Model comparison

GPT-4 vs Qwen1.5-14B

Qwen1.5-14B is the stronger model overall, scoring 32.7 to 29.1 on the Noometry Index.

Last verified . 17 shared benchmarks.

GPT-4 OpenAI

29.1

Rank #316 Confirmed

Qwen1.5-14B Alibaba (Qwen)

32.7

Rank #253 Confirmed

Summary

  • They share 17 benchmarks with published results for both. GPT-4 scores higher in 4 categories and Qwen1.5-14B in 4 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in math, where Qwen1.5-14B leads 32.4 to 10.8.
  • Qwen1.5-14B has downloadable open weights; the other is API-only.

Side by side

GPT-4 and Qwen1.5-14B specifications
GPT-4Qwen1.5-14B
ProviderOpenAIAlibaba (Qwen)
Noometry Index29.132.7
Released2023-03-142024-02-04
WeightsProprietaryOpen
Context window8K—
Max output8K—
Input $ / M tokens$30—
Output $ / M tokens$60—
Results tracked3817

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Category by category

Coding Qwen1.5-14B leads

GPT-4: 31.6 (#283), Qwen1.5-14B: 33.1 (#263)

Coding benchmarks
BenchmarkGPT-4Qwen1.5-14B
LMArena Coding12541138
WeirdML12.4%—
BigCodeBench Instruct46%—
BigCodeBench Complete57.2%—
HumanEval+79.3%—

Agentic & Tool Use Not comparable

GPT-4: —, Qwen1.5-14B: —

Agentic & Tool Use benchmarks
BenchmarkGPT-4Qwen1.5-14B
METR Time Horizons36.1%—

Reasoning Qwen1.5-14B leads

GPT-4: 17.8 (#289), Qwen1.5-14B: 21.4 (#223)

Reasoning benchmarks
BenchmarkGPT-4Qwen1.5-14B
LMArena Hard Prompts12411113
Chess Puzzles4%—
Mystery Game Puzzles12%—
DTBench62.7%—
LMCA17.1%—
BIG-Bench Hard75.1%—
Epoch Capabilities Index125.89—
ForecastBench57.8—
HellaSwag95.3%—
WinoGrande87.5%—

Math Qwen1.5-14B leads

GPT-4: 10.8 (#309), Qwen1.5-14B: 32.4 (#215)

Math benchmarks
BenchmarkGPT-4Qwen1.5-14B
LMArena Math12691125
OTIS Mock AIME 2024-20251.1%—
MATH Level 523%—
GSM8K92%—

Knowledge Qwen1.5-14B leads

GPT-4: 18.4 (#282), Qwen1.5-14B: 29.8 (#232)

Knowledge benchmarks
BenchmarkGPT-4Qwen1.5-14B
LMArena Expert12111094
MMLU86.4%68.6%
GPQA Diamond35.7%—
TriviaQA84.8%—

Multilingual GPT-4 leads

GPT-4: 40.6 (#215), Qwen1.5-14B: 30.7 (#262)

Multilingual benchmarks
BenchmarkGPT-4Qwen1.5-14B
LMArena Non-English12461095
LMArena Chinese12421147
LMArena French12831116
LMArena German12511043
LMArena Japanese12091019
LMArena Russian12511046
LMArena Spanish12611085
LMArena Korean1184—

Instruction Following GPT-4 leads

GPT-4: 65.3 (#222), Qwen1.5-14B: 56.8 (#271)

Instruction Following benchmarks
BenchmarkGPT-4Qwen1.5-14B
LMArena Instruction Following12411102

Long Context GPT-4 leads

GPT-4: 37.7 (#212), Qwen1.5-14B: 33.7 (#257)

Long Context benchmarks
BenchmarkGPT-4Qwen1.5-14B
LMArena Longer Query12441113

Writing & Preference GPT-4 leads

GPT-4: 34.9 (#268), Qwen1.5-14B: 33.6 (#276)

Writing & Preference benchmarks
BenchmarkGPT-4Qwen1.5-14B
LMArena Text12631128
LMArena Creative Writing12441091
LMArena Multi-Turn12571110
EQ-Bench Creative Writing752—

Frequently asked questions

Is GPT-4 better than Qwen1.5-14B?

Qwen1.5-14B is the stronger model overall, scoring 32.7 to 29.1 on the Noometry Index.

Is GPT-4 or Qwen1.5-14B better for coding?

Qwen1.5-14B scores higher on coding benchmarks: 33.1 versus 31.6 in the Noometry coding category.

How many benchmarks do GPT-4 and Qwen1.5-14B share?

17 benchmarks have published results for both models. GPT-4 has 38 scored results on Noometry and Qwen1.5-14B has 17.

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