Model comparison

GPT-5.6 Sol vs Qwen3-1.7B

GPT-5.6 Sol is the stronger model overall, scoring 65.0 to 26.6 on the Noometry Index.

Last verified October 12, 2026. 3 shared benchmarks.

GPT-5.6 Sol OpenAI

65.0

Rank #7 Confirmed

Qwen3-1.7B

Alibaba (Qwen)

26.6

Rank #336 Reported

Summary

They share 3 benchmarks with published results for both. GPT-5.6 Sol scores higher in 4 categories and Qwen3-1.7B in 0 categories; 4 gaps are clear of the uncertainty.
The widest gap is in math, where GPT-5.6 Sol leads 85.6 to 16.3.
The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 100% for GPT-5.6 Sol and 8.1% for Qwen3-1.7B.
Qwen3-1.7B has downloadable open weights; the other is API-only.

Side by side

GPT-5.6 Sol and Qwen3-1.7B specifications
	GPT-5.6 Sol	Qwen3-1.7B
Provider	OpenAI	Alibaba (Qwen)
Noometry Index	65.0	26.6
Released	2026-07-09	2025-04-29
Weights	Proprietary	Open
Context window	1.05M	—
Max output	128K	—
Input $ / M tokens	$4	—
Output $ / M tokens	$20	—
Results tracked	65	4

Sponsored placements are available on pages like this one. Advertise on Noometry

Category by category

Coding Not comparable

GPT-5.6 Sol: 65.1 (#7), Qwen3-1.7B: —

Coding benchmarks
Benchmark	GPT-5.6 Sol	Qwen3-1.7B
DeepSWE	72.7%	—
FrontierCode	47.5%	—
CursorBench	41.7%	—
LMArena WebDev	1618	—
FrontierSWE	32.2%	—
SciCode	57.1%	—
GSO	76.5%	—
WeirdML	89.4%	—
LMArena Coding	1498	—
MirrorCode	20%	—
ALE-Bench	2,177	—

Agentic & Tool Use GPT-5.6 Sol leads

GPT-5.6 Sol: 50.3 (#7), Qwen3-1.7B: 24.7 (#115)

Agentic & Tool Use benchmarks
Benchmark	GPT-5.6 Sol	Qwen3-1.7B
APEX-Agents	51.4%	—
Berkeley Function Calling Leaderboard	—	28.4%
OSWorld 2.0	27.3%	—
τ²-bench Banking	46.9%	—
PostTrainBench	36.2%	—
BALROG	60%	—
GBAEval	52.6%	—
GDP.pdf	30.7%	—
LMArena Search	1257	—
Vending-Bench 2	9,619	—

Reasoning GPT-5.6 Sol leads

GPT-5.6 Sol: 74.8 (#8), Qwen3-1.7B: 19.2 (#267)

Reasoning benchmarks
Benchmark	GPT-5.6 Sol	Qwen3-1.7B
Chess Puzzles	64%	0%
ARC-AGI-2	92.5%	—
SimpleBench	71.7%	—
Kagi LLM Benchmark	67%	—
NYT Connections (extended)	93.8%	—
ARC-AGI-1	97.5%	—
CritPt	32.3%	—
EnigmaEval	37.1%	—
EBR-Bench	44.8%	—
LMArena Hard Prompts	1484	—
Mystery Game Puzzles	58%	—
DTBench	96%	—
LMCA	59.2%	—
Surface Evolver Bench	93.1%	—
Bench to the Future 3	0.14	—
Epoch Capabilities Index	161.66	—

Math GPT-5.6 Sol leads

GPT-5.6 Sol: 85.6 (#9), Qwen3-1.7B: 16.3 (#294)

Math benchmarks
Benchmark	GPT-5.6 Sol	Qwen3-1.7B
OTIS Mock AIME 2024-2025	100%	8.1%
FrontierMath (Tiers 1-3)	89.1%	—
FrontierMath Tier 4	82.9%	—
ProofBench	83%	—
LMArena Math	1474	—
FrontierMath Erdős	0%	—

Knowledge GPT-5.6 Sol leads

GPT-5.6 Sol: 64.3 (#18), Qwen3-1.7B: 19.6 (#278)

Knowledge benchmarks
Benchmark	GPT-5.6 Sol	Qwen3-1.7B
GPQA Diamond	93.5%	38%
SimpleQA Verified	69.7%	—
Vectara Hallucination Rate	12.4%	—
LMArena Expert	1516	—

Multimodal Not comparable

GPT-5.6 Sol: 48.6 (#9), Qwen3-1.7B: —

Multimodal benchmarks
Benchmark	GPT-5.6 Sol	Qwen3-1.7B
LMArena Vision	1281	—
Blueprint-Bench 2	33.6%	—
Furniture Assembly	56.7%	—
LMArena Document	1483	—

Multilingual Not comparable

GPT-5.6 Sol: 55.3 (#32), Qwen3-1.7B: —

Multilingual benchmarks
Benchmark	GPT-5.6 Sol	Qwen3-1.7B
LMArena Non-English	1452	—
LMArena Chinese	1527	—
LMArena French	1477	—
LMArena German	1476	—
LMArena Japanese	1471	—
LMArena Korean	1442	—
LMArena Russian	1468	—
LMArena Spanish	1441	—

Instruction Following Not comparable

GPT-5.6 Sol: 77.7 (#16), Qwen3-1.7B: —

Instruction Following benchmarks
Benchmark	GPT-5.6 Sol	Qwen3-1.7B
LMArena Instruction Following	1482	—

Long Context Not comparable

GPT-5.6 Sol: 45.4 (#42), Qwen3-1.7B: —

Long Context benchmarks
Benchmark	GPT-5.6 Sol	Qwen3-1.7B
LMArena Longer Query	1480	—

Writing & Preference Not comparable

GPT-5.6 Sol: 73.3 (#12), Qwen3-1.7B: —

Writing & Preference benchmarks
Benchmark	GPT-5.6 Sol	Qwen3-1.7B
LMArena Text	1457	—
LMArena Creative Writing	1448	—
EQ-Bench Creative Writing	1972	—
EQ-Bench 4	1250	—
LMArena Multi-Turn	1460	—

Frequently asked questions

Is GPT-5.6 Sol better than Qwen3-1.7B?