Model comparison
Olmo 3 32b Think vs Qwen3 14B
Olmo 3 32b Think is the stronger model overall, scoring 38.7 to 35.5 on the Noometry Index.
Last verified . 0 shared benchmarks.
Allen Institute for AI (Ai2)
Alibaba (Qwen)Summary
- The widest gap is in reasoning, where Olmo 3 32b Think leads 25.9 to 18.5.
Side by side
| Olmo 3 32b Think | Qwen3 14B | |
|---|---|---|
| Provider | Allen Institute for AI (Ai2) | Alibaba (Qwen) |
| Noometry Index | 38.7 | 35.5 |
| Released | — | 2025-04 |
| Weights | Open | Open |
| Context window | — | 131K |
| Max output | — | 8K |
| Input $ / M tokens | — | $0.35 |
| Output $ / M tokens | — | $1.40 |
| Results tracked | 14 | 12 |
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Category by category
Coding Olmo 3 32b Think leads
Olmo 3 32b Think: 38.6 (#172), Qwen3 14B: 37.3 (#195)
| Benchmark | Olmo 3 32b Think | Qwen3 14B |
|---|---|---|
| SciCode | — | 31.6% |
| LMArena Coding | 1319 | — |
Agentic & Tool Use Not comparable
Olmo 3 32b Think: —, Qwen3 14B: 29.6 (#83)
| Benchmark | Olmo 3 32b Think | Qwen3 14B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 41% |
Reasoning Olmo 3 32b Think leads
Olmo 3 32b Think: 25.9 (#140), Qwen3 14B: 18.5 (#280)
| Benchmark | Olmo 3 32b Think | Qwen3 14B |
|---|---|---|
| Kagi LLM Benchmark | — | 49.1% |
| CritPt | — | 0% |
| Chess Puzzles | — | 4% |
| LMArena Hard Prompts | 1302 | — |
| DTBench | — | 64% |
| LMCA | — | 18.2% |
| Epoch Capabilities Index | — | 138.23 |
Math Qwen3 14B leads
Olmo 3 32b Think: 36.5 (#165), Qwen3 14B: 38.6 (#133)
| Benchmark | Olmo 3 32b Think | Qwen3 14B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 66.4% |
| LMArena Math | 1316 | — |
Knowledge Qwen3 14B leads
Olmo 3 32b Think: 35.0 (#190), Qwen3 14B: 39.3 (#134)
| Benchmark | Olmo 3 32b Think | Qwen3 14B |
|---|---|---|
| GPQA Diamond | — | 63.8% |
| Vectara Hallucination Rate | — | 5.4% |
| LMArena Expert | 1273 | — |
Multilingual Not comparable
Olmo 3 32b Think: 41.2 (#210), Qwen3 14B: —
| Benchmark | Olmo 3 32b Think | Qwen3 14B |
|---|---|---|
| LMArena Non-English | 1255 | — |
| LMArena Chinese | 1300 | — |
| LMArena French | 1291 | — |
| LMArena German | 1290 | — |
| LMArena Russian | 1254 | — |
Instruction Following Not comparable
Olmo 3 32b Think: 67.2 (#198), Qwen3 14B: —
| Benchmark | Olmo 3 32b Think | Qwen3 14B |
|---|---|---|
| LMArena Instruction Following | 1275 | — |
Long Context Olmo 3 32b Think leads
Olmo 3 32b Think: 39.4 (#182), Qwen3 14B: 38.1 (#204)
| Benchmark | Olmo 3 32b Think | Qwen3 14B |
|---|---|---|
| Fiction.LiveBench | — | 62.5% |
| LMArena Longer Query | 1296 | — |
Writing & Preference Not comparable
Olmo 3 32b Think: 49.1 (#193), Qwen3 14B: —
| Benchmark | Olmo 3 32b Think | Qwen3 14B |
|---|---|---|
| LMArena Text | 1300 | — |
| LMArena Creative Writing | 1256 | — |
| LMArena Multi-Turn | 1290 | — |
Frequently asked questions
Is Olmo 3 32b Think better than Qwen3 14B?
Olmo 3 32b Think is the stronger model overall, scoring 38.7 to 35.5 on the Noometry Index.
Is Olmo 3 32b Think or Qwen3 14B better for coding?
Olmo 3 32b Think scores higher on coding benchmarks: 38.6 versus 37.3 in the Noometry coding category.
How many benchmarks do Olmo 3 32b Think and Qwen3 14B share?
0 benchmarks have published results for both models. Olmo 3 32b Think has 14 scored results on Noometry and Qwen3 14B has 12.