Model comparison

GPT-4 Turbo vs Qwen2.5 7B Instruct

GPT-4 Turbo is the stronger model overall, scoring 30.5 to 29.0 on the Noometry Index. Qwen2.5 7B Instruct costs 49× less per token, which makes it the better buy when GPT-4 Turbo's lead doesn't matter for your workload.

Last verified October 12, 2026. 9 shared benchmarks.

GPT-4 Turbo OpenAI

30.5

Rank #292 Confirmed

Qwen2.5 7B Instruct

Alibaba (Qwen)

29.0

Rank #320 Confirmed

Summary

They share 9 benchmarks with published results for both. GPT-4 Turbo scores higher in 3 categories and Qwen2.5 7B Instruct in 3 categories; 5 gaps are clear of the uncertainty.
The widest gap is in knowledge, where GPT-4 Turbo leads 24.3 to 17.0.
The biggest single-benchmark swing is DTBench: 61.6% for GPT-4 Turbo and 47.7% for Qwen2.5 7B Instruct.
Qwen2.5 7B Instruct is cheaper at $0.17 / $0.70 per million input/output tokens, against $10 / $30 for GPT-4 Turbo.
Qwen2.5 7B Instruct accepts more context: 131K tokens versus 128K.
Qwen2.5 7B Instruct has downloadable open weights; the other is API-only.

Side by side

GPT-4 Turbo and Qwen2.5 7B Instruct specifications
	GPT-4 Turbo	Qwen2.5 7B Instruct
Provider	OpenAI	Alibaba (Qwen)
Noometry Index	30.5	29.0
Released	2023-11-06	2024-09
Weights	Proprietary	Open
Context window	128K	131K
Max output	4K	8K
Input $ / M tokens	$10	$0.17
Output $ / M tokens	$30	$0.70
Results tracked	36	15

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Category by category

Coding Qwen2.5 7B Instruct leads

GPT-4 Turbo: 33.8 (#249), Qwen2.5 7B Instruct: 36.5 (#208)

Coding benchmarks
Benchmark	GPT-4 Turbo	Qwen2.5 7B Instruct
BigCodeBench Instruct	48.2%	37.6%
BigCodeBench Complete	58.2%	46.1%
WeirdML	18%	—
LMArena Coding	1268	—
HumanEval+	86.6%	—
MBPP+	73.3%	—

Agentic & Tool Use Not comparable

GPT-4 Turbo: —, Qwen2.5 7B Instruct: 23.8 (#124)

Agentic & Tool Use benchmarks
Benchmark	GPT-4 Turbo	Qwen2.5 7B Instruct
BALROG	—	7.8%
METR Time Horizons	36.7%	—

Reasoning Too close to call

GPT-4 Turbo: 15.3 (#317), Qwen2.5 7B Instruct: 14.8 (#322)

Reasoning benchmarks
Benchmark	GPT-4 Turbo	Qwen2.5 7B Instruct
Chess Puzzles	6%	0%
DTBench	61.6%	47.7%
LMCA	9.8%	6.4%
Epoch Capabilities Index	127.25	118.51
SimpleBench	25.1%	—
LMArena Hard Prompts	1251	—
ForecastBench	59.4	—

Math Qwen2.5 7B Instruct leads

GPT-4 Turbo: 9.0 (#322), Qwen2.5 7B Instruct: 12.6 (#306)

Math benchmarks
Benchmark	GPT-4 Turbo	Qwen2.5 7B Instruct
OTIS Mock AIME 2024-2025	6.7%	2.5%
FrontierMath (Tiers 1-3)	0.7%	—
Omni-MATH	—	29.4%
LMArena Math	1272	—
MATH Level 5	46.7%	—

Knowledge GPT-4 Turbo leads

GPT-4 Turbo: 24.3 (#268), Qwen2.5 7B Instruct: 17.0 (#286)

Knowledge benchmarks
Benchmark	GPT-4 Turbo	Qwen2.5 7B Instruct
GPQA Diamond	46.6%	35.5%
MMLU	81.3%	72.9%
MMLU-Pro	—	53.9%
Confabulations	28.4%	—
GPQA (HELM)	—	34.1%
LMArena Expert	1223	—

Multimodal Not comparable

GPT-4 Turbo: 30.6 (#110), Qwen2.5 7B Instruct: —

Multimodal benchmarks
Benchmark	GPT-4 Turbo	Qwen2.5 7B Instruct
LMArena Vision	1090	—

Multilingual Not comparable

GPT-4 Turbo: 40.5 (#216), Qwen2.5 7B Instruct: —

Multilingual benchmarks
Benchmark	GPT-4 Turbo	Qwen2.5 7B Instruct
LMArena Non-English	1245	—
LMArena Chinese	1242	—
LMArena French	1276	—
LMArena German	1259	—
LMArena Japanese	1194	—
LMArena Korean	1187	—
LMArena Russian	1259	—
LMArena Spanish	1260	—

Instruction Following GPT-4 Turbo leads

GPT-4 Turbo: 65.8 (#216), Qwen2.5 7B Instruct: 63.2 (#231)

Instruction Following benchmarks
Benchmark	GPT-4 Turbo	Qwen2.5 7B Instruct
IFEval	—	74.1%
LMArena Instruction Following	1249	—

Long Context Not comparable

GPT-4 Turbo: 38.0 (#206), Qwen2.5 7B Instruct: —

Long Context benchmarks
Benchmark	GPT-4 Turbo	Qwen2.5 7B Instruct
LMArena Longer Query	1254	—

Writing & Preference Qwen2.5 7B Instruct leads

GPT-4 Turbo: 47.7 (#206), Qwen2.5 7B Instruct: 48.8 (#195)

Writing & Preference benchmarks
Benchmark	GPT-4 Turbo	Qwen2.5 7B Instruct
LMArena Text	1272	—
LMArena Creative Writing	1269	—
WildBench	—	73.1%
LMArena Multi-Turn	1267	—

Frequently asked questions

Is GPT-4 Turbo better than Qwen2.5 7B Instruct?

Which is cheaper, GPT-4 Turbo or Qwen2.5 7B Instruct?

Qwen2.5 7B Instruct is cheaper. It lists at $0.17 per million input tokens and $0.70 per million output tokens; GPT-4 Turbo lists at $10 and $30.

Is GPT-4 Turbo or Qwen2.5 7B Instruct better for coding?

Qwen2.5 7B Instruct scores higher on coding benchmarks: 36.5 versus 33.8 in the Noometry coding category.

Which has the bigger context window?

Qwen2.5 7B Instruct does, with 131K tokens against 128K.

How many benchmarks do GPT-4 Turbo and Qwen2.5 7B Instruct share?

9 benchmarks have published results for both models. GPT-4 Turbo has 36 scored results on Noometry and Qwen2.5 7B Instruct has 15.