Model comparison

gpt-oss-20b vs Qwen3.5-9B

Qwen3.5-9B is the stronger model overall, scoring 33.8 to 32.5 on the Noometry Index. gpt-oss-20b costs 3.1× less per token, which makes it the better buy when Qwen3.5-9B'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

Qwen3.5-9B

Alibaba (Qwen)

33.8

Rank #236 Confirmed

Summary

They share 9 benchmarks with published results for both. gpt-oss-20b scores higher in 2 categories and Qwen3.5-9B in 3 categories; 5 gaps are clear of the uncertainty.
The widest gap is in knowledge, where Qwen3.5-9B leads 46.0 to 34.6.
The biggest single-benchmark swing is GPQA Diamond: 60.8% for gpt-oss-20b and 79% for Qwen3.5-9B.
gpt-oss-20b is cheaper at $0.018 / $0.09 per million input/output tokens, against $0.10 / $0.15 for Qwen3.5-9B.
Qwen3.5-9B accepts more context: 262K tokens versus 131K.

Side by side

gpt-oss-20b and Qwen3.5-9B specifications
	gpt-oss-20b	Qwen3.5-9B
Provider	OpenAI	Alibaba (Qwen)
Noometry Index	32.5	33.8
Released	2025-08-05	2026-02-23
Weights	Open	Open
Context window	131K	262K
Max output	16K	66K
Input $ / M tokens	$0.018	$0.10
Output $ / M tokens	$0.09	$0.15
Results tracked	34	10

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Category by category

Coding gpt-oss-20b leads

gpt-oss-20b: 37.6 (#192), Qwen3.5-9B: 35.9 (#217)

Coding benchmarks
Benchmark	gpt-oss-20b	Qwen3.5-9B
SciCode	34.4%	27.5%
WeirdML	40.9%	—
LMArena Coding	1306	—
ALE-Bench	566.05	—

Agentic & Tool Use Qwen3.5-9B leads

gpt-oss-20b: 9.3 (#154), Qwen3.5-9B: 14.5 (#151)

Agentic & Tool Use benchmarks
Benchmark	gpt-oss-20b	Qwen3.5-9B
Terminal-Bench	3.4%	9.2%

Reasoning Qwen3.5-9B leads

gpt-oss-20b: 19.3 (#261), Qwen3.5-9B: 23.1 (#182)

Reasoning benchmarks
Benchmark	gpt-oss-20b	Qwen3.5-9B
CritPt	1.4%	0.3%
Chess Puzzles	4%	12%
DTBench	68%	71.2%
LMCA	14.5%	24.5%
Epoch Capabilities Index	137.82	139.46
Kagi LLM Benchmark	53.2%	—
LMArena Hard Prompts	1274	—

Math gpt-oss-20b leads

gpt-oss-20b: 39.4 (#103), Qwen3.5-9B: 34.8 (#192)

Math benchmarks
Benchmark	gpt-oss-20b	Qwen3.5-9B
OTIS Mock AIME 2024-2025	65.3%	61.7%
MathArena Final-Answer Competitions	—	48.5%
Omni-MATH	56.5%	—
LMArena Math	1317	—

Knowledge Qwen3.5-9B leads

gpt-oss-20b: 34.6 (#195), Qwen3.5-9B: 46.0 (#84)

Knowledge benchmarks
Benchmark	gpt-oss-20b	Qwen3.5-9B
GPQA Diamond	60.8%	79%
MMLU-Pro	74%	—
GPQA (HELM)	59.4%	—
LMArena Expert	1258	—

Multilingual Not comparable

gpt-oss-20b: 42.2 (#197), Qwen3.5-9B: —

Multilingual benchmarks
Benchmark	gpt-oss-20b	Qwen3.5-9B
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), Qwen3.5-9B: —

Instruction Following benchmarks
Benchmark	gpt-oss-20b	Qwen3.5-9B
IFEval	73.2%	—
LMArena Instruction Following	1236	—

Long Context Not comparable

gpt-oss-20b: 37.9 (#209), Qwen3.5-9B: —

Long Context benchmarks
Benchmark	gpt-oss-20b	Qwen3.5-9B
LMArena Longer Query	1250	—

Writing & Preference Not comparable

gpt-oss-20b: 35.5 (#265), Qwen3.5-9B: —

Writing & Preference benchmarks
Benchmark	gpt-oss-20b	Qwen3.5-9B
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 Qwen3.5-9B?

Which is cheaper, gpt-oss-20b or Qwen3.5-9B?

gpt-oss-20b is cheaper. It lists at $0.018 per million input tokens and $0.09 per million output tokens; Qwen3.5-9B lists at $0.10 and $0.15.

Is gpt-oss-20b or Qwen3.5-9B better for coding?

gpt-oss-20b scores higher on coding benchmarks: 37.6 versus 35.9 in the Noometry coding category.

Which has the bigger context window?

Qwen3.5-9B does, with 262K tokens against 131K.

How many benchmarks do gpt-oss-20b and Qwen3.5-9B share?

9 benchmarks have published results for both models. gpt-oss-20b has 34 scored results on Noometry and Qwen3.5-9B has 10.