Noometry

Model comparison

GPT-4 vs Qwen3.5-9B

Qwen3.5-9B is the stronger model overall, scoring 33.8 to 29.1 on the Noometry Index.

Last verified . 6 shared benchmarks.

GPT-4 OpenAI

29.1

Rank #316 Confirmed

Qwen3.5-9B Alibaba (Qwen)

33.8

Rank #236 Confirmed

Summary

  • They share 6 benchmarks with published results for both. GPT-4 scores higher in 0 categories and Qwen3.5-9B in 4 categories; 4 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where Qwen3.5-9B leads 46.0 to 18.4.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 1.1% for GPT-4 and 61.7% for Qwen3.5-9B.
  • Qwen3.5-9B is cheaper at $0.10 / $0.15 per million input/output tokens, against $30 / $60 for GPT-4.
  • Qwen3.5-9B accepts more context: 262K tokens versus 8K.
  • Qwen3.5-9B has downloadable open weights; the other is API-only.

Side by side

GPT-4Qwen3.5-9B
ProviderOpenAIAlibaba (Qwen)
Noometry Index29.133.8
Released2023-03-142026-02-23
WeightsProprietaryOpen
Context window8K262K
Max output8K66K
Input $ / M tokens$30$0.10
Output $ / M tokens$60$0.15
Results tracked3810

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Category by category

Coding Qwen3.5-9B leads

GPT-4: 31.6 (#283), Qwen3.5-9B: 35.9 (#217)

BenchmarkGPT-4Qwen3.5-9B
SciCode—27.5%
WeirdML12.4%—
BigCodeBench Instruct46%—
LMArena Coding1254—
BigCodeBench Complete57.2%—
HumanEval+79.3%—

Agentic & Tool Use Not comparable

GPT-4: —, Qwen3.5-9B: 14.5 (#151)

BenchmarkGPT-4Qwen3.5-9B
Terminal-Bench—9.2%
METR Time Horizons36.1%—

Reasoning Qwen3.5-9B leads

GPT-4: 17.8 (#289), Qwen3.5-9B: 23.1 (#182)

BenchmarkGPT-4Qwen3.5-9B
Chess Puzzles4%12%
DTBench62.7%71.2%
LMCA17.1%24.5%
Epoch Capabilities Index125.89139.46
CritPt—0.3%
LMArena Hard Prompts1241—
Mystery Game Puzzles12%—
BIG-Bench Hard75.1%—
ForecastBench57.8—
HellaSwag95.3%—
WinoGrande87.5%—

Math Qwen3.5-9B leads

GPT-4: 10.8 (#309), Qwen3.5-9B: 34.8 (#192)

BenchmarkGPT-4Qwen3.5-9B
OTIS Mock AIME 2024-20251.1%61.7%
MathArena Final-Answer Competitions—48.5%
LMArena Math1269—
MATH Level 523%—
GSM8K92%—

Knowledge Qwen3.5-9B leads

GPT-4: 18.4 (#282), Qwen3.5-9B: 46.0 (#84)

BenchmarkGPT-4Qwen3.5-9B
GPQA Diamond35.7%79%
LMArena Expert1211—
MMLU86.4%—
TriviaQA84.8%—

Multilingual Not comparable

GPT-4: 40.6 (#215), Qwen3.5-9B: —

BenchmarkGPT-4Qwen3.5-9B
LMArena Non-English1246—
LMArena Chinese1242—
LMArena French1283—
LMArena German1251—
LMArena Japanese1209—
LMArena Korean1184—
LMArena Russian1251—
LMArena Spanish1261—

Instruction Following Not comparable

GPT-4: 65.3 (#222), Qwen3.5-9B: —

BenchmarkGPT-4Qwen3.5-9B
LMArena Instruction Following1241—

Long Context Not comparable

GPT-4: 37.7 (#212), Qwen3.5-9B: —

BenchmarkGPT-4Qwen3.5-9B
LMArena Longer Query1244—

Writing & Preference Not comparable

GPT-4: 34.9 (#268), Qwen3.5-9B: —

BenchmarkGPT-4Qwen3.5-9B
LMArena Text1263—
LMArena Creative Writing1244—
EQ-Bench Creative Writing752—
LMArena Multi-Turn1257—

Frequently asked questions

Is GPT-4 better than Qwen3.5-9B?

Qwen3.5-9B is the stronger model overall, scoring 33.8 to 29.1 on the Noometry Index.

Which is cheaper, GPT-4 or Qwen3.5-9B?

Qwen3.5-9B is cheaper. It lists at $0.10 per million input tokens and $0.15 per million output tokens; GPT-4 lists at $30 and $60.

Is GPT-4 or Qwen3.5-9B better for coding?

Qwen3.5-9B scores higher on coding benchmarks: 35.9 versus 31.6 in the Noometry coding category.

Which has the bigger context window?

Qwen3.5-9B does, with 262K tokens against 8K.

How many benchmarks do GPT-4 and Qwen3.5-9B share?

6 benchmarks have published results for both models. GPT-4 has 38 scored results on Noometry and Qwen3.5-9B has 10.

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