Model comparison
o1 vs Qwen3 14B
o1 is the stronger model overall, scoring 40.9 to 35.5 on the Noometry Index. Qwen3 14B costs 43× less per token, which makes it the better buy when o1's lead doesn't matter for your workload.
Last verified . 7 shared benchmarks.
Alibaba (Qwen)Summary
- They share 7 benchmarks with published results for both. o1 scores higher in 4 categories and Qwen3 14B in 2 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in long context, where o1 leads 50.3 to 38.1.
- The biggest single-benchmark swing is Fiction.LiveBench: 83.3% for o1 and 62.5% for Qwen3 14B.
- Qwen3 14B is cheaper at $0.35 / $1.40 per million input/output tokens, against $15 / $60 for o1.
- o1 accepts more context: 200K tokens versus 131K.
- Qwen3 14B has downloadable open weights; the other is API-only.
Side by side
| o1 | Qwen3 14B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 40.9 | 35.5 |
| Released | 2024-09-12 | 2025-04 |
| Weights | Proprietary | Open |
| Context window | 200K | 131K |
| Max output | 100K | 8K |
| Input $ / M tokens | $15 | $0.35 |
| Output $ / M tokens | $60 | $1.40 |
| Results tracked | 52 | 12 |
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Category by category
Coding o1 leads
o1: 46.1 (#70), Qwen3 14B: 37.3 (#195)
| Benchmark | o1 | Qwen3 14B |
|---|---|---|
| Aider Polyglot | 61.7% | — |
| SciCode | — | 31.6% |
| WeirdML | 47.6% | — |
| LiveBench Coding | 69.7% | — |
| LMArena Coding | 1367 | — |
| CadEval | 56% | — |
| HumanEval+ | 89% | — |
| MBPP+ | 80.2% | — |
Agentic & Tool Use Qwen3 14B leads
o1: 24.6 (#117), Qwen3 14B: 29.6 (#83)
| Benchmark | o1 | Qwen3 14B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 41% |
| Cybench | 10% | — |
| METR Time Horizons | 51.1% | — |
Reasoning o1 leads
o1: 27.9 (#111), Qwen3 14B: 18.5 (#280)
| Benchmark | o1 | Qwen3 14B |
|---|---|---|
| Chess Puzzles | 15% | 4% |
| DTBench | 74.7% | 64% |
| LMCA | 22.3% | 18.2% |
| Epoch Capabilities Index | 141.91 | 138.23 |
| SimpleBench | 41.7% | — |
| Kagi LLM Benchmark | — | 49.1% |
| ARC-AGI-1 | 30.7% | — |
| CritPt | — | 0% |
| EnigmaEval | 5.7% | — |
| LiveBench Reasoning | 91.6% | — |
| LMArena Hard Prompts | 1371 | — |
| LiveBench Data Analysis | 65.5% | — |
| LiveBench | 75.7% | — |
Math Qwen3 14B leads
o1: 36.1 (#175), Qwen3 14B: 38.6 (#133)
| Benchmark | o1 | Qwen3 14B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 73.3% | 66.4% |
| FrontierMath (Tiers 1-3) | 14.7% | — |
| LiveBench Math | 80.3% | — |
| LMArena Math | 1388 | — |
| MATH Level 5 | 94.7% | — |
| FrontierMath (Feb 2025 set) | 9.3% | — |
Knowledge o1 leads
o1: 41.5 (#110), Qwen3 14B: 39.3 (#134)
| Benchmark | o1 | Qwen3 14B |
|---|---|---|
| GPQA Diamond | 76.8% | 63.8% |
| Humanity's Last Exam | 8% | — |
| SimpleQA Verified | 41.1% | — |
| Confabulations | 11.7% | — |
| Vectara Hallucination Rate | — | 5.4% |
| LMArena Expert | 1361 | — |
Multimodal Not comparable
o1: 34.2 (#93), Qwen3 14B: —
| Benchmark | o1 | Qwen3 14B |
|---|---|---|
| LMArena Vision | 1168 | — |
| GeoBench | 80% | — |
| VPCT | 37% | — |
| SpatialViz-Bench | 41.4% | — |
Multilingual Not comparable
o1: 48.6 (#142), Qwen3 14B: —
| Benchmark | o1 | Qwen3 14B |
|---|---|---|
| LMArena Non-English | 1358 | — |
| LMArena Chinese | 1394 | — |
| LMArena French | 1344 | — |
| LMArena German | 1337 | — |
| LMArena Japanese | 1346 | — |
| LMArena Korean | 1396 | — |
| LMArena Russian | 1356 | — |
| LMArena Spanish | 1345 | — |
Instruction Following Not comparable
o1: 74.8 (#86), Qwen3 14B: —
| Benchmark | o1 | Qwen3 14B |
|---|---|---|
| LiveBench Instruction Following | 81.5% | — |
| LMArena Instruction Following | 1367 | — |
Long Context o1 leads
o1: 50.3 (#9), Qwen3 14B: 38.1 (#204)
| Benchmark | o1 | Qwen3 14B |
|---|---|---|
| Fiction.LiveBench | 83.3% | 62.5% |
| LMArena Longer Query | 1378 | — |
Writing & Preference Not comparable
o1: 55.6 (#144), Qwen3 14B: —
| Benchmark | o1 | Qwen3 14B |
|---|---|---|
| LMArena Text | 1366 | — |
| LMArena Creative Writing | 1348 | — |
| Short-Story Creative Writing | 70.2% | — |
| LMArena Multi-Turn | 1369 | — |
| LiveBench Language | 65.4% | — |
Frequently asked questions
Is o1 better than Qwen3 14B?
o1 is the stronger model overall, scoring 40.9 to 35.5 on the Noometry Index. Qwen3 14B costs 43× less per token, which makes it the better buy when o1's lead doesn't matter for your workload.
Which is cheaper, o1 or Qwen3 14B?
Qwen3 14B is cheaper. It lists at $0.35 per million input tokens and $1.40 per million output tokens; o1 lists at $15 and $60.
Is o1 or Qwen3 14B better for coding?
o1 scores higher on coding benchmarks: 46.1 versus 37.3 in the Noometry coding category.
Which has the bigger context window?
o1 does, with 200K tokens against 131K.
How many benchmarks do o1 and Qwen3 14B share?
7 benchmarks have published results for both models. o1 has 52 scored results on Noometry and Qwen3 14B has 12.