Noometry

Model comparison

GPT-6 Sol vs Qwen1.5-32B

GPT-6 Sol is the stronger model overall, scoring 61.8 to 30.5 on the Noometry Index.

Last verified . 18 shared benchmarks.

GPT-6 Sol OpenAI

61.8

Rank #12 Confirmed

Qwen1.5-32B Alibaba (Qwen)

30.5

Rank #293 Confirmed

Summary

  • They share 18 benchmarks with published results for both. GPT-6 Sol scores higher in 8 categories and Qwen1.5-32B in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in math, where GPT-6 Sol leads 87.2 to 33.0.
  • The biggest single-benchmark swing is GPQA Diamond: 94.3% for GPT-6 Sol and 30.7% for Qwen1.5-32B.
  • Qwen1.5-32B has downloadable open weights; the other is API-only.

Side by side

GPT-6 SolQwen1.5-32B
ProviderOpenAIAlibaba (Qwen)
Noometry Index61.830.5
Released2026-09-222024-02-04
WeightsProprietaryOpen
Context window1.05M—
Max output128K—
Input $ / M tokens$2—
Output $ / M tokens$10—
Results tracked4521

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Category by category

Coding GPT-6 Sol leads

GPT-6 Sol: 60.1 (#11), Qwen1.5-32B: 31.7 (#282)

BenchmarkGPT-6 SolQwen1.5-32B
LMArena Coding14471155
DeepSWE68.8%—
FrontierCode49.3%—
LMArena WebDev1688—
SciCode57.6%—
BigCodeBench Instruct—32.3%
BigCodeBench Complete—42%
ALE-Bench2,462—

Agentic & Tool Use Not comparable

GPT-6 Sol: 37.2 (#36), Qwen1.5-32B: —

BenchmarkGPT-6 SolQwen1.5-32B
APEX-Agents54.3%—
GDP.pdf26.4%—
Vending-Bench 214,428—

Reasoning GPT-6 Sol leads

GPT-6 Sol: 74.0 (#9), Qwen1.5-32B: 21.8 (#212)

BenchmarkGPT-6 SolQwen1.5-32B
LMArena Hard Prompts14181130
ARC-AGI-289.6%—
NYT Connections (extended)90.1%—
ARC-AGI-195.5%—
CritPt30.9%—
EBR-Bench53.3%—
Mystery Game Puzzles56%—
DTBench97.3%—
LMCA59.1%—
Epoch Capabilities Index162.72—

Math GPT-6 Sol leads

GPT-6 Sol: 87.2 (#7), Qwen1.5-32B: 33.0 (#207)

BenchmarkGPT-6 SolQwen1.5-32B
LMArena Math14021155
FrontierMath (Tiers 1-3)89.8%—
FrontierMath Tier 490%—
OTIS Mock AIME 2024-2025100%—
ProofBench83%—

Knowledge GPT-6 Sol leads

GPT-6 Sol: 64.8 (#15), Qwen1.5-32B: 13.5 (#296)

BenchmarkGPT-6 SolQwen1.5-32B
GPQA Diamond94.3%30.7%
LMArena Expert14391126
SimpleQA Verified60.7%—
Vectara Hallucination Rate6.5%—
MMLU—74.4%

Multimodal Not comparable

GPT-6 Sol: 47.6 (#10), Qwen1.5-32B: —

BenchmarkGPT-6 SolQwen1.5-32B
LMArena Vision1245—
Blueprint-Bench 236.9%—
Furniture Assembly58.3%—

Multilingual GPT-6 Sol leads

GPT-6 Sol: 50.5 (#118), Qwen1.5-32B: 31.4 (#259)

BenchmarkGPT-6 SolQwen1.5-32B
LMArena Non-English13851106
LMArena Chinese14051177
LMArena French14101101
LMArena German13901058
LMArena Japanese13851027
LMArena Korean13411008
LMArena Russian14011073
LMArena Spanish13841089

Instruction Following GPT-6 Sol leads

GPT-6 Sol: 74.5 (#94), Qwen1.5-32B: 57.7 (#265)

BenchmarkGPT-6 SolQwen1.5-32B
LMArena Instruction Following14121116

Long Context GPT-6 Sol leads

GPT-6 Sol: 43.1 (#108), Qwen1.5-32B: 34.7 (#246)

BenchmarkGPT-6 SolQwen1.5-32B
LMArena Longer Query14111146

Writing & Preference GPT-6 Sol leads

GPT-6 Sol: 71.9 (#18), Qwen1.5-32B: 34.2 (#271)

BenchmarkGPT-6 SolQwen1.5-32B
LMArena Text13951137
LMArena Creative Writing13781083
LMArena Multi-Turn14121140
EQ-Bench Creative Writing2125—

Frequently asked questions

Is GPT-6 Sol better than Qwen1.5-32B?

GPT-6 Sol is the stronger model overall, scoring 61.8 to 30.5 on the Noometry Index.

Is GPT-6 Sol or Qwen1.5-32B better for coding?

GPT-6 Sol scores higher on coding benchmarks: 60.1 versus 31.7 in the Noometry coding category.

How many benchmarks do GPT-6 Sol and Qwen1.5-32B share?

18 benchmarks have published results for both models. GPT-6 Sol has 45 scored results on Noometry and Qwen1.5-32B has 21.

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