Model comparison
Laguna M.1 vs Qwen3 32B
Qwen3 32B is the stronger model overall, scoring 38.8 to 31.9 on the Noometry Index.
Last verified . 0 shared benchmarks.
Poolside
Alibaba (Qwen)Summary
- The widest gap is in math, where Qwen3 32B leads 37.9 to 20.3.
- Laguna M.1 accepts more context: 262K tokens versus 131K.
Side by side
| Laguna M.1 | Qwen3 32B | |
|---|---|---|
| Provider | Poolside | Alibaba (Qwen) |
| Noometry Index | 31.9 | 38.8 |
| Released | 2026-04-28 | 2025-04 |
| Weights | Open | Open |
| Context window | 262K | 131K |
| Max output | 33K | 16K |
| Input $ / M tokens | — | $0.70 |
| Output $ / M tokens | — | $2.80 |
| Results tracked | 3 | 26 |
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Category by category
Coding Too close to call
Laguna M.1: 36.4 (#195), Qwen3 32B: 37.3 (#184)
| Benchmark | Laguna M.1 | Qwen3 32B |
|---|---|---|
| Aider Polyglot | — | 40% |
| LMArena WebDev | 1348 | — |
| SciCode | — | 35.4% |
| LMArena Coding | — | 1358 |
Agentic & Tool Use Not comparable
Laguna M.1: —, Qwen3 32B: 32.3 (#58)
| Benchmark | Laguna M.1 | Qwen3 32B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 48.7% |
Reasoning Laguna M.1 leads
Laguna M.1: 21.9 (#187), Qwen3 32B: 19.6 (#233)
| Benchmark | Laguna M.1 | Qwen3 32B |
|---|---|---|
| Kagi LLM Benchmark | — | 54.9% |
| CritPt | — | 0.3% |
| Chess Puzzles | — | 5% |
| LMArena Hard Prompts | — | 1335 |
| DTBench | — | 67.5% |
| LMCA | — | 17.3% |
| Surface Evolver Bench | 15.6% | — |
| Epoch Capabilities Index | — | 138.51 |
Math Qwen3 32B leads
Laguna M.1: 20.3 (#276), Qwen3 32B: 37.9 (#89)
| Benchmark | Laguna M.1 | Qwen3 32B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 66.9% |
| ProofBench | 0% | — |
| LMArena Math | — | 1399 |
Knowledge Not comparable
Laguna M.1: —, Qwen3 32B: 40.0 (#112)
| Benchmark | Laguna M.1 | Qwen3 32B |
|---|---|---|
| GPQA Diamond | — | 65.7% |
| Vectara Hallucination Rate | — | 5.9% |
| LMArena Expert | — | 1362 |
Multilingual Not comparable
Laguna M.1: —, Qwen3 32B: 45.8 (#162)
| Benchmark | Laguna M.1 | Qwen3 32B |
|---|---|---|
| LMArena Non-English | — | 1317 |
| LMArena Chinese | — | 1357 |
| LMArena German | — | 1341 |
| LMArena Russian | — | 1311 |
Instruction Following Not comparable
Laguna M.1: —, Qwen3 32B: 69.1 (#174)
| Benchmark | Laguna M.1 | Qwen3 32B |
|---|---|---|
| LMArena Instruction Following | — | 1305 |
Long Context Not comparable
Laguna M.1: —, Qwen3 32B: 43.7 (#83)
| Benchmark | Laguna M.1 | Qwen3 32B |
|---|---|---|
| Fiction.LiveBench | — | 74.2% |
| LMArena Longer Query | — | 1327 |
Writing & Preference Not comparable
Laguna M.1: —, Qwen3 32B: 53.1 (#158)
| Benchmark | Laguna M.1 | Qwen3 32B |
|---|---|---|
| LMArena Text | — | 1340 |
| LMArena Creative Writing | — | 1297 |
| LMArena Multi-Turn | — | 1331 |
Frequently asked questions
Is Laguna M.1 better than Qwen3 32B?
Qwen3 32B is the stronger model overall, scoring 38.8 to 31.9 on the Noometry Index.
Is Laguna M.1 or Qwen3 32B better for coding?
They score almost the same on coding (36.4 vs 37.3); test both on your own repository before choosing.
Which has the bigger context window?
Laguna M.1 does, with 262K tokens against 131K.
How many benchmarks do Laguna M.1 and Qwen3 32B share?
0 benchmarks have published results for both models. Laguna M.1 has 3 scored results on Noometry and Qwen3 32B has 26.