Model comparison

Llama 3.2 3B vs Qwen3.5 27B

Qwen3.5 27B is the stronger model overall, scoring 41.9 to 28.9 on the Noometry Index. Llama 3.2 3B costs 6.9× less per token, which makes it the better buy when Qwen3.5 27B's lead doesn't matter for your workload.

Last verified October 12, 2026. 13 shared benchmarks.

Llama 3.2 3B

Summary

They share 13 benchmarks with published results for both. Llama 3.2 3B scores higher in 0 categories and Qwen3.5 27B in 8 categories; 8 gaps are clear of the uncertainty.
The widest gap is in writing & preference, where Qwen3.5 27B leads 59.3 to 24.7.
Llama 3.2 3B is cheaper at $0.05 / $0.33 per million input/output tokens, against $0.30 / $2.40 for Qwen3.5 27B.
Qwen3.5 27B accepts more context: 262K tokens versus 131K.

Side by side

Llama 3.2 3B and Qwen3.5 27B specifications
	Llama 3.2 3B	Qwen3.5 27B
Provider	Meta	Alibaba (Qwen)
Noometry Index	28.9	41.9
Released	2024-09-24	2026-02-23
Weights	Open	Open
Context window	131K	262K
Max output	118K	66K
Input $ / M tokens	$0.05	$0.30
Output $ / M tokens	$0.33	$2.40
Results tracked	18	28

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Category by category

Coding Qwen3.5 27B leads

Llama 3.2 3B: 27.6 (#319), Qwen3.5 27B: 38.9 (#168)

Coding benchmarks
Benchmark	Llama 3.2 3B	Qwen3.5 27B
LMArena Coding	1098	1427
LMArena WebDev	—	1358
WeirdML	—	39.5%
BigCodeBench Instruct	23.4%	—
BigCodeBench Complete	28.3%	—
ALE-Bench	—	349.45

Agentic & Tool Use Not comparable

Llama 3.2 3B: 20.1 (#143), Qwen3.5 27B: —

Agentic & Tool Use benchmarks
Benchmark	Llama 3.2 3B	Qwen3.5 27B
Berkeley Function Calling Leaderboard	21.9%	—
BALROG	10.1%	—
Vending-Bench 2	—	201.98

Reasoning Qwen3.5 27B leads

Llama 3.2 3B: 21.0 (#228), Qwen3.5 27B: 27.5 (#117)

Reasoning benchmarks
Benchmark	Llama 3.2 3B	Qwen3.5 27B
LMArena Hard Prompts	1095	1414
NYT Connections (extended)	—	47.9%
Thematic Generalization	—	45.5%
DTBench	—	82.4%
LMCA	—	34%

Math Qwen3.5 27B leads

Llama 3.2 3B: 32.4 (#214), Qwen3.5 27B: 38.8 (#127)

Math benchmarks
Benchmark	Llama 3.2 3B	Qwen3.5 27B
LMArena Math	1126	1429
MathArena Final-Answer Competitions	—	56.7%

Knowledge Qwen3.5 27B leads

Llama 3.2 3B: 29.7 (#235), Qwen3.5 27B: 38.0 (#150)

Knowledge benchmarks
Benchmark	Llama 3.2 3B	Qwen3.5 27B
LMArena Expert	1090	1428
Vectara Hallucination Rate	—	12.1%

Multimodal Not comparable

Llama 3.2 3B: —, Qwen3.5 27B: 39.4 (#59)

Multimodal benchmarks
Benchmark	Llama 3.2 3B	Qwen3.5 27B
LMArena Vision	—	1241

Multilingual Qwen3.5 27B leads

Llama 3.2 3B: 26.2 (#281), Qwen3.5 27B: 50.8 (#115)

Multilingual benchmarks
Benchmark	Llama 3.2 3B	Qwen3.5 27B
LMArena Non-English	1019	1390
LMArena Chinese	1017	1478
LMArena German	1056	1393
LMArena Russian	949	1390
LMArena French	—	1410
LMArena Japanese	—	1345
LMArena Korean	—	1358
LMArena Spanish	—	1407

Instruction Following Qwen3.5 27B leads

Llama 3.2 3B: 56.0 (#275), Qwen3.5 27B: 73.5 (#119)

Instruction Following benchmarks
Benchmark	Llama 3.2 3B	Qwen3.5 27B
LMArena Instruction Following	1089	1393

Long Context Qwen3.5 27B leads

Llama 3.2 3B: 33.4 (#261), Qwen3.5 27B: 43.1 (#106)

Long Context benchmarks
Benchmark	Llama 3.2 3B	Qwen3.5 27B
LMArena Longer Query	1100	1413

Writing & Preference Qwen3.5 27B leads

Llama 3.2 3B: 24.7 (#307), Qwen3.5 27B: 59.3 (#111)

Writing & Preference benchmarks
Benchmark	Llama 3.2 3B	Qwen3.5 27B
LMArena Text	1110	1409
LMArena Creative Writing	1094	1362
LMArena Multi-Turn	1105	1410
EQ-Bench Creative Writing	595	—

Frequently asked questions

Is Llama 3.2 3B better than Qwen3.5 27B?

Which is cheaper, Llama 3.2 3B or Qwen3.5 27B?

Llama 3.2 3B is cheaper. It lists at $0.05 per million input tokens and $0.33 per million output tokens; Qwen3.5 27B lists at $0.30 and $2.40.

Is Llama 3.2 3B or Qwen3.5 27B better for coding?

Qwen3.5 27B scores higher on coding benchmarks: 38.9 versus 27.6 in the Noometry coding category.

Which has the bigger context window?

Qwen3.5 27B does, with 262K tokens against 131K.

How many benchmarks do Llama 3.2 3B and Qwen3.5 27B share?

13 benchmarks have published results for both models. Llama 3.2 3B has 18 scored results on Noometry and Qwen3.5 27B has 28.