Noometry

Model comparison

Mixtral 8x7B vs Qwen3.8 27B

Qwen3.8 27B is the stronger model overall, scoring 46.0 to 27.1 on the Noometry Index.

Last verified . 19 shared benchmarks.

Mixtral 8x7B Mistral AI

27.1

Rank #334 Confirmed

Qwen3.8 27B Alibaba (Qwen)

46.0

Rank #68 Confirmed

Summary

  • They share 19 benchmarks with published results for both. Mixtral 8x7B scores higher in 0 categories and Qwen3.8 27B in 8 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where Qwen3.8 27B leads 65.8 to 34.2.
  • The biggest single-benchmark swing is DTBench: 49.6% for Mixtral 8x7B and 88% for Qwen3.8 27B.
  • Qwen3.8 27B is cheaper at $0.04 / $2.30 per million input/output tokens, against $0.70 / $0.70 for Mixtral 8x7B.
  • Qwen3.8 27B accepts more context: 262K tokens versus 32K.

Side by side

Mixtral 8x7BQwen3.8 27B
ProviderMistral AIAlibaba (Qwen)
Noometry Index27.146.0
Released2023-12-112026-08-14
WeightsOpenOpen
Context window32K262K
Max output32K33K
Input $ / M tokens$0.70$0.04
Output $ / M tokens$0.70$2.30
Results tracked3831

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Category by category

Coding Qwen3.8 27B leads

Mixtral 8x7B: 32.8 (#269), Qwen3.8 27B: 50.5 (#44)

BenchmarkMixtral 8x7BQwen3.8 27B
LMArena Coding11261482
LMArena WebDev—1593
SciCode—46.6%
HumanEval+39.6%—
MBPP+49.7%—

Agentic & Tool Use Not comparable

Mixtral 8x7B: —, Qwen3.8 27B: 32.9 (#57)

BenchmarkMixtral 8x7BQwen3.8 27B
APEX-Agents—47.5%

Reasoning Qwen3.8 27B leads

Mixtral 8x7B: 18.2 (#285), Qwen3.8 27B: 41.0 (#54)

BenchmarkMixtral 8x7BQwen3.8 27B
LMArena Hard Prompts11151460
DTBench49.6%88%
Epoch Capabilities Index118.47149.38
ARC-AGI-2—42.4%
NYT Connections (extended)—54.5%
ARC-AGI-1—87.5%
CritPt—5.4%
LMCA—41.4%
Surface Evolver Bench—45%
Adversarial NLI55.2%—
ForecastBench56.3—
HellaSwag86.7%—
PIQA83.6%—
WinoGrande77.2%—

Math Qwen3.8 27B leads

Mixtral 8x7B: 18.8 (#289), Qwen3.8 27B: 37.1 (#161)

BenchmarkMixtral 8x7BQwen3.8 27B
LMArena Math11471456
ProofBench—16%
Omni-MATH10.5%—
MATH Level 510%—
GSM8K74.4%—

Knowledge Qwen3.8 27B leads

Mixtral 8x7B: 11.0 (#301), Qwen3.8 27B: 41.6 (#109)

BenchmarkMixtral 8x7BQwen3.8 27B
LMArena Expert10881482
GPQA Diamond30.6%—
MMLU-Pro33.5%—
GPQA (HELM)29.6%—
ARC (AI2) Challenge87.3%—
MMLU70.6%—
OpenBookQA85.8%—
TriviaQA82.2%—

Multimodal Not comparable

Mixtral 8x7B: —, Qwen3.8 27B: 41.3 (#37)

BenchmarkMixtral 8x7BQwen3.8 27B
LMArena Vision—1271

Multilingual Qwen3.8 27B leads

Mixtral 8x7B: 29.6 (#266), Qwen3.8 27B: 53.7 (#60)

BenchmarkMixtral 8x7BQwen3.8 27B
LMArena Non-English10771430
LMArena Chinese10551504
LMArena French11661465
LMArena German11141438
LMArena Japanese9311384
LMArena Korean9681393
LMArena Russian10901415
LMArena Spanish11111448

Instruction Following Qwen3.8 27B leads

Mixtral 8x7B: 51.0 (#297), Qwen3.8 27B: 75.8 (#53)

BenchmarkMixtral 8x7BQwen3.8 27B
LMArena Instruction Following11091439
IFEval57.5%—

Long Context Qwen3.8 27B leads

Mixtral 8x7B: 33.4 (#260), Qwen3.8 27B: 44.3 (#70)

BenchmarkMixtral 8x7BQwen3.8 27B
LMArena Longer Query11031450

Writing & Preference Qwen3.8 27B leads

Mixtral 8x7B: 34.2 (#270), Qwen3.8 27B: 65.8 (#43)

BenchmarkMixtral 8x7BQwen3.8 27B
LMArena Text11321441
LMArena Creative Writing11091384
LMArena Multi-Turn11151441
EQ-Bench Creative Writing—1671
WildBench67.3%—

Frequently asked questions

Is Mixtral 8x7B better than Qwen3.8 27B?

Qwen3.8 27B is the stronger model overall, scoring 46.0 to 27.1 on the Noometry Index.

Which is cheaper, Mixtral 8x7B or Qwen3.8 27B?

Qwen3.8 27B is cheaper. It lists at $0.04 per million input tokens and $2.30 per million output tokens; Mixtral 8x7B lists at $0.70 and $0.70.

Is Mixtral 8x7B or Qwen3.8 27B better for coding?

Qwen3.8 27B scores higher on coding benchmarks: 50.5 versus 32.8 in the Noometry coding category.

Which has the bigger context window?

Qwen3.8 27B does, with 262K tokens against 32K.

How many benchmarks do Mixtral 8x7B and Qwen3.8 27B share?

19 benchmarks have published results for both models. Mixtral 8x7B has 38 scored results on Noometry and Qwen3.8 27B has 31.

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