Noometry

Model comparison

GPT-4 vs Qwen3.5 27B

Qwen3.5 27B is the stronger model overall, scoring 41.9 to 29.1 on the Noometry Index.

Last verified . 20 shared benchmarks.

GPT-4 OpenAI

29.1

Rank #316 Confirmed

Qwen3.5 27B Alibaba (Qwen)

41.9

Rank #127 Confirmed

Summary

  • They share 20 benchmarks with published results for both. GPT-4 scores higher in 0 categories and Qwen3.5 27B in 8 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in math, where Qwen3.5 27B leads 38.8 to 10.8.
  • The biggest single-benchmark swing is WeirdML: 12.4% for GPT-4 and 39.5% for Qwen3.5 27B.
  • Qwen3.5 27B is cheaper at $0.30 / $2.40 per million input/output tokens, against $30 / $60 for GPT-4.
  • Qwen3.5 27B accepts more context: 262K tokens versus 8K.
  • Qwen3.5 27B has downloadable open weights; the other is API-only.

Side by side

GPT-4Qwen3.5 27B
ProviderOpenAIAlibaba (Qwen)
Noometry Index29.141.9
Released2023-03-142026-02-23
WeightsProprietaryOpen
Context window8K262K
Max output8K66K
Input $ / M tokens$30$0.30
Output $ / M tokens$60$2.40
Results tracked3828

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Category by category

Coding Qwen3.5 27B leads

GPT-4: 31.6 (#283), Qwen3.5 27B: 38.9 (#168)

BenchmarkGPT-4Qwen3.5 27B
WeirdML12.4%39.5%
LMArena Coding12541427
LMArena WebDev—1358
BigCodeBench Instruct46%—
BigCodeBench Complete57.2%—
ALE-Bench—349.45
HumanEval+79.3%—

Agentic & Tool Use Not comparable

GPT-4: —, Qwen3.5 27B: —

BenchmarkGPT-4Qwen3.5 27B
METR Time Horizons36.1%—
Vending-Bench 2—201.98

Reasoning Qwen3.5 27B leads

GPT-4: 17.8 (#289), Qwen3.5 27B: 27.5 (#117)

BenchmarkGPT-4Qwen3.5 27B
LMArena Hard Prompts12411414
DTBench62.7%82.4%
LMCA17.1%34%
NYT Connections (extended)—47.9%
Chess Puzzles4%—
Thematic Generalization—45.5%
Mystery Game Puzzles12%—
BIG-Bench Hard75.1%—
Epoch Capabilities Index125.89—
ForecastBench57.8—
HellaSwag95.3%—
WinoGrande87.5%—

Math Qwen3.5 27B leads

GPT-4: 10.8 (#309), Qwen3.5 27B: 38.8 (#127)

BenchmarkGPT-4Qwen3.5 27B
LMArena Math12691429
MathArena Final-Answer Competitions—56.7%
OTIS Mock AIME 2024-20251.1%—
MATH Level 523%—
GSM8K92%—

Knowledge Qwen3.5 27B leads

GPT-4: 18.4 (#282), Qwen3.5 27B: 38.0 (#150)

BenchmarkGPT-4Qwen3.5 27B
LMArena Expert12111428
GPQA Diamond35.7%—
Vectara Hallucination Rate—12.1%
MMLU86.4%—
TriviaQA84.8%—

Multimodal Not comparable

GPT-4: —, Qwen3.5 27B: 39.4 (#59)

BenchmarkGPT-4Qwen3.5 27B
LMArena Vision—1241

Multilingual Qwen3.5 27B leads

GPT-4: 40.6 (#215), Qwen3.5 27B: 50.8 (#115)

BenchmarkGPT-4Qwen3.5 27B
LMArena Non-English12461390
LMArena Chinese12421478
LMArena French12831410
LMArena German12511393
LMArena Japanese12091345
LMArena Korean11841358
LMArena Russian12511390
LMArena Spanish12611407

Instruction Following Qwen3.5 27B leads

GPT-4: 65.3 (#222), Qwen3.5 27B: 73.5 (#119)

BenchmarkGPT-4Qwen3.5 27B
LMArena Instruction Following12411393

Long Context Qwen3.5 27B leads

GPT-4: 37.7 (#212), Qwen3.5 27B: 43.1 (#106)

BenchmarkGPT-4Qwen3.5 27B
LMArena Longer Query12441413

Writing & Preference Qwen3.5 27B leads

GPT-4: 34.9 (#268), Qwen3.5 27B: 59.3 (#111)

BenchmarkGPT-4Qwen3.5 27B
LMArena Text12631409
LMArena Creative Writing12441362
LMArena Multi-Turn12571410
EQ-Bench Creative Writing752—

Frequently asked questions

Is GPT-4 better than Qwen3.5 27B?

Qwen3.5 27B is the stronger model overall, scoring 41.9 to 29.1 on the Noometry Index.

Which is cheaper, GPT-4 or Qwen3.5 27B?

Qwen3.5 27B is cheaper. It lists at $0.30 per million input tokens and $2.40 per million output tokens; GPT-4 lists at $30 and $60.

Is GPT-4 or Qwen3.5 27B better for coding?

Qwen3.5 27B scores higher on coding benchmarks: 38.9 versus 31.6 in the Noometry coding category.

Which has the bigger context window?

Qwen3.5 27B does, with 262K tokens against 8K.

How many benchmarks do GPT-4 and Qwen3.5 27B share?

20 benchmarks have published results for both models. GPT-4 has 38 scored results on Noometry and Qwen3.5 27B has 28.

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