Model comparison
Qwen2.5-Coder-32B vs Qwen3-1.7B
Qwen2.5-Coder-32B is the stronger model overall, scoring 32.9 to 26.2 on the Noometry Index.
Last verified . 0 shared benchmarks.
Alibaba (Qwen)Summary
- The widest gap is in math, where Qwen2.5-Coder-32B leads 30.8 to 15.4.
Side by side
| Qwen2.5-Coder-32B | Qwen3-1.7B | |
|---|---|---|
| Provider | Alibaba (Qwen) | Alibaba (Qwen) |
| Noometry Index | 32.9 | 26.2 |
| Released | 2024-09-18 | 2025-04-29 |
| Weights | Open | Open |
| Context window | 33K | — |
| Max output | 29K | — |
| Input $ / M tokens | $0.66 | — |
| Output $ / M tokens | $1 | — |
| Results tracked | 31 | 4 |
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Category by category
Coding Not comparable
Qwen2.5-Coder-32B: 22.4 (#328), Qwen3-1.7B: —
| Benchmark | Qwen2.5-Coder-32B | Qwen3-1.7B |
|---|---|---|
| SWE-bench Verified (bash only) | 9% | — |
| Aider Polyglot | 16.4% | — |
| BigCodeBench Instruct | 49% | — |
| LiveBench Coding | 56.9% | — |
| LMArena Coding | 1276 | — |
| BigCodeBench Complete | 58% | — |
| HumanEval+ | 87.2% | — |
| MBPP+ | 77% | — |
Agentic & Tool Use Not comparable
Qwen2.5-Coder-32B: —, Qwen3-1.7B: 24.5 (#108)
| Benchmark | Qwen2.5-Coder-32B | Qwen3-1.7B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 28.4% |
Reasoning Qwen2.5-Coder-32B leads
Qwen2.5-Coder-32B: 20.4 (#220), Qwen3-1.7B: 18.5 (#263)
| Benchmark | Qwen2.5-Coder-32B | Qwen3-1.7B |
|---|---|---|
| Chess Puzzles | — | 0% |
| LiveBench Reasoning | 42.1% | — |
| LMArena Hard Prompts | 1251 | — |
| LiveBench Data Analysis | 49.9% | — |
| Epoch Capabilities Index | 119.41 | — |
| HellaSwag | 83% | — |
| LiveBench | 46.2% | — |
| WinoGrande | 80.8% | — |
Math Qwen2.5-Coder-32B leads
Qwen2.5-Coder-32B: 30.8 (#203), Qwen3-1.7B: 15.4 (#288)
| Benchmark | Qwen2.5-Coder-32B | Qwen3-1.7B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 8.1% |
| LiveBench Math | 46.6% | — |
| LMArena Math | 1251 | — |
| GSM8K | 93% | — |
Knowledge Qwen2.5-Coder-32B leads
Qwen2.5-Coder-32B: 32.9 (#200), Qwen3-1.7B: 19.6 (#273)
| Benchmark | Qwen2.5-Coder-32B | Qwen3-1.7B |
|---|---|---|
| GPQA Diamond | — | 38% |
| LMArena Expert | 1221 | — |
| ARC (AI2) Challenge | 70.5% | — |
| MMLU | 79.1% | — |
Multilingual Not comparable
Qwen2.5-Coder-32B: 38.0 (#230), Qwen3-1.7B: —
| Benchmark | Qwen2.5-Coder-32B | Qwen3-1.7B |
|---|---|---|
| LMArena Non-English | 1205 | — |
| LMArena Chinese | 1222 | — |
| LMArena Russian | 1228 | — |
Instruction Following Not comparable
Qwen2.5-Coder-32B: 61.6 (#240), Qwen3-1.7B: —
| Benchmark | Qwen2.5-Coder-32B | Qwen3-1.7B |
|---|---|---|
| LiveBench Instruction Following | 58.7% | — |
| LMArena Instruction Following | 1223 | — |
Long Context Not comparable
Qwen2.5-Coder-32B: 37.9 (#204), Qwen3-1.7B: —
| Benchmark | Qwen2.5-Coder-32B | Qwen3-1.7B |
|---|---|---|
| LMArena Longer Query | 1251 | — |
Writing & Preference Not comparable
Qwen2.5-Coder-32B: 41.8 (#235), Qwen3-1.7B: —
| Benchmark | Qwen2.5-Coder-32B | Qwen3-1.7B |
|---|---|---|
| LMArena Text | 1230 | — |
| LMArena Creative Writing | 1174 | — |
| LMArena Multi-Turn | 1222 | — |
| LiveBench Language | 23.3% | — |
Frequently asked questions
Is Qwen2.5-Coder-32B better than Qwen3-1.7B?
Qwen2.5-Coder-32B is the stronger model overall, scoring 32.9 to 26.2 on the Noometry Index.
How many benchmarks do Qwen2.5-Coder-32B and Qwen3-1.7B share?
0 benchmarks have published results for both models. Qwen2.5-Coder-32B has 31 scored results on Noometry and Qwen3-1.7B has 4.