Noometry

Model comparison

GPT-6 Sol vs Qwen3 32B

GPT-6 Sol is the stronger model overall, scoring 49.2 to 38.8 on the Noometry Index. Qwen3 32B costs 3.3× less per token, which makes it the better buy when GPT-6 Sol's lead doesn't matter for your workload.

Last verified . 13 shared benchmarks.

GPT-6 Sol OpenAI

49.2

Rank #46 Confirmed

Qwen3 32B Alibaba (Qwen)

38.8

Rank #166 Confirmed

Summary

  • They share 13 benchmarks with published results for both. GPT-6 Sol scores higher in 7 categories and Qwen3 32B in 2 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where GPT-6 Sol leads 49.3 to 19.6.
  • Qwen3 32B is cheaper at $0.70 / $2.80 per million input/output tokens, against $2 / $10 for GPT-6 Sol.
  • GPT-6 Sol accepts more context: 1.05M tokens versus 131K.
  • Qwen3 32B has downloadable open weights; the other is API-only.

Side by side

GPT-6 SolQwen3 32B
ProviderOpenAIAlibaba (Qwen)
Noometry Index49.238.8
Released2026-09-222025-04
WeightsProprietaryOpen
Context window1.05M131K
Max output128K16K
Input $ / M tokens$2$0.70
Output $ / M tokens$10$2.80
Results tracked2226

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Category by category

Coding GPT-6 Sol leads

GPT-6 Sol: 59.6 (#11), Qwen3 32B: 37.3 (#184)

BenchmarkGPT-6 SolQwen3 32B
LMArena Coding14531358
DeepSWE68.8%—
FrontierCode49.3%—
Aider Polyglot—40%
LMArena WebDev1692—
SciCode—35.4%

Agentic & Tool Use GPT-6 Sol leads

GPT-6 Sol: 33.5 (#49), Qwen3 32B: 32.3 (#58)

BenchmarkGPT-6 SolQwen3 32B
Berkeley Function Calling Leaderboard—48.7%
GDP.pdf28%—

Reasoning GPT-6 Sol leads

GPT-6 Sol: 49.3 (#34), Qwen3 32B: 19.6 (#233)

BenchmarkGPT-6 SolQwen3 32B
LMArena Hard Prompts14201335
Kagi LLM Benchmark—54.9%
NYT Connections (extended)90.1%—
CritPt—0.3%
Chess Puzzles—5%
EBR-Bench53.3%—
DTBench—67.5%
LMCA—17.3%
Epoch Capabilities Index—138.51

Math Qwen3 32B leads

GPT-6 Sol: 35.8 (#135), Qwen3 32B: 37.9 (#89)

BenchmarkGPT-6 SolQwen3 32B
LMArena Math14041399
OTIS Mock AIME 2024-2025—66.9%

Knowledge GPT-6 Sol leads

GPT-6 Sol: 43.0 (#87), Qwen3 32B: 40.0 (#112)

BenchmarkGPT-6 SolQwen3 32B
Vectara Hallucination Rate6.5%5.9%
LMArena Expert14491362
GPQA Diamond—65.7%

Multimodal Not comparable

GPT-6 Sol: 47.6 (#9), Qwen3 32B: —

BenchmarkGPT-6 SolQwen3 32B
Furniture Assembly58.3%—

Multilingual GPT-6 Sol leads

GPT-6 Sol: 51.0 (#113), Qwen3 32B: 45.8 (#162)

BenchmarkGPT-6 SolQwen3 32B
LMArena Non-English13891317
LMArena Chinese14161357
LMArena Russian14071311
LMArena German—1341
LMArena Spanish1377—

Instruction Following GPT-6 Sol leads

GPT-6 Sol: 74.4 (#97), Qwen3 32B: 69.1 (#174)

BenchmarkGPT-6 SolQwen3 32B
LMArena Instruction Following14061305

Long Context Too close to call

GPT-6 Sol: 43.2 (#100), Qwen3 32B: 43.7 (#83)

BenchmarkGPT-6 SolQwen3 32B
LMArena Longer Query14151327
Fiction.LiveBench—74.2%

Writing & Preference GPT-6 Sol leads

GPT-6 Sol: 72.3 (#15), Qwen3 32B: 53.1 (#158)

BenchmarkGPT-6 SolQwen3 32B
LMArena Text13961340
LMArena Creative Writing13921297
LMArena Multi-Turn14051331
EQ-Bench Creative Writing2125—

Frequently asked questions

Is GPT-6 Sol better than Qwen3 32B?

GPT-6 Sol is the stronger model overall, scoring 49.2 to 38.8 on the Noometry Index. Qwen3 32B costs 3.3× less per token, which makes it the better buy when GPT-6 Sol's lead doesn't matter for your workload.

Which is cheaper, GPT-6 Sol or Qwen3 32B?

Qwen3 32B is cheaper. It lists at $0.70 per million input tokens and $2.80 per million output tokens; GPT-6 Sol lists at $2 and $10.

Is GPT-6 Sol or Qwen3 32B better for coding?

GPT-6 Sol scores higher on coding benchmarks: 59.6 versus 37.3 in the Noometry coding category.

Which has the bigger context window?

GPT-6 Sol does, with 1.05M tokens against 131K.

How many benchmarks do GPT-6 Sol and Qwen3 32B share?

13 benchmarks have published results for both models. GPT-6 Sol has 22 scored results on Noometry and Qwen3 32B has 26.

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