Model comparison
o3 vs Qwen3 Coder Next
o3 is the stronger model overall, scoring 47.5 to 34.3 on the Noometry Index. Qwen3 Coder Next costs 12× less per token, which makes it the better buy when o3's lead doesn't matter for your workload.
Last verified . 2 shared benchmarks.
Alibaba (Qwen)Summary
- They share 2 benchmarks with published results for both. o3 scores higher in 2 categories and Qwen3 Coder Next in 0 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in coding, where o3 leads 46.8 to 36.3.
- The biggest single-benchmark swing is WeirdML: 52.4% for o3 and 34.4% for Qwen3 Coder Next.
- Qwen3 Coder Next is cheaper at $0.12 / $0.80 per million input/output tokens, against $2 / $8 for o3.
- Qwen3 Coder Next accepts more context: 262K tokens versus 200K.
- Qwen3 Coder Next has downloadable open weights; the other is API-only.
Side by side
| o3 | Qwen3 Coder Next | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 47.5 | 34.3 |
| Released | 2025-04-16 | 2026-02-02 |
| Weights | Proprietary | Open |
| Context window | 200K | 262K |
| Max output | 100K | 66K |
| Input $ / M tokens | $2 | $0.12 |
| Output $ / M tokens | $8 | $0.80 |
| Results tracked | 63 | 3 |
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Category by category
Coding o3 leads
o3: 46.8 (#64), Qwen3 Coder Next: 36.3 (#210)
| Benchmark | o3 | Qwen3 Coder Next |
|---|---|---|
| WeirdML | 52.4% | 34.4% |
| SWE-bench Verified | 62.3% | — |
| SWE-bench Verified (bash only) | 58.4% | — |
| Aider Polyglot | 81.3% | — |
| SciCode | — | 32.3% |
| GSO | 8.8% | — |
| LMArena Coding | 1408 | — |
| CadEval | 74% | — |
| ALE-Bench | 933.55 | — |
Agentic & Tool Use Not comparable
o3: 34.5 (#44), Qwen3 Coder Next: —
| Benchmark | o3 | Qwen3 Coder Next |
|---|---|---|
| Berkeley Function Calling Leaderboard | 63% | — |
| GDPval | 30.8% | — |
| DeepResearch Bench | 45.2% | — |
| OSWorld | 23% | — |
| LMArena Search | 1144 | — |
| METR Time Horizons | 65.4% | — |
Reasoning o3 leads
o3: 32.0 (#78), Qwen3 Coder Next: 22.4 (#196)
| Benchmark | o3 | Qwen3 Coder Next |
|---|---|---|
| CritPt | 1.4% | 0% |
| ARC-AGI-2 | 6.5% | — |
| SimpleBench | 53.1% | — |
| Kagi LLM Benchmark | 67.6% | — |
| ARC-AGI-1 | 60.8% | — |
| Chess Puzzles | 38% | — |
| EnigmaEval | 13.1% | — |
| LMArena Hard Prompts | 1402 | — |
| Mystery Game Puzzles | 29% | — |
| DTBench | 84.8% | — |
| LMCA | 39.7% | — |
| Epoch Capabilities Index | 146.86 | — |
| ForecastBench | 62.5 | — |
Math Not comparable
o3: 50.2 (#58), Qwen3 Coder Next: —
| Benchmark | o3 | Qwen3 Coder Next |
|---|---|---|
| FrontierMath (Tiers 1-3) | 33.3% | — |
| OTIS Mock AIME 2024-2025 | 84.4% | — |
| Omni-MATH | 71.4% | — |
| LMArena Math | 1426 | — |
| MATH Level 5 | 97.8% | — |
| FrontierMath (Feb 2025 set) | 18.7% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge Not comparable
o3: 54.6 (#52), Qwen3 Coder Next: —
| Benchmark | o3 | Qwen3 Coder Next |
|---|---|---|
| GPQA Diamond | 81.8% | — |
| Humanity's Last Exam | 20.3% | — |
| SimpleQA Verified | 49.4% | — |
| MMLU-Pro | 85.9% | — |
| Confabulations | 14.4% | — |
| GPQA (HELM) | 75.3% | — |
| LMArena Expert | 1402 | — |
Multimodal Not comparable
o3: 41.4 (#36), Qwen3 Coder Next: —
| Benchmark | o3 | Qwen3 Coder Next |
|---|---|---|
| LMArena Vision | 1214 | — |
| GeoBench | 74% | — |
| VPCT | 52% | — |
Multilingual Not comparable
o3: 51.7 (#105), Qwen3 Coder Next: —
| Benchmark | o3 | Qwen3 Coder Next |
|---|---|---|
| LMArena Non-English | 1401 | — |
| LMArena Chinese | 1437 | — |
| LMArena French | 1430 | — |
| LMArena German | 1420 | — |
| LMArena Japanese | 1403 | — |
| LMArena Korean | 1370 | — |
| LMArena Russian | 1406 | — |
| LMArena Spanish | 1395 | — |
Instruction Following Not comparable
o3: 72.8 (#127), Qwen3 Coder Next: —
| Benchmark | o3 | Qwen3 Coder Next |
|---|---|---|
| IFEval | 86.9% | — |
| LMArena Instruction Following | 1368 | — |
Long Context Not comparable
o3: 53.3 (#6), Qwen3 Coder Next: —
| Benchmark | o3 | Qwen3 Coder Next |
|---|---|---|
| Fiction.LiveBench | 88.9% | — |
| CL-bench | 17.8% | — |
| LMArena Longer Query | 1372 | — |
Writing & Preference Not comparable
o3: 63.5 (#64), Qwen3 Coder Next: —
| Benchmark | o3 | Qwen3 Coder Next |
|---|---|---|
| LMArena Text | 1410 | — |
| LMArena Creative Writing | 1359 | — |
| Short-Story Creative Writing | 83.9% | — |
| EQ-Bench Creative Writing | 1676 | — |
| WildBench | 86.1% | — |
| LMArena Multi-Turn | 1405 | — |
Frequently asked questions
Is o3 better than Qwen3 Coder Next?
o3 is the stronger model overall, scoring 47.5 to 34.3 on the Noometry Index. Qwen3 Coder Next costs 12× less per token, which makes it the better buy when o3's lead doesn't matter for your workload.
Which is cheaper, o3 or Qwen3 Coder Next?
Qwen3 Coder Next is cheaper. It lists at $0.12 per million input tokens and $0.80 per million output tokens; o3 lists at $2 and $8.
Is o3 or Qwen3 Coder Next better for coding?
o3 scores higher on coding benchmarks: 46.8 versus 36.3 in the Noometry coding category.
Which has the bigger context window?
Qwen3 Coder Next does, with 262K tokens against 200K.
How many benchmarks do o3 and Qwen3 Coder Next share?
2 benchmarks have published results for both models. o3 has 63 scored results on Noometry and Qwen3 Coder Next has 3.