Model comparison

gpt-oss-20b vs Qwen3 14B

Qwen3 14B is the stronger model overall, scoring 35.5 to 32.5 on the Noometry Index. gpt-oss-20b costs 17× less per token, which makes it the better buy when Qwen3 14B's lead doesn't matter for your workload.

Last verified October 10, 2026. 9 shared benchmarks.

gpt-oss-20b OpenAI

32.5

Rank #255 Confirmed

Qwen3 14B

Alibaba (Qwen)

35.5

Rank #225 Confirmed

Summary

They share 9 benchmarks with published results for both. gpt-oss-20b scores higher in 3 categories and Qwen3 14B in 3 categories; 2 gaps are clear of the uncertainty.
The widest gap is in agentic & tool use, where Qwen3 14B leads 29.6 to 9.3.
gpt-oss-20b is cheaper at $0.018 / $0.09 per million input/output tokens, against $0.35 / $1.40 for Qwen3 14B.

Side by side

gpt-oss-20b and Qwen3 14B specifications
	gpt-oss-20b	Qwen3 14B
Provider	OpenAI	Alibaba (Qwen)
Noometry Index	32.5	35.5
Released	2025-08-05	2025-04
Weights	Open	Open
Context window	131K	131K
Max output	16K	8K
Input $ / M tokens	$0.018	$0.35
Output $ / M tokens	$0.09	$1.40
Results tracked	34	12

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Category by category

Coding Too close to call

gpt-oss-20b: 37.6 (#192), Qwen3 14B: 37.3 (#195)

Coding benchmarks
Benchmark	gpt-oss-20b	Qwen3 14B
SciCode	34.4%	31.6%
WeirdML	40.9%	—
LMArena Coding	1306	—
ALE-Bench	566.05	—

Agentic & Tool Use Qwen3 14B leads

gpt-oss-20b: 9.3 (#154), Qwen3 14B: 29.6 (#83)

Agentic & Tool Use benchmarks
Benchmark	gpt-oss-20b	Qwen3 14B
Terminal-Bench	3.4%	—
Berkeley Function Calling Leaderboard	—	41%

Reasoning Too close to call

gpt-oss-20b: 19.3 (#261), Qwen3 14B: 18.5 (#280)

Reasoning benchmarks
Benchmark	gpt-oss-20b	Qwen3 14B
Kagi LLM Benchmark	53.2%	49.1%
CritPt	1.4%	0%
Chess Puzzles	4%	4%
DTBench	68%	64%
LMCA	14.5%	18.2%
Epoch Capabilities Index	137.82	138.23
LMArena Hard Prompts	1274	—

Math Too close to call

gpt-oss-20b: 39.4 (#103), Qwen3 14B: 38.6 (#133)

Math benchmarks
Benchmark	gpt-oss-20b	Qwen3 14B
OTIS Mock AIME 2024-2025	65.3%	66.4%
Omni-MATH	56.5%	—
LMArena Math	1317	—

Knowledge Qwen3 14B leads

gpt-oss-20b: 34.6 (#195), Qwen3 14B: 39.3 (#134)

Knowledge benchmarks
Benchmark	gpt-oss-20b	Qwen3 14B
GPQA Diamond	60.8%	63.8%
MMLU-Pro	74%	—
Vectara Hallucination Rate	—	5.4%
GPQA (HELM)	59.4%	—
LMArena Expert	1258	—

Multilingual Not comparable

gpt-oss-20b: 42.2 (#197), Qwen3 14B: —

Multilingual benchmarks
Benchmark	gpt-oss-20b	Qwen3 14B
LMArena Non-English	1268	—
LMArena Chinese	1314	—
LMArena German	1255	—
LMArena Japanese	1244	—
LMArena Korean	1236	—
LMArena Russian	1278	—
LMArena Spanish	1267	—

Instruction Following Not comparable

gpt-oss-20b: 61.8 (#240), Qwen3 14B: —

Instruction Following benchmarks
Benchmark	gpt-oss-20b	Qwen3 14B
IFEval	73.2%	—
LMArena Instruction Following	1236	—

Long Context Too close to call

gpt-oss-20b: 37.9 (#209), Qwen3 14B: 38.1 (#204)

Long Context benchmarks
Benchmark	gpt-oss-20b	Qwen3 14B
Fiction.LiveBench	—	62.5%
LMArena Longer Query	1250	—

Writing & Preference Not comparable

gpt-oss-20b: 35.5 (#265), Qwen3 14B: —

Writing & Preference benchmarks
Benchmark	gpt-oss-20b	Qwen3 14B
LMArena Text	1287	—
LMArena Creative Writing	1201	—
EQ-Bench Creative Writing	666	—
WildBench	73.7%	—
LMArena Multi-Turn	1268	—

Frequently asked questions

Is gpt-oss-20b better than Qwen3 14B?

Which is cheaper, gpt-oss-20b or Qwen3 14B?

gpt-oss-20b is cheaper. It lists at $0.018 per million input tokens and $0.09 per million output tokens; Qwen3 14B lists at $0.35 and $1.40.

Is gpt-oss-20b or Qwen3 14B better for coding?

They score almost the same on coding (37.6 vs 37.3); test both on your own repository before choosing.

Which has the bigger context window?

Both accept 131K tokens.

How many benchmarks do gpt-oss-20b and Qwen3 14B share?

9 benchmarks have published results for both models. gpt-oss-20b has 34 scored results on Noometry and Qwen3 14B has 12.