Noometry

Model comparison

Qwen3 235B-A22B vs Yi-34B

Qwen3 235B-A22B is the stronger model overall, scoring 43.5 to 27.8 on the Noometry Index.

Last verified . 20 shared benchmarks.

Qwen3 235B-A22B Alibaba (Qwen)

43.5

Rank #91 Confirmed

Yi-34B 01.AI

27.8

Rank #329 Confirmed

Summary

  • They share 20 benchmarks with published results for both. Qwen3 235B-A22B scores higher in 7 categories and Yi-34B in 1 category; 8 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where Qwen3 235B-A22B leads 49.6 to 7.5.
  • The biggest single-benchmark swing is GPQA Diamond: 80.1% for Qwen3 235B-A22B and 14.7% for Yi-34B.

Side by side

Qwen3 235B-A22BYi-34B
ProviderAlibaba (Qwen)01.AI
Noometry Index43.527.8
Released2025-042023-11-02
WeightsOpenOpen
Context window131K—
Max output16K—
Input $ / M tokens$0.70—
Output $ / M tokens$2.80—
Results tracked4923

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Category by category

Coding Qwen3 235B-A22B leads

Qwen3 235B-A22B: 44.3 (#75), Yi-34B: 32.3 (#274)

BenchmarkQwen3 235B-A22BYi-34B
LMArena Coding14451112
Aider Polyglot59.6%—
SciCode42.4%—
WeirdML41%—

Agentic & Tool Use Not comparable

Qwen3 235B-A22B: 33.9 (#51), Yi-34B: —

BenchmarkQwen3 235B-A22BYi-34B
Berkeley Function Calling Leaderboard52.1%—
Vending-Bench 2-11.34—

Reasoning Yi-34B leads

Qwen3 235B-A22B: 15.7 (#311), Yi-34B: 21.2 (#226)

BenchmarkQwen3 235B-A22BYi-34B
LMArena Hard Prompts14331104
Epoch Capabilities Index143.85117.39
ARC-AGI-21.3%—
SimpleBench31%—
Kagi LLM Benchmark69.4%—
ARC-AGI-111%—
CritPt0%—
Chess Puzzles12%—
Mystery Game Puzzles9%—
DTBench80.3%—
LMCA29.3%—
BIG-Bench Hard—71.7%
ForecastBench59.7—

Math Qwen3 235B-A22B leads

Qwen3 235B-A22B: 50.4 (#57), Yi-34B: 21.6 (#282)

BenchmarkQwen3 235B-A22BYi-34B
LMArena Math14321114
MATH Level 568.9%5.1%
OTIS Mock AIME 2024-202586.7%—
Omni-MATH71.8%—
FrontierMath (Feb 2025 set)8.5%—
FrontierMath Tier 4 (v1)0%—
GSM8K—76%

Knowledge Qwen3 235B-A22B leads

Qwen3 235B-A22B: 49.6 (#73), Yi-34B: 7.5 (#309)

BenchmarkQwen3 235B-A22BYi-34B
GPQA Diamond80.1%14.7%
LMArena Expert14631061
SimpleQA Verified40.4%—
MMLU-Pro84.4%—
Confabulations15.6%—
Vectara Hallucination Rate9.3%—
GPQA (HELM)72.7%—
MMLU—76.3%

Multilingual Qwen3 235B-A22B leads

Qwen3 235B-A22B: 52.3 (#89), Yi-34B: 29.7 (#264)

BenchmarkQwen3 235B-A22BYi-34B
LMArena Non-English14091079
LMArena Chinese14811176
LMArena French14451081
LMArena German14331042
LMArena Japanese1399993
LMArena Korean1391959
LMArena Russian14111050
LMArena Spanish14301070

Instruction Following Qwen3 235B-A22B leads

Qwen3 235B-A22B: 72.6 (#136), Yi-34B: 56.2 (#274)

BenchmarkQwen3 235B-A22BYi-34B
LMArena Instruction Following14081091
IFEval83.5%—

Long Context Qwen3 235B-A22B leads

Qwen3 235B-A22B: 46.1 (#26), Yi-34B: 33.2 (#264)

BenchmarkQwen3 235B-A22BYi-34B
LMArena Longer Query14261094
Fiction.LiveBench75%—

Writing & Preference Qwen3 235B-A22B leads

Qwen3 235B-A22B: 59.6 (#108), Yi-34B: 34.1 (#273)

BenchmarkQwen3 235B-A22BYi-34B
LMArena Text14191129
LMArena Creative Writing13841108
LMArena Multi-Turn14321113
Short-Story Creative Writing83%—
EQ-Bench Creative Writing1366—
WildBench86.6%—

Frequently asked questions

Is Qwen3 235B-A22B better than Yi-34B?

Qwen3 235B-A22B is the stronger model overall, scoring 43.5 to 27.8 on the Noometry Index.

Is Qwen3 235B-A22B or Yi-34B better for coding?

Qwen3 235B-A22B scores higher on coding benchmarks: 44.3 versus 32.3 in the Noometry coding category.

How many benchmarks do Qwen3 235B-A22B and Yi-34B share?

20 benchmarks have published results for both models. Qwen3 235B-A22B has 49 scored results on Noometry and Yi-34B has 23.

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