Model comparison

GPT-4.1 vs Qwen3.5-9B

GPT-4.1 is the stronger model overall, scoring 35.9 to 33.8 on the Noometry Index. Qwen3.5-9B costs 31× less per token, which makes it the better buy when GPT-4.1's lead doesn't matter for your workload.

Last verified October 10, 2026. 6 shared benchmarks.

GPT-4.1 OpenAI

35.9

Rank #219 Confirmed

Qwen3.5-9B

Alibaba (Qwen)

33.8

Rank #236 Confirmed

Summary

They share 6 benchmarks with published results for both. GPT-4.1 scores higher in 1 category and Qwen3.5-9B in 4 categories; 5 gaps are clear of the uncertainty.
The widest gap is in agentic & tool use, where GPT-4.1 leads 34.7 to 14.5.
The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 38.3% for GPT-4.1 and 61.7% for Qwen3.5-9B.
Qwen3.5-9B is cheaper at $0.10 / $0.15 per million input/output tokens, against $2 / $8 for GPT-4.1.
GPT-4.1 accepts more context: 1.05M tokens versus 262K.
Qwen3.5-9B has downloadable open weights; the other is API-only.

Side by side

GPT-4.1 and Qwen3.5-9B specifications
	GPT-4.1	Qwen3.5-9B
Provider	OpenAI	Alibaba (Qwen)
Noometry Index	35.9	33.8
Released	2025-04-14	2026-02-23
Weights	Proprietary	Open
Context window	1.05M	262K
Max output	33K	66K
Input $ / M tokens	$2	$0.10
Output $ / M tokens	$8	$0.15
Results tracked	52	10

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Category by category

Coding Qwen3.5-9B leads

GPT-4.1: 34.4 (#238), Qwen3.5-9B: 35.9 (#217)

Coding benchmarks
Benchmark	GPT-4.1	Qwen3.5-9B
SWE-bench Verified	48.5%	—
SWE-bench Verified (bash only)	39.6%	—
Aider Polyglot	52.4%	—
SciCode	—	27.5%
WeirdML	39%	—
LMArena Coding	1391	—
CadEval	42%	—
ALE-Bench	558.1	—

Agentic & Tool Use GPT-4.1 leads

GPT-4.1: 34.7 (#43), Qwen3.5-9B: 14.5 (#151)

Agentic & Tool Use benchmarks
Benchmark	GPT-4.1	Qwen3.5-9B
Terminal-Bench	—	9.2%
Berkeley Function Calling Leaderboard	54%	—

Reasoning Qwen3.5-9B leads

GPT-4.1: 11.7 (#339), Qwen3.5-9B: 23.1 (#182)

Reasoning benchmarks
Benchmark	GPT-4.1	Qwen3.5-9B
Chess Puzzles	6%	12%
DTBench	68.3%	71.2%
LMCA	25.6%	24.5%
Epoch Capabilities Index	136.78	139.46
ARC-AGI-2	0.4%	—
SimpleBench	27%	—
Kagi LLM Benchmark	52.3%	—
ARC-AGI-1	5.5%	—
CritPt	—	0.3%
EnigmaEval	2.2%	—
LMArena Hard Prompts	1384	—
ForecastBench	61.5	—

Math Qwen3.5-9B leads

GPT-4.1: 22.3 (#280), Qwen3.5-9B: 34.8 (#192)

Math benchmarks
Benchmark	GPT-4.1	Qwen3.5-9B
OTIS Mock AIME 2024-2025	38.3%	61.7%
FrontierMath (Tiers 1-3)	6%	—
MathArena Final-Answer Competitions	—	48.5%
Omni-MATH	47.1%	—
LMArena Math	1370	—
MATH Level 5	83%	—
FrontierMath (Feb 2025 set)	5.5%	—
FrontierMath Tier 4 (v1)	0%	—

Knowledge Qwen3.5-9B leads

GPT-4.1: 37.1 (#160), Qwen3.5-9B: 46.0 (#84)

Knowledge benchmarks
Benchmark	GPT-4.1	Qwen3.5-9B
GPQA Diamond	66.9%	79%
Humanity's Last Exam	5.4%	—
SimpleQA Verified	31.1%	—
MMLU-Pro	81.1%	—
Vectara Hallucination Rate	5.6%	—
GPQA (HELM)	65.9%	—
LMArena Expert	1364	—

Multimodal Not comparable

GPT-4.1: 38.2 (#67), Qwen3.5-9B: —

Multimodal benchmarks
Benchmark	GPT-4.1	Qwen3.5-9B
LMArena Vision	1211	—
GeoBench	72%	—

Multilingual Not comparable

GPT-4.1: 49.4 (#133), Qwen3.5-9B: —

Multilingual benchmarks
Benchmark	GPT-4.1	Qwen3.5-9B
LMArena Non-English	1370	—
LMArena Chinese	1382	—
LMArena French	1382	—
LMArena German	1381	—
LMArena Japanese	1319	—
LMArena Korean	1339	—
LMArena Russian	1377	—
LMArena Spanish	1376	—

Instruction Following Not comparable

GPT-4.1: 71.3 (#153), Qwen3.5-9B: —

Instruction Following benchmarks
Benchmark	GPT-4.1	Qwen3.5-9B
IFEval	83.8%	—
LMArena Instruction Following	1367	—

Long Context Not comparable

GPT-4.1: 40.0 (#163), Qwen3.5-9B: —

Long Context benchmarks
Benchmark	GPT-4.1	Qwen3.5-9B
Fiction.LiveBench	63.9%	—
LMArena Longer Query	1385	—

Writing & Preference Not comparable

GPT-4.1: 57.6 (#125), Qwen3.5-9B: —

Writing & Preference benchmarks
Benchmark	GPT-4.1	Qwen3.5-9B
LMArena Text	1383	—
LMArena Creative Writing	1363	—
EQ-Bench Creative Writing	1420	—
WildBench	85.4%	—
LMArena Multi-Turn	1398	—

Frequently asked questions

Is GPT-4.1 better than Qwen3.5-9B?

Which is cheaper, GPT-4.1 or Qwen3.5-9B?

Qwen3.5-9B is cheaper. It lists at $0.10 per million input tokens and $0.15 per million output tokens; GPT-4.1 lists at $2 and $8.

Is GPT-4.1 or Qwen3.5-9B better for coding?

Qwen3.5-9B scores higher on coding benchmarks: 35.9 versus 34.4 in the Noometry coding category.

Which has the bigger context window?

GPT-4.1 does, with 1.05M tokens against 262K.

How many benchmarks do GPT-4.1 and Qwen3.5-9B share?

6 benchmarks have published results for both models. GPT-4.1 has 52 scored results on Noometry and Qwen3.5-9B has 10.