Model comparison

Llama 3.2 1B vs Qwen3.6 Flash

Qwen3.6 Flash is the stronger model overall, scoring 38.8 to 20.1 on the Noometry Index. Llama 3.2 1B costs 6.0× less per token, which makes it the better buy when Qwen3.6 Flash's lead doesn't matter for your workload.

Last verified . 4 shared benchmarks.

Llama 3.2 1B Meta

20.1

Rank #354 Confirmed

Qwen3.6 Flash Alibaba (Qwen)

38.8

Rank #182 Confirmed

Summary

  • They share 4 benchmarks with published results for both. Llama 3.2 1B scores higher in 0 categories and Qwen3.6 Flash in 3 categories; 3 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where Qwen3.6 Flash leads 42.1 to 7.2.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 0.6% for Llama 3.2 1B and 84.4% for Qwen3.6 Flash.
  • Llama 3.2 1B is cheaper at $0.027 / $0.20 per million input/output tokens, against $0.19 / $1.13 for Qwen3.6 Flash.
  • Qwen3.6 Flash accepts more context: 1M tokens versus 60K.
  • Llama 3.2 1B has downloadable open weights; the other is API-only.

Side by side

Llama 3.2 1B and Qwen3.6 Flash specifications
Llama 3.2 1BQwen3.6 Flash
ProviderMetaAlibaba (Qwen)
Noometry Index20.138.8
Released2024-09-242026-04-27
WeightsOpenProprietary
Context window60K1M
Max output54K66K
Input $ / M tokens$0.027$0.19
Output $ / M tokens$0.20$1.13
Results tracked2213

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Category by category

Coding Not comparable

Llama 3.2 1B: 21.1 (#338), Qwen3.6 Flash: —

Coding benchmarks
BenchmarkLlama 3.2 1BQwen3.6 Flash
BigCodeBench Instruct8.2%—
LMArena Coding1070—
BigCodeBench Complete11.3%—
ALE-Bench—326.4

Agentic & Tool Use Not comparable

Llama 3.2 1B: 14.6 (#150), Qwen3.6 Flash: —

Agentic & Tool Use benchmarks
BenchmarkLlama 3.2 1BQwen3.6 Flash
Berkeley Function Calling Leaderboard10.8%—
BALROG6.6%—

Reasoning Qwen3.6 Flash leads

Llama 3.2 1B: 16.2 (#308), Qwen3.6 Flash: 29.0 (#96)

Reasoning benchmarks
BenchmarkLlama 3.2 1BQwen3.6 Flash
Chess Puzzles0%20%
Epoch Capabilities Index101.99143.26
SimpleBench—35.2%
LMArena Hard Prompts1044—
Mystery Game Puzzles—18%
DTBench—77.1%
LMCA—31%

Math Qwen3.6 Flash leads

Llama 3.2 1B: 10.4 (#313), Qwen3.6 Flash: 39.0 (#117)

Math benchmarks
BenchmarkLlama 3.2 1BQwen3.6 Flash
OTIS Mock AIME 2024-20250.6%84.4%
FrontierMath (Tiers 1-3)—22.5%
LMArena Math1086—
FrontierMath (Feb 2025 set)—10.3%
FrontierMath Tier 4 (v1)—0%

Knowledge Qwen3.6 Flash leads

Llama 3.2 1B: 7.2 (#312), Qwen3.6 Flash: 42.1 (#100)

Knowledge benchmarks
BenchmarkLlama 3.2 1BQwen3.6 Flash
GPQA Diamond23.9%83.3%
SimpleQA Verified—15.9%
LMArena Expert1007—

Multilingual Not comparable

Llama 3.2 1B: 23.8 (#292), Qwen3.6 Flash: —

Multilingual benchmarks
BenchmarkLlama 3.2 1BQwen3.6 Flash
LMArena Non-English973—
LMArena Chinese959—
LMArena German1014—
LMArena Russian941—

Instruction Following Not comparable

Llama 3.2 1B: 52.4 (#290), Qwen3.6 Flash: —

Instruction Following benchmarks
BenchmarkLlama 3.2 1BQwen3.6 Flash
LMArena Instruction Following1031—

Long Context Not comparable

Llama 3.2 1B: 31.9 (#274), Qwen3.6 Flash: —

Long Context benchmarks
BenchmarkLlama 3.2 1BQwen3.6 Flash
LMArena Longer Query1050—

Writing & Preference Not comparable

Llama 3.2 1B: 21.3 (#310), Qwen3.6 Flash: —

Writing & Preference benchmarks
BenchmarkLlama 3.2 1BQwen3.6 Flash
LMArena Text1055—
LMArena Creative Writing1033—
EQ-Bench Creative Writing200—
LMArena Multi-Turn1030—

Frequently asked questions

Is Llama 3.2 1B better than Qwen3.6 Flash?

Qwen3.6 Flash is the stronger model overall, scoring 38.8 to 20.1 on the Noometry Index. Llama 3.2 1B costs 6.0× less per token, which makes it the better buy when Qwen3.6 Flash's lead doesn't matter for your workload.

Which is cheaper, Llama 3.2 1B or Qwen3.6 Flash?

Llama 3.2 1B is cheaper. It lists at $0.027 per million input tokens and $0.20 per million output tokens; Qwen3.6 Flash lists at $0.19 and $1.13.

Which has the bigger context window?

Qwen3.6 Flash does, with 1M tokens against 60K.

How many benchmarks do Llama 3.2 1B and Qwen3.6 Flash share?

4 benchmarks have published results for both models. Llama 3.2 1B has 22 scored results on Noometry and Qwen3.6 Flash has 13.

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