Model comparison

GPT-5 Mini vs Qwen3.7 Plus

Qwen3.7 Plus is the stronger model overall, scoring 45.0 to 41.7 on the Noometry Index.

Last verified . 28 shared benchmarks.

GPT-5 Mini OpenAI

41.7

Rank #115 Confirmed

Qwen3.7 Plus Alibaba (Qwen)

45.0

Rank #66 Confirmed

Summary

  • They share 28 benchmarks with published results for both. GPT-5 Mini scores higher in 3 categories and Qwen3.7 Plus in 7 categories; 9 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where Qwen3.7 Plus leads 38.4 to 24.1.
  • The biggest single-benchmark swing is GPQA Diamond: 75% for GPT-5 Mini and 87.9% for Qwen3.7 Plus.
  • Both cost about the same: $0.25 input and $2 output per million tokens.
  • Qwen3.7 Plus accepts more context: 1M tokens versus 400K.

Side by side

GPT-5 Mini and Qwen3.7 Plus specifications
GPT-5 MiniQwen3.7 Plus
ProviderOpenAIAlibaba (Qwen)
Noometry Index41.745.0
Released2025-08-072026-06-02
WeightsProprietaryProprietary
Context window400K1M
Max output128K131K
Input $ / M tokens$0.25$0.40
Output $ / M tokens$2$1.60
Results tracked6032

Sponsored placements are available on pages like this one. Advertise on Noometry

Category by category

Coding GPT-5 Mini leads

GPT-5 Mini: 40.0 (#134), Qwen3.7 Plus: 36.1 (#200)

Coding benchmarks
BenchmarkGPT-5 MiniQwen3.7 Plus
SciCode39.2%45.5%
LMArena Coding14061473
SWE-bench Verified64.7%—
FrontierCode—10.2%
SWE-bench Verified (bash only)59.8%—
SWE-bench Multilingual39.7%—
WeirdML52.7%—
ALE-Bench799.77—
AlgoTune1.38—

Agentic & Tool Use GPT-5 Mini leads

GPT-5 Mini: 31.0 (#64), Qwen3.7 Plus: 21.2 (#130)

Agentic & Tool Use benchmarks
BenchmarkGPT-5 MiniQwen3.7 Plus
Terminal-Bench34.8%—
Berkeley Function Calling Leaderboard55.5%—
OSWorld 2.0—2.8%
Vending-Bench 2-31.18—

Reasoning Qwen3.7 Plus leads

GPT-5 Mini: 24.1 (#153), Qwen3.7 Plus: 38.4 (#54)

Reasoning benchmarks
BenchmarkGPT-5 MiniQwen3.7 Plus
CritPt0%9.1%
Chess Puzzles30%24%
LMArena Hard Prompts13801460
Mystery Game Puzzles10%17%
DTBench80.5%84%
LMCA34.2%37.6%
Epoch Capabilities Index145.51147.39
ARC-AGI-24.4%—
Kagi LLM Benchmark70.3%—
NYT Connections (extended)—74.8%
ARC-AGI-154.3%—
EnigmaEval8.2%—
ForecastBench61—

Math Qwen3.7 Plus leads

GPT-5 Mini: 46.3 (#59), Qwen3.7 Plus: 49.3 (#47)

Math benchmarks
BenchmarkGPT-5 MiniQwen3.7 Plus
FrontierMath (Tiers 1-3)46.7%34.4%
OTIS Mock AIME 2024-202586.7%93.3%
LMArena Math13771467
FrontierMath Tier 412.2%—
ProofBench9%—
Omni-MATH72.2%—
MATH Level 597.8%—
FrontierMath (Feb 2025 set)27.2%—
FrontierMath Tier 4 (v1)6.3%—

Knowledge Qwen3.7 Plus leads

GPT-5 Mini: 45.5 (#80), Qwen3.7 Plus: 54.9 (#46)

Knowledge benchmarks
BenchmarkGPT-5 MiniQwen3.7 Plus
GPQA Diamond75%87.9%
LMArena Expert13771467
Humanity's Last Exam19.4%—
SimpleQA Verified21.6%—
MMLU-Pro83.5%—
Confabulations13.3%—
Vectara Hallucination Rate12.9%—
GPQA (HELM)75.6%—

Multimodal Qwen3.7 Plus leads

GPT-5 Mini: 35.0 (#80), Qwen3.7 Plus: 41.2 (#30)

Multimodal benchmarks
BenchmarkGPT-5 MiniQwen3.7 Plus
LMArena Vision12021281
VPCT40.2%—
LMArena Document—1444

Multilingual Qwen3.7 Plus leads

GPT-5 Mini: 49.1 (#131), Qwen3.7 Plus: 55.0 (#36)

Multilingual benchmarks
BenchmarkGPT-5 MiniQwen3.7 Plus
LMArena Non-English13631445
LMArena Chinese13871510
LMArena French13851471
LMArena German13661471
LMArena Japanese13421411
LMArena Korean13061416
LMArena Russian13621457
LMArena Spanish13551453

Instruction Following Too close to call

GPT-5 Mini: 76.4 (#43), Qwen3.7 Plus: 75.9 (#49)

Instruction Following benchmarks
BenchmarkGPT-5 MiniQwen3.7 Plus
LMArena Instruction Following13571439
IFEval92.7%—

Long Context Qwen3.7 Plus leads

GPT-5 Mini: 41.9 (#127), Qwen3.7 Plus: 44.5 (#61)

Long Context benchmarks
BenchmarkGPT-5 MiniQwen3.7 Plus
LMArena Longer Query13551454
Fiction.LiveBench69.4%—

Writing & Preference Qwen3.7 Plus leads

GPT-5 Mini: 55.4 (#143), Qwen3.7 Plus: 64.5 (#54)

Writing & Preference benchmarks
BenchmarkGPT-5 MiniQwen3.7 Plus
LMArena Text13731454
LMArena Creative Writing13251439
LMArena Multi-Turn13631459
Short-Story Creative Writing83.1%—
EQ-Bench Creative Writing1313—
WildBench85.5%—

Frequently asked questions

Is GPT-5 Mini better than Qwen3.7 Plus?

Qwen3.7 Plus is the stronger model overall, scoring 45.0 to 41.7 on the Noometry Index.

Which is cheaper, GPT-5 Mini or Qwen3.7 Plus?

GPT-5 Mini is cheaper. It lists at $0.25 per million input tokens and $2 per million output tokens; Qwen3.7 Plus lists at $0.40 and $1.60.

Is GPT-5 Mini or Qwen3.7 Plus better for coding?

GPT-5 Mini scores higher on coding benchmarks: 40.0 versus 36.1 in the Noometry coding category.

Which has the bigger context window?

Qwen3.7 Plus does, with 1M tokens against 400K.

How many benchmarks do GPT-5 Mini and Qwen3.7 Plus share?

28 benchmarks have published results for both models. GPT-5 Mini has 60 scored results on Noometry and Qwen3.7 Plus has 32.

Related comparisons

Go deeper