Model comparison
Llama 3.2 1B vs Qwen3.6 Plus
Qwen3.6 Plus is the stronger model overall, scoring 47.5 to 20.1 on the Noometry Index. Llama 3.2 1B costs 16× less per token, which makes it the better buy when Qwen3.6 Plus's lead doesn't matter for your workload.
Last verified . 17 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- They share 17 benchmarks with published results for both. Llama 3.2 1B scores higher in 0 categories and Qwen3.6 Plus in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3.6 Plus leads 56.1 to 7.2.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 0.6% for Llama 3.2 1B and 93.3% for Qwen3.6 Plus.
- Llama 3.2 1B is cheaper at $0.027 / $0.20 per million input/output tokens, against $0.50 / $3 for Qwen3.6 Plus.
- Qwen3.6 Plus 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 | Qwen3.6 Plus | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 20.1 | 47.5 |
| Released | 2024-09-24 | 2026-03-31 |
| Weights | Open | Proprietary |
| Context window | 60K | 1M |
| Max output | 54K | 66K |
| Input $ / M tokens | $0.027 | $0.50 |
| Output $ / M tokens | $0.20 | $3 |
| Results tracked | 22 | 37 |
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Category by category
Coding Qwen3.6 Plus leads
Llama 3.2 1B: 21.1 (#338), Qwen3.6 Plus: 40.8 (#130)
| Benchmark | Llama 3.2 1B | Qwen3.6 Plus |
|---|---|---|
| LMArena Coding | 1070 | 1467 |
| SWE-bench Verified | — | 57.9% |
| LMArena WebDev | — | 1461 |
| SciCode | — | 40.7% |
| BigCodeBench Instruct | 8.2% | — |
| BigCodeBench Complete | 11.3% | — |
| ALE-Bench | — | 670.15 |
Agentic & Tool Use Not comparable
Llama 3.2 1B: 14.6 (#150), Qwen3.6 Plus: —
| Benchmark | Llama 3.2 1B | Qwen3.6 Plus |
|---|---|---|
| Berkeley Function Calling Leaderboard | 10.8% | — |
| BALROG | 6.6% | — |
| Vending-Bench 2 | — | 5,115 |
Reasoning Qwen3.6 Plus leads
Llama 3.2 1B: 16.2 (#308), Qwen3.6 Plus: 29.3 (#93)
| Benchmark | Llama 3.2 1B | Qwen3.6 Plus |
|---|---|---|
| Chess Puzzles | 0% | 17% |
| LMArena Hard Prompts | 1044 | 1449 |
| Epoch Capabilities Index | 101.99 | 147.65 |
| NYT Connections (extended) | — | 60.3% |
| CritPt | — | 2.9% |
| Thematic Generalization | — | 59.5% |
| Mystery Game Puzzles | — | 12% |
| DTBench | — | 81.9% |
| LMCA | — | 33.1% |
Math Qwen3.6 Plus leads
Llama 3.2 1B: 10.4 (#313), Qwen3.6 Plus: 51.8 (#54)
| Benchmark | Llama 3.2 1B | Qwen3.6 Plus |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 0.6% | 93.3% |
| LMArena Math | 1086 | 1450 |
| FrontierMath (Tiers 1-3) | — | 38.2% |
| FrontierMath (Feb 2025 set) | — | 26.2% |
| FrontierMath Tier 4 (v1) | — | 8.3% |
Knowledge Qwen3.6 Plus leads
Llama 3.2 1B: 7.2 (#312), Qwen3.6 Plus: 56.1 (#45)
| Benchmark | Llama 3.2 1B | Qwen3.6 Plus |
|---|---|---|
| GPQA Diamond | 23.9% | 88.4% |
| LMArena Expert | 1007 | 1454 |
| SimpleQA Verified | — | 44.1% |
Multilingual Qwen3.6 Plus leads
Llama 3.2 1B: 23.8 (#292), Qwen3.6 Plus: 53.3 (#70)
| Benchmark | Llama 3.2 1B | Qwen3.6 Plus |
|---|---|---|
| LMArena Non-English | 973 | 1424 |
| LMArena Chinese | 959 | 1477 |
| LMArena German | 1014 | 1452 |
| LMArena Russian | 941 | 1434 |
| LMArena French | — | 1455 |
| LMArena Japanese | — | 1389 |
| LMArena Korean | — | 1379 |
| LMArena Spanish | — | 1432 |
Instruction Following Qwen3.6 Plus leads
Llama 3.2 1B: 52.4 (#290), Qwen3.6 Plus: 75.0 (#74)
| Benchmark | Llama 3.2 1B | Qwen3.6 Plus |
|---|---|---|
| LMArena Instruction Following | 1031 | 1425 |
Long Context Qwen3.6 Plus leads
Llama 3.2 1B: 31.9 (#274), Qwen3.6 Plus: 45.2 (#49)
| Benchmark | Llama 3.2 1B | Qwen3.6 Plus |
|---|---|---|
| LMArena Longer Query | 1050 | 1439 |
| CL-bench | — | 20.3% |
Writing & Preference Qwen3.6 Plus leads
Llama 3.2 1B: 21.3 (#310), Qwen3.6 Plus: 62.2 (#82)
| Benchmark | Llama 3.2 1B | Qwen3.6 Plus |
|---|---|---|
| LMArena Text | 1055 | 1437 |
| LMArena Creative Writing | 1033 | 1404 |
| LMArena Multi-Turn | 1030 | 1438 |
| EQ-Bench Creative Writing | 200 | — |
Frequently asked questions
Is Llama 3.2 1B better than Qwen3.6 Plus?
Qwen3.6 Plus is the stronger model overall, scoring 47.5 to 20.1 on the Noometry Index. Llama 3.2 1B costs 16× less per token, which makes it the better buy when Qwen3.6 Plus's lead doesn't matter for your workload.
Which is cheaper, Llama 3.2 1B or Qwen3.6 Plus?
Llama 3.2 1B is cheaper. It lists at $0.027 per million input tokens and $0.20 per million output tokens; Qwen3.6 Plus lists at $0.50 and $3.
Is Llama 3.2 1B or Qwen3.6 Plus better for coding?
Qwen3.6 Plus scores higher on coding benchmarks: 40.8 versus 21.1 in the Noometry coding category.
Which has the bigger context window?
Qwen3.6 Plus does, with 1M tokens against 60K.
How many benchmarks do Llama 3.2 1B and Qwen3.6 Plus share?
17 benchmarks have published results for both models. Llama 3.2 1B has 22 scored results on Noometry and Qwen3.6 Plus has 37.