Model comparison
Llama 3.2 1B vs Qwen3-1.7B
Qwen3-1.7B is the stronger model overall, scoring 26.6 to 20.1 on the Noometry Index.
Last verified . 4 shared benchmarks.
Summary
- They share 4 benchmarks with published results for both. Llama 3.2 1B scores higher in 0 categories and Qwen3-1.7B in 4 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3-1.7B leads 19.6 to 7.2.
- The biggest single-benchmark swing is Berkeley Function Calling Leaderboard: 10.8% for Llama 3.2 1B and 28.4% for Qwen3-1.7B.
Side by side
| Llama 3.2 1B | Qwen3-1.7B | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 20.1 | 26.6 |
| Released | 2024-09-24 | 2025-04-29 |
| Weights | Open | Open |
| Context window | 60K | — |
| Max output | 54K | — |
| Input $ / M tokens | $0.027 | — |
| Output $ / M tokens | $0.20 | — |
| Results tracked | 22 | 4 |
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Category by category
Coding Not comparable
Llama 3.2 1B: 21.1 (#338), Qwen3-1.7B: —
| Benchmark | Llama 3.2 1B | Qwen3-1.7B |
|---|---|---|
| BigCodeBench Instruct | 8.2% | — |
| LMArena Coding | 1070 | — |
| BigCodeBench Complete | 11.3% | — |
Agentic & Tool Use Qwen3-1.7B leads
Llama 3.2 1B: 14.6 (#150), Qwen3-1.7B: 24.7 (#115)
| Benchmark | Llama 3.2 1B | Qwen3-1.7B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 10.8% | 28.4% |
| BALROG | 6.6% | — |
Reasoning Qwen3-1.7B leads
Llama 3.2 1B: 16.2 (#308), Qwen3-1.7B: 19.2 (#267)
| Benchmark | Llama 3.2 1B | Qwen3-1.7B |
|---|---|---|
| Chess Puzzles | 0% | 0% |
| LMArena Hard Prompts | 1044 | — |
| Epoch Capabilities Index | 101.99 | — |
Math Qwen3-1.7B leads
Llama 3.2 1B: 10.4 (#313), Qwen3-1.7B: 16.3 (#294)
| Benchmark | Llama 3.2 1B | Qwen3-1.7B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 0.6% | 8.1% |
| LMArena Math | 1086 | — |
Knowledge Qwen3-1.7B leads
Llama 3.2 1B: 7.2 (#312), Qwen3-1.7B: 19.6 (#278)
| Benchmark | Llama 3.2 1B | Qwen3-1.7B |
|---|---|---|
| GPQA Diamond | 23.9% | 38% |
| LMArena Expert | 1007 | — |
Multilingual Not comparable
Llama 3.2 1B: 23.8 (#292), Qwen3-1.7B: —
| Benchmark | Llama 3.2 1B | Qwen3-1.7B |
|---|---|---|
| LMArena Non-English | 973 | — |
| LMArena Chinese | 959 | — |
| LMArena German | 1014 | — |
| LMArena Russian | 941 | — |
Instruction Following Not comparable
Llama 3.2 1B: 52.4 (#290), Qwen3-1.7B: —
| Benchmark | Llama 3.2 1B | Qwen3-1.7B |
|---|---|---|
| LMArena Instruction Following | 1031 | — |
Long Context Not comparable
Llama 3.2 1B: 31.9 (#274), Qwen3-1.7B: —
| Benchmark | Llama 3.2 1B | Qwen3-1.7B |
|---|---|---|
| LMArena Longer Query | 1050 | — |
Writing & Preference Not comparable
Llama 3.2 1B: 21.3 (#310), Qwen3-1.7B: —
| Benchmark | Llama 3.2 1B | Qwen3-1.7B |
|---|---|---|
| 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 Qwen3-1.7B?
Qwen3-1.7B is the stronger model overall, scoring 26.6 to 20.1 on the Noometry Index.
How many benchmarks do Llama 3.2 1B and Qwen3-1.7B share?
4 benchmarks have published results for both models. Llama 3.2 1B has 22 scored results on Noometry and Qwen3-1.7B has 4.