Noometry

Model comparison

GPT-4 Turbo vs Qwen3 14B

Qwen3 14B is the stronger model overall, scoring 35.5 to 30.5 on the Noometry Index.

Last verified . 6 shared benchmarks.

GPT-4 Turbo OpenAI

30.5

Rank #292 Confirmed

Qwen3 14B Alibaba (Qwen)

35.5

Rank #225 Confirmed

Summary

  • They share 6 benchmarks with published results for both. GPT-4 Turbo scores higher in 0 categories and Qwen3 14B in 5 categories; 4 gaps are clear of the uncertainty.
  • The widest gap is in math, where Qwen3 14B leads 38.6 to 9.0.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 6.7% for GPT-4 Turbo and 66.4% for Qwen3 14B.
  • Qwen3 14B is cheaper at $0.35 / $1.40 per million input/output tokens, against $10 / $30 for GPT-4 Turbo.
  • Qwen3 14B accepts more context: 131K tokens versus 128K.
  • Qwen3 14B has downloadable open weights; the other is API-only.

Side by side

GPT-4 TurboQwen3 14B
ProviderOpenAIAlibaba (Qwen)
Noometry Index30.535.5
Released2023-11-062025-04
WeightsProprietaryOpen
Context window128K131K
Max output4K8K
Input $ / M tokens$10$0.35
Output $ / M tokens$30$1.40
Results tracked3612

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

Category by category

Coding Qwen3 14B leads

GPT-4 Turbo: 33.8 (#249), Qwen3 14B: 37.3 (#195)

BenchmarkGPT-4 TurboQwen3 14B
SciCode—31.6%
WeirdML18%—
BigCodeBench Instruct48.2%—
LMArena Coding1268—
BigCodeBench Complete58.2%—
HumanEval+86.6%—
MBPP+73.3%—

Agentic & Tool Use Not comparable

GPT-4 Turbo: —, Qwen3 14B: 29.6 (#83)

BenchmarkGPT-4 TurboQwen3 14B
Berkeley Function Calling Leaderboard—41%
METR Time Horizons36.7%—

Reasoning Qwen3 14B leads

GPT-4 Turbo: 15.3 (#317), Qwen3 14B: 18.5 (#280)

BenchmarkGPT-4 TurboQwen3 14B
Chess Puzzles6%4%
DTBench61.6%64%
LMCA9.8%18.2%
Epoch Capabilities Index127.25138.23
SimpleBench25.1%—
Kagi LLM Benchmark—49.1%
CritPt—0%
LMArena Hard Prompts1251—
ForecastBench59.4—

Math Qwen3 14B leads

GPT-4 Turbo: 9.0 (#322), Qwen3 14B: 38.6 (#133)

BenchmarkGPT-4 TurboQwen3 14B
OTIS Mock AIME 2024-20256.7%66.4%
FrontierMath (Tiers 1-3)0.7%—
LMArena Math1272—
MATH Level 546.7%—

Knowledge Qwen3 14B leads

GPT-4 Turbo: 24.3 (#268), Qwen3 14B: 39.3 (#134)

BenchmarkGPT-4 TurboQwen3 14B
GPQA Diamond46.6%63.8%
Confabulations28.4%—
Vectara Hallucination Rate—5.4%
LMArena Expert1223—
MMLU81.3%—

Multimodal Not comparable

GPT-4 Turbo: 30.6 (#110), Qwen3 14B: —

BenchmarkGPT-4 TurboQwen3 14B
LMArena Vision1090—

Multilingual Not comparable

GPT-4 Turbo: 40.5 (#216), Qwen3 14B: —

BenchmarkGPT-4 TurboQwen3 14B
LMArena Non-English1245—
LMArena Chinese1242—
LMArena French1276—
LMArena German1259—
LMArena Japanese1194—
LMArena Korean1187—
LMArena Russian1259—
LMArena Spanish1260—

Instruction Following Not comparable

GPT-4 Turbo: 65.8 (#216), Qwen3 14B: —

BenchmarkGPT-4 TurboQwen3 14B
LMArena Instruction Following1249—

Long Context Too close to call

GPT-4 Turbo: 38.0 (#206), Qwen3 14B: 38.1 (#204)

BenchmarkGPT-4 TurboQwen3 14B
Fiction.LiveBench—62.5%
LMArena Longer Query1254—

Writing & Preference Not comparable

GPT-4 Turbo: 47.7 (#206), Qwen3 14B: —

BenchmarkGPT-4 TurboQwen3 14B
LMArena Text1272—
LMArena Creative Writing1269—
LMArena Multi-Turn1267—

Frequently asked questions

Is GPT-4 Turbo better than Qwen3 14B?

Qwen3 14B is the stronger model overall, scoring 35.5 to 30.5 on the Noometry Index.

Which is cheaper, GPT-4 Turbo or Qwen3 14B?

Qwen3 14B is cheaper. It lists at $0.35 per million input tokens and $1.40 per million output tokens; GPT-4 Turbo lists at $10 and $30.

Is GPT-4 Turbo or Qwen3 14B better for coding?

Qwen3 14B scores higher on coding benchmarks: 37.3 versus 33.8 in the Noometry coding category.

Which has the bigger context window?

Qwen3 14B does, with 131K tokens against 128K.

How many benchmarks do GPT-4 Turbo and Qwen3 14B share?

6 benchmarks have published results for both models. GPT-4 Turbo has 36 scored results on Noometry and Qwen3 14B has 12.

Related comparisons

Go deeper