110B leads

Mixtral 8x22B: 22.9 (#275), Qwen1.5-110B: 33.7 (#201)

Math benchmarks
BenchmarkMixtral 8x22BQwen1.5-110B
LMArena Math11841185
Omni-MATH16.3%—
MATH Level 524.2%—

Knowledge Qwen1.5-110B leads

Mixtral 8x22B: 15.1 (#293), Qwen1.5-110B: 31.2 (#219)

Knowledge benchmarks
BenchmarkMixtral 8x22BQwen1.5-110B
LMArena Expert11131144
GPQA Diamond34.1%—
MMLU-Pro46%—
GPQA (HELM)33.4%—
MMLU77.8%—

Multilingual Too close to call

Mixtral 8x22B: 32.8 (#255), Qwen1.5-110B: 33.6 (#250)

Multilingual benchmarks
BenchmarkMixtral 8x22BQwen1.5-110B
LMArena Non-English11281142
LMArena Chinese11161206
LMArena French11661151
LMArena German11411123
LMArena Japanese10371074
LMArena Korean10571044
LMArena Russian11581118
LMArena Spanish11511142

Instruction Following Qwen1.5-110B leads

Mixtral 8x22B: 57.7 (#266), Qwen1.5-110B: 60.3 (#252)

Instruction Following benchmarks
BenchmarkMixtral 8x22BQwen1.5-110B
LMArena Instruction Following11471158
IFEval72.4%—

Long Context Too close to call

Mixtral 8x22B: 34.7 (#247), Qwen1.5-110B: 35.1 (#242)

Long Context benchmarks
BenchmarkMixtral 8x22BQwen1.5-110B
LMArena Longer Query11441157

Writing & Preference Qwen1.5-110B leads

Mixtral 8x22B: 36.9 (#262), Qwen1.5-110B: 38.0 (#255)

Writing & Preference benchmarks
BenchmarkMixtral 8x22BQwen1.5-110B
LMArena Text11621175
LMArena Creative Writing11411148
LMArena Multi-Turn11301160
WildBench71.1%—

Frequently asked questions

Is Mixtral 8x22B better than Qwen1.5-110B?

Qwen1.5-110B is the stronger model overall, scoring 34.2 to 27.1 on the Noometry Index.

Is Mixtral 8x22B or Qwen1.5-110B better for coding?

Qwen1.5-110B scores higher on coding benchmarks: 33.0 versus 24.2 in the Noometry coding category.

How many benchmarks do Mixtral 8x22B and Qwen1.5-110B share?

20 benchmarks have published results for both models. Mixtral 8x22B has 34 scored results on Noometry and Qwen1.5-110B has 20.

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