Model comparison

GPT-4o vs Qwen3.5 397B-A17B

Qwen3.5 397B-A17B is the stronger model overall, scoring 46.0 to 28.6 on the Noometry Index.

Last verified . 25 shared benchmarks.

GPT-4o OpenAI

28.6

Rank #324 Confirmed

Qwen3.5 397B-A17B Alibaba (Qwen)

46.0

Rank #67 Confirmed

Summary

  • They share 25 benchmarks with published results for both. GPT-4o scores higher in 0 categories and Qwen3.5 397B-A17B in 10 categories; 10 gaps are clear of the uncertainty.
  • The widest gap is in math, where Qwen3.5 397B-A17B leads 46.1 to 10.6.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 6.4% for GPT-4o and 88.9% for Qwen3.5 397B-A17B.
  • Qwen3.5 397B-A17B is cheaper at $0.60 / $3.60 per million input/output tokens, against $2.50 / $10 for GPT-4o.
  • Qwen3.5 397B-A17B accepts more context: 262K tokens versus 128K.
  • Qwen3.5 397B-A17B has downloadable open weights; the other is API-only.

Side by side

GPT-4o and Qwen3.5 397B-A17B specifications
GPT-4oQwen3.5 397B-A17B
ProviderOpenAIAlibaba (Qwen)
Noometry Index28.646.0
Released2024-05-132026-02-01
WeightsProprietaryOpen
Context window128K262K
Max output16K66K
Input $ / M tokens$2.50$0.60
Output $ / M tokens$10$3.60
Results tracked7236

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

Category by category

Coding Qwen3.5 397B-A17B leads

GPT-4o: 24.8 (#328), Qwen3.5 397B-A17B: 42.0 (#114)

Coding benchmarks
BenchmarkGPT-4oQwen3.5 397B-A17B
LMArena Coding12971465
SWE-bench Verified31%—
SWE-bench Verified (bash only)21.6%—
Aider Polyglot45.3%—
LMArena WebDev—1400
GSO0%—
WeirdML25.1%—
BigCodeBench Instruct51.1%—
LiveBench Coding51.4%—
BigCodeBench Complete61.1%—
CadEval26%—
HumanEval+87.2%—
MBPP+72.2%—

Agentic & Tool Use Qwen3.5 397B-A17B leads

GPT-4o: 21.0 (#141), Qwen3.5 397B-A17B: 33.3 (#53)

Agentic & Tool Use benchmarks
BenchmarkGPT-4oQwen3.5 397B-A17B
APEX-Agents—24.9%
GDPval9.9%—
TheAgentCompany8.6%—
τ²-bench Airline—81.5%
τ²-bench Banking—9.8%
τ²-bench Retail—84.4%
τ²-bench Telecom—97.8%
Cybench12.5%—
BALROG32.3%—
LMArena Search1006—
METR Time Horizons40.8%—

Reasoning Qwen3.5 397B-A17B leads

GPT-4o: 9.4 (#343), Qwen3.5 397B-A17B: 34.5 (#70)

Reasoning benchmarks
BenchmarkGPT-4oQwen3.5 397B-A17B
Chess Puzzles13%13%
LMArena Hard Prompts12811448
DTBench64.5%87.5%
LMCA16.6%37.9%
Epoch Capabilities Index128.97146.65
ARC-AGI-20%—
SimpleBench17.8%—
Kagi LLM Benchmark—73.7%
NYT Connections (extended)—58.9%
ARC-AGI-14.5%—
CritPt0%—
EnigmaEval0.8%—
Thematic Generalization—65.1%
LiveBench Reasoning55.8%—
Mystery Game Puzzles—18%
LiveBench Data Analysis60.9%—
ForecastBench57.7—
LiveBench55.3%—

Math Qwen3.5 397B-A17B leads

GPT-4o: 10.6 (#312), Qwen3.5 397B-A17B: 46.1 (#73)

Math benchmarks
BenchmarkGPT-4oQwen3.5 397B-A17B
FrontierMath (Tiers 1-3)0.4%31.2%
OTIS Mock AIME 2024-20256.4%88.9%
LMArena Math12851454
Omni-MATH29.3%—
LiveBench Math49.5%—
MATH Level 553.3%—
FrontierMath (Feb 2025 set)0.3%—

Knowledge Qwen3.5 397B-A17B leads

GPT-4o: 28.8 (#242), Qwen3.5 397B-A17B: 53.3 (#58)

Knowledge benchmarks
BenchmarkGPT-4oQwen3.5 397B-A17B
GPQA Diamond49.2%86.4%
LMArena Expert12501462
Humanity's Last Exam2.7%—
SimpleQA Verified26%—
MMLU-Pro71.3%—
Confabulations15.3%—
Vectara Hallucination Rate9.6%—
GPQA (HELM)52%—
MMLU88.1%—

Multimodal Qwen3.5 397B-A17B leads

GPT-4o: 34.5 (#91), Qwen3.5 397B-A17B: 40.7 (#44)

Multimodal benchmarks
BenchmarkGPT-4oQwen3.5 397B-A17B
LMArena Vision11371263
Video-MME71.9%—
GeoBench71%—
VPCT40%—
ScienceQA88.5%—

Multilingual Qwen3.5 397B-A17B leads

GPT-4o: 43.2 (#186), Qwen3.5 397B-A17B: 53.7 (#59)

Multilingual benchmarks
BenchmarkGPT-4oQwen3.5 397B-A17B
LMArena Non-English12831430
LMArena Chinese12771500
LMArena French13041461
LMArena German12821447
LMArena Japanese12571426
LMArena Korean12341384
LMArena Russian12861429
LMArena Spanish12921441

Instruction Following Qwen3.5 397B-A17B leads

GPT-4o: 66.6 (#207), Qwen3.5 397B-A17B: 75.0 (#77)

Instruction Following benchmarks
BenchmarkGPT-4oQwen3.5 397B-A17B
LMArena Instruction Following12781424
LiveBench Instruction Following68.6%—
IFEval81.7%—

Long Context Qwen3.5 397B-A17B leads

GPT-4o: 39.4 (#179), Qwen3.5 397B-A17B: 44.1 (#74)

Long Context benchmarks
BenchmarkGPT-4oQwen3.5 397B-A17B
LMArena Longer Query12891442
Fiction.LiveBench66.7%—

Writing & Preference Qwen3.5 397B-A17B leads

GPT-4o: 52.6 (#166), Qwen3.5 397B-A17B: 62.3 (#79)

Writing & Preference benchmarks
BenchmarkGPT-4oQwen3.5 397B-A17B
LMArena Text13001438
LMArena Creative Writing12921401
LMArena Multi-Turn13021446
Short-Story Creative Writing81.8%—
EQ-Bench Creative Writing—1478
WildBench82.8%—
LiveBench Language47.6%—

Frequently asked questions

Is GPT-4o better than Qwen3.5 397B-A17B?

Qwen3.5 397B-A17B is the stronger model overall, scoring 46.0 to 28.6 on the Noometry Index.

Which is cheaper, GPT-4o or Qwen3.5 397B-A17B?

Qwen3.5 397B-A17B is cheaper. It lists at $0.60 per million input tokens and $3.60 per million output tokens; GPT-4o lists at $2.50 and $10.

Is GPT-4o or Qwen3.5 397B-A17B better for coding?

Qwen3.5 397B-A17B scores higher on coding benchmarks: 42.0 versus 24.8 in the Noometry coding category.

Which has the bigger context window?

Qwen3.5 397B-A17B does, with 262K tokens against 128K.

How many benchmarks do GPT-4o and Qwen3.5 397B-A17B share?

25 benchmarks have published results for both models. GPT-4o has 72 scored results on Noometry and Qwen3.5 397B-A17B has 36.

Related comparisons

Go deeper