Model comparison

GPT-6 Sol vs Qwen3.5-9B

GPT-6 Sol is the stronger model overall, scoring 49.2 to 33.3 on the Noometry Index. Qwen3.5-9B costs 36× less per token, which makes it the better buy when GPT-6 Sol's lead doesn't matter for your workload.

Last verified October 10, 2026. 0 shared benchmarks.

GPT-6 Sol OpenAI

49.2

Rank #46 Confirmed

Qwen3.5-9B

Alibaba (Qwen)

33.3

Rank #235 Confirmed

Summary

The widest gap is in reasoning, where GPT-6 Sol leads 49.3 to 22.5.
Qwen3.5-9B is cheaper at $0.10 / $0.15 per million input/output tokens, against $2 / $10 for GPT-6 Sol.
GPT-6 Sol accepts more context: 1.05M tokens versus 262K.
Qwen3.5-9B has downloadable open weights; the other is API-only.

Side by side

GPT-6 Sol and Qwen3.5-9B specifications
	GPT-6 Sol	Qwen3.5-9B
Provider	OpenAI	Alibaba (Qwen)
Noometry Index	49.2	33.3
Released	2026-09-22	2026-02-23
Weights	Proprietary	Open
Context window	1.05M	262K
Max output	128K	66K
Input $ / M tokens	$2	$0.10
Output $ / M tokens	$10	$0.15
Results tracked	22	10

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Category by category

Coding GPT-6 Sol leads

GPT-6 Sol: 59.6 (#11), Qwen3.5-9B: 35.3 (#213)

Coding benchmarks
Benchmark	GPT-6 Sol	Qwen3.5-9B
DeepSWE	68.8%	—
FrontierCode	49.3%	—
LMArena WebDev	1692	—
SciCode	—	27.5%
LMArena Coding	1453	—

Agentic & Tool Use GPT-6 Sol leads

GPT-6 Sol: 33.5 (#49), Qwen3.5-9B: 14.4 (#143)

Agentic & Tool Use benchmarks
Benchmark	GPT-6 Sol	Qwen3.5-9B
Terminal-Bench	—	9.2%
GDP.pdf	28%	—

Reasoning GPT-6 Sol leads

GPT-6 Sol: 49.3 (#34), Qwen3.5-9B: 22.5 (#178)

Reasoning benchmarks
Benchmark	GPT-6 Sol	Qwen3.5-9B
NYT Connections (extended)	90.1%	—
CritPt	—	0.3%
Chess Puzzles	—	12%
EBR-Bench	53.3%	—
LMArena Hard Prompts	1420	—
DTBench	—	71.2%
LMCA	—	24.5%
Epoch Capabilities Index	—	139.45

Math GPT-6 Sol leads

GPT-6 Sol: 35.8 (#135), Qwen3.5-9B: 33.5 (#174)

Math benchmarks
Benchmark	GPT-6 Sol	Qwen3.5-9B
MathArena Final-Answer Competitions	—	48.5%
OTIS Mock AIME 2024-2025	—	61.7%
LMArena Math	1404	—

Knowledge Qwen3.5-9B leads

GPT-6 Sol: 43.0 (#87), Qwen3.5-9B: 46.0 (#77)

Knowledge benchmarks
Benchmark	GPT-6 Sol	Qwen3.5-9B
GPQA Diamond	—	79%
Vectara Hallucination Rate	6.5%	—
LMArena Expert	1449	—

Multimodal Not comparable

GPT-6 Sol: 47.6 (#9), Qwen3.5-9B: —

Multimodal benchmarks
Benchmark	GPT-6 Sol	Qwen3.5-9B
Furniture Assembly	58.3%	—

Multilingual Not comparable

GPT-6 Sol: 51.0 (#113), Qwen3.5-9B: —

Multilingual benchmarks
Benchmark	GPT-6 Sol	Qwen3.5-9B
LMArena Non-English	1389	—
LMArena Chinese	1416	—
LMArena Russian	1407	—
LMArena Spanish	1377	—

Instruction Following Not comparable

GPT-6 Sol: 74.4 (#97), Qwen3.5-9B: —

Instruction Following benchmarks
Benchmark	GPT-6 Sol	Qwen3.5-9B
LMArena Instruction Following	1406	—

Long Context Not comparable

GPT-6 Sol: 43.2 (#100), Qwen3.5-9B: —

Long Context benchmarks
Benchmark	GPT-6 Sol	Qwen3.5-9B
LMArena Longer Query	1415	—

Writing & Preference Not comparable

GPT-6 Sol: 72.3 (#15), Qwen3.5-9B: —

Writing & Preference benchmarks
Benchmark	GPT-6 Sol	Qwen3.5-9B
LMArena Text	1396	—
LMArena Creative Writing	1392	—
EQ-Bench Creative Writing	2125	—
LMArena Multi-Turn	1405	—

Frequently asked questions

Is GPT-6 Sol better than Qwen3.5-9B?

Which is cheaper, GPT-6 Sol 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-6 Sol lists at $2 and $10.

Is GPT-6 Sol or Qwen3.5-9B better for coding?

GPT-6 Sol scores higher on coding benchmarks: 59.6 versus 35.3 in the Noometry coding category.

Which has the bigger context window?

GPT-6 Sol does, with 1.05M tokens against 262K.

How many benchmarks do GPT-6 Sol and Qwen3.5-9B share?

0 benchmarks have published results for both models. GPT-6 Sol has 22 scored results on Noometry and Qwen3.5-9B has 10.