Model comparison

Llama 3.2 1B vs Qwen3.5-9B

Qwen3.5-9B is the stronger model overall, scoring 33.3 to 19.9 on the Noometry Index. Llama 3.2 1B costs 1.6× 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. 4 shared benchmarks.

Llama 3.2 1B

Summary

They share 4 benchmarks with published results for both. Llama 3.2 1B scores higher in 1 category and Qwen3.5-9B in 4 categories; 4 gaps are clear of the uncertainty.
The widest gap is in knowledge, where Qwen3.5-9B leads 46.0 to 7.2.
The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 0.6% for Llama 3.2 1B and 61.7% for Qwen3.5-9B.
Llama 3.2 1B is cheaper at $0.027 / $0.20 per million input/output tokens, against $0.10 / $0.15 for Qwen3.5-9B.
Qwen3.5-9B accepts more context: 262K tokens versus 60K.

Side by side

Llama 3.2 1B and Qwen3.5-9B specifications
	Llama 3.2 1B	Qwen3.5-9B
Provider	Meta	Alibaba (Qwen)
Noometry Index	19.9	33.3
Released	2024-09-24	2026-02-23
Weights	Open	Open
Context window	60K	262K
Max output	54K	66K
Input $ / M tokens	$0.027	$0.10
Output $ / M tokens	$0.20	$0.15
Results tracked	22	10

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Category by category

Coding Qwen3.5-9B leads

Llama 3.2 1B: 20.6 (#333), Qwen3.5-9B: 35.3 (#213)

Coding benchmarks
Benchmark	Llama 3.2 1B	Qwen3.5-9B
SciCode	—	27.5%
BigCodeBench Instruct	8.2%	—
LMArena Coding	1071	—
BigCodeBench Complete	11.3%	—

Agentic & Tool Use Too close to call

Llama 3.2 1B: 14.5 (#142), Qwen3.5-9B: 14.4 (#143)

Agentic & Tool Use benchmarks
Benchmark	Llama 3.2 1B	Qwen3.5-9B
Terminal-Bench	—	9.2%
Berkeley Function Calling Leaderboard	10.8%	—
BALROG	6.6%	—

Reasoning Qwen3.5-9B leads

Llama 3.2 1B: 15.6 (#304), Qwen3.5-9B: 22.5 (#178)

Reasoning benchmarks
Benchmark	Llama 3.2 1B	Qwen3.5-9B
Chess Puzzles	0%	12%
Epoch Capabilities Index	101.95	139.45
CritPt	—	0.3%
LMArena Hard Prompts	1044	—
DTBench	—	71.2%
LMCA	—	24.5%

Math Qwen3.5-9B leads

Llama 3.2 1B: 9.7 (#308), Qwen3.5-9B: 33.5 (#174)

Math benchmarks
Benchmark	Llama 3.2 1B	Qwen3.5-9B
OTIS Mock AIME 2024-2025	0.6%	61.7%
MathArena Final-Answer Competitions	—	48.5%
LMArena Math	1086	—

Knowledge Qwen3.5-9B leads

Llama 3.2 1B: 7.2 (#307), Qwen3.5-9B: 46.0 (#77)

Knowledge benchmarks
Benchmark	Llama 3.2 1B	Qwen3.5-9B
GPQA Diamond	23.9%	79%
LMArena Expert	1007	—

Multilingual Not comparable

Llama 3.2 1B: 23.9 (#287), Qwen3.5-9B: —

Multilingual benchmarks
Benchmark	Llama 3.2 1B	Qwen3.5-9B
LMArena Non-English	973	—
LMArena Chinese	958	—
LMArena German	1014	—
LMArena Russian	941	—

Instruction Following Not comparable

Llama 3.2 1B: 52.6 (#285), Qwen3.5-9B: —

Instruction Following benchmarks
Benchmark	Llama 3.2 1B	Qwen3.5-9B
LMArena Instruction Following	1031	—

Long Context Not comparable

Llama 3.2 1B: 31.9 (#269), Qwen3.5-9B: —

Long Context benchmarks
Benchmark	Llama 3.2 1B	Qwen3.5-9B
LMArena Longer Query	1050	—

Writing & Preference Not comparable

Llama 3.2 1B: 21.4 (#305), Qwen3.5-9B: —

Writing & Preference benchmarks
Benchmark	Llama 3.2 1B	Qwen3.5-9B
LMArena Text	1055	—
LMArena Creative Writing	1033	—
EQ-Bench Creative Writing	200	—
LMArena Multi-Turn	1030	—

Frequently asked questions

Is Llama 3.2 1B better than Qwen3.5-9B?

Which is cheaper, Llama 3.2 1B or Qwen3.5-9B?

Llama 3.2 1B is cheaper. It lists at $0.027 per million input tokens and $0.20 per million output tokens; Qwen3.5-9B lists at $0.10 and $0.15.

Is Llama 3.2 1B or Qwen3.5-9B better for coding?

Qwen3.5-9B scores higher on coding benchmarks: 35.3 versus 20.6 in the Noometry coding category.

Which has the bigger context window?

Qwen3.5-9B does, with 262K tokens against 60K.

How many benchmarks do Llama 3.2 1B and Qwen3.5-9B share?

4 benchmarks have published results for both models. Llama 3.2 1B has 22 scored results on Noometry and Qwen3.5-9B has 10.