Model comparison

Mixtral 8x7B vs Qwen1.5-72B

Qwen1.5-72B is the stronger model overall, scoring 30.8 to 27.1 on the Noometry Index.

Last verified . 20 shared benchmarks.

Mixtral 8x7B Mistral AI

27.1

Rank #334 Confirmed

Qwen1.5-72B Alibaba (Qwen)

30.8

Rank #285 Confirmed

Summary

  • They share 20 benchmarks with published results for both. Mixtral 8x7B scores higher in 1 category and Qwen1.5-72B in 7 categories; 6 gaps are clear of the uncertainty.
  • The widest gap is in math, where Qwen1.5-72B leads 33.2 to 18.8.

Side by side

Mixtral 8x7B and Qwen1.5-72B specifications
Mixtral 8x7BQwen1.5-72B
ProviderMistral AIAlibaba (Qwen)
Noometry Index27.130.8
Released2023-12-112024-02-04
WeightsOpenOpen
Context window32K—
Max output32K—
Input $ / M tokens$0.70—
Output $ / M tokens$0.70—
Results tracked3822

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Category by category

Coding Too close to call

Mixtral 8x7B: 32.8 (#269), Qwen1.5-72B: 31.9 (#277)

Coding benchmarks
BenchmarkMixtral 8x7BQwen1.5-72B
LMArena Coding11261165
HumanEval+39.6%59.1%
MBPP+49.7%61.6%
BigCodeBench Instruct—33.2%
BigCodeBench Complete—40.3%

Reasoning Qwen1.5-72B leads

Mixtral 8x7B: 18.2 (#285), Qwen1.5-72B: 22.2 (#203)

Reasoning benchmarks
BenchmarkMixtral 8x7BQwen1.5-72B
LMArena Hard Prompts11151148
DTBench49.6%—
Adversarial NLI55.2%—
Epoch Capabilities Index118.47—
ForecastBench56.3—
HellaSwag86.7%—
PIQA83.6%—
WinoGrande77.2%—

Math Qwen1.5-72B leads

Mixtral 8x7B: 18.8 (#289), Qwen1.5-72B: 33.2 (#205)

Math benchmarks
BenchmarkMixtral 8x7BQwen1.5-72B
LMArena Math11471164
Omni-MATH10.5%—
MATH Level 510%—
GSM8K74.4%—

Knowledge Too close to call

Mixtral 8x7B: 11.0 (#301), Qwen1.5-72B: 11.5 (#300)

Knowledge benchmarks
BenchmarkMixtral 8x7BQwen1.5-72B
GPQA Diamond30.6%28.8%
LMArena Expert10881136
MMLU-Pro33.5%—
GPQA (HELM)29.6%—
ARC (AI2) Challenge87.3%—
MMLU70.6%—
OpenBookQA85.8%—
TriviaQA82.2%—

Multilingual Qwen1.5-72B leads

Mixtral 8x7B: 29.6 (#266), Qwen1.5-72B: 33.2 (#253)

Multilingual benchmarks
BenchmarkMixtral 8x7BQwen1.5-72B
LMArena Non-English10771135
LMArena Chinese10551186
LMArena French11661159
LMArena German11141084
LMArena Japanese9311061
LMArena Korean9681050
LMArena Russian10901104
LMArena Spanish11111110

Instruction Following Qwen1.5-72B leads

Mixtral 8x7B: 51.0 (#297), Qwen1.5-72B: 59.3 (#256)

Instruction Following benchmarks
BenchmarkMixtral 8x7BQwen1.5-72B
LMArena Instruction Following11091141
IFEval57.5%—

Long Context Qwen1.5-72B leads

Mixtral 8x7B: 33.4 (#260), Qwen1.5-72B: 35.1 (#243)

Long Context benchmarks
BenchmarkMixtral 8x7BQwen1.5-72B
LMArena Longer Query11031157

Writing & Preference Qwen1.5-72B leads

Mixtral 8x7B: 34.2 (#270), Qwen1.5-72B: 37.3 (#258)

Writing & Preference benchmarks
BenchmarkMixtral 8x7BQwen1.5-72B
LMArena Text11321166
LMArena Creative Writing11091137
LMArena Multi-Turn11151160
WildBench67.3%—

Frequently asked questions

Is Mixtral 8x7B better than Qwen1.5-72B?

Qwen1.5-72B is the stronger model overall, scoring 30.8 to 27.1 on the Noometry Index.

Is Mixtral 8x7B or Qwen1.5-72B better for coding?

They score almost the same on coding (32.8 vs 31.9); test both on your own repository before choosing.

How many benchmarks do Mixtral 8x7B and Qwen1.5-72B share?

20 benchmarks have published results for both models. Mixtral 8x7B has 38 scored results on Noometry and Qwen1.5-72B has 22.

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