Noometry

Model comparison

GPT-4 vs Qwen3.8 27B

Qwen3.8 27B is the stronger model overall, scoring 46.0 to 29.1 on the Noometry Index.

Last verified . 21 shared benchmarks.

GPT-4 OpenAI

29.1

Rank #316 Confirmed

Qwen3.8 27B Alibaba (Qwen)

46.0

Rank #68 Confirmed

Summary

  • They share 21 benchmarks with published results for both. GPT-4 scores higher in 0 categories and Qwen3.8 27B in 8 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where Qwen3.8 27B leads 65.8 to 34.9.
  • The biggest single-benchmark swing is DTBench: 62.7% for GPT-4 and 88% for Qwen3.8 27B.
  • Qwen3.8 27B is cheaper at $0.04 / $2.30 per million input/output tokens, against $30 / $60 for GPT-4.
  • Qwen3.8 27B accepts more context: 262K tokens versus 8K.
  • Qwen3.8 27B has downloadable open weights; the other is API-only.

Side by side

GPT-4Qwen3.8 27B
ProviderOpenAIAlibaba (Qwen)
Noometry Index29.146.0
Released2023-03-142026-08-14
WeightsProprietaryOpen
Context window8K262K
Max output8K33K
Input $ / M tokens$30$0.04
Output $ / M tokens$60$2.30
Results tracked3831

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Category by category

Coding Qwen3.8 27B leads

GPT-4: 31.6 (#283), Qwen3.8 27B: 50.5 (#44)

BenchmarkGPT-4Qwen3.8 27B
LMArena Coding12541482
LMArena WebDev—1593
SciCode—46.6%
WeirdML12.4%—
BigCodeBench Instruct46%—
BigCodeBench Complete57.2%—
HumanEval+79.3%—

Agentic & Tool Use Not comparable

GPT-4: —, Qwen3.8 27B: 32.9 (#57)

BenchmarkGPT-4Qwen3.8 27B
APEX-Agents—47.5%
METR Time Horizons36.1%—

Reasoning Qwen3.8 27B leads

GPT-4: 17.8 (#289), Qwen3.8 27B: 41.0 (#54)

BenchmarkGPT-4Qwen3.8 27B
LMArena Hard Prompts12411460
DTBench62.7%88%
LMCA17.1%41.4%
Epoch Capabilities Index125.89149.38
ARC-AGI-2—42.4%
NYT Connections (extended)—54.5%
ARC-AGI-1—87.5%
CritPt—5.4%
Chess Puzzles4%—
Mystery Game Puzzles12%—
Surface Evolver Bench—45%
BIG-Bench Hard75.1%—
ForecastBench57.8—
HellaSwag95.3%—
WinoGrande87.5%—

Math Qwen3.8 27B leads

GPT-4: 10.8 (#309), Qwen3.8 27B: 37.1 (#161)

BenchmarkGPT-4Qwen3.8 27B
LMArena Math12691456
OTIS Mock AIME 2024-20251.1%—
ProofBench—16%
MATH Level 523%—
GSM8K92%—

Knowledge Qwen3.8 27B leads

GPT-4: 18.4 (#282), Qwen3.8 27B: 41.6 (#109)

BenchmarkGPT-4Qwen3.8 27B
LMArena Expert12111482
GPQA Diamond35.7%—
MMLU86.4%—
TriviaQA84.8%—

Multimodal Not comparable

GPT-4: —, Qwen3.8 27B: 41.3 (#37)

BenchmarkGPT-4Qwen3.8 27B
LMArena Vision—1271

Multilingual Qwen3.8 27B leads

GPT-4: 40.6 (#215), Qwen3.8 27B: 53.7 (#60)

BenchmarkGPT-4Qwen3.8 27B
LMArena Non-English12461430
LMArena Chinese12421504
LMArena French12831465
LMArena German12511438
LMArena Japanese12091384
LMArena Korean11841393
LMArena Russian12511415
LMArena Spanish12611448

Instruction Following Qwen3.8 27B leads

GPT-4: 65.3 (#222), Qwen3.8 27B: 75.8 (#53)

BenchmarkGPT-4Qwen3.8 27B
LMArena Instruction Following12411439

Long Context Qwen3.8 27B leads

GPT-4: 37.7 (#212), Qwen3.8 27B: 44.3 (#70)

BenchmarkGPT-4Qwen3.8 27B
LMArena Longer Query12441450

Writing & Preference Qwen3.8 27B leads

GPT-4: 34.9 (#268), Qwen3.8 27B: 65.8 (#43)

BenchmarkGPT-4Qwen3.8 27B
LMArena Text12631441
LMArena Creative Writing12441384
EQ-Bench Creative Writing7521671
LMArena Multi-Turn12571441

Frequently asked questions

Is GPT-4 better than Qwen3.8 27B?

Qwen3.8 27B is the stronger model overall, scoring 46.0 to 29.1 on the Noometry Index.

Which is cheaper, GPT-4 or Qwen3.8 27B?

Qwen3.8 27B is cheaper. It lists at $0.04 per million input tokens and $2.30 per million output tokens; GPT-4 lists at $30 and $60.

Is GPT-4 or Qwen3.8 27B better for coding?

Qwen3.8 27B scores higher on coding benchmarks: 50.5 versus 31.6 in the Noometry coding category.

Which has the bigger context window?

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

How many benchmarks do GPT-4 and Qwen3.8 27B share?

21 benchmarks have published results for both models. GPT-4 has 38 scored results on Noometry and Qwen3.8 27B has 31.

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