Model comparison
GPT-5.3 Codex vs Qwen3.8 Max
Qwen3.8 Max is the stronger model overall, scoring 56.8 to 45.8 on the Noometry Index.
Last verified . 2 shared benchmarks.
Alibaba (Qwen)Summary
- They share 2 benchmarks with published results for both. GPT-5.3 Codex scores higher in 1 category and Qwen3.8 Max in 1 category; 2 gaps are clear of the uncertainty.
- The widest gap is in coding, where Qwen3.8 Max leads 53.5 to 48.6.
- Qwen3.8 Max is cheaper at $2 / $6 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Codex.
- Qwen3.8 Max accepts more context: 1M tokens versus 400K.
Side by side
| GPT-5.3 Codex | Qwen3.8 Max | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 45.8 | 56.8 |
| Released | 2026-02-05 | 2026-08-02 |
| Weights | Proprietary | Proprietary |
| Context window | 400K | 1M |
| Max output | 128K | 131K |
| Input $ / M tokens | $1.75 | $2 |
| Output $ / M tokens | $14 | $6 |
| Results tracked | 8 | 39 |
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Category by category
Coding Qwen3.8 Max leads
GPT-5.3 Codex: 48.6 (#56), Qwen3.8 Max: 53.5 (#29)
| Benchmark | GPT-5.3 Codex | Qwen3.8 Max |
|---|---|---|
| LMArena WebDev | 1409 | 1674 |
| SWE-bench Verified | 74.8% | — |
| DeepSWE | — | 57.5% |
| FrontierSWE | — | 17.8% |
| SciCode | — | 53.2% |
| WeirdML | 79.3% | — |
| LMArena Coding | — | 1502 |
| ALE-Bench | 1,655 | — |
Agentic & Tool Use GPT-5.3 Codex leads
GPT-5.3 Codex: 48.0 (#9), Qwen3.8 Max: 45.4 (#14)
| Benchmark | GPT-5.3 Codex | Qwen3.8 Max |
|---|---|---|
| Terminal-Bench | 78.4% | — |
| APEX-Agents | — | 63.3% |
| τ²-bench Banking | — | 55.1% |
| GDP.pdf | — | 23.2% |
| METR Time Horizons | 74.5% | — |
| Vending-Bench 2 | 5,940 | — |
Reasoning Not comparable
GPT-5.3 Codex: —, Qwen3.8 Max: 54.4 (#26)
| Benchmark | GPT-5.3 Codex | Qwen3.8 Max |
|---|---|---|
| Epoch Capabilities Index | 156.77 | 156.41 |
| NYT Connections (extended) | — | 88.3% |
| CritPt | — | 20% |
| Chess Puzzles | — | 40% |
| LMArena Hard Prompts | — | 1496 |
| Mystery Game Puzzles | — | 38% |
| DTBench | — | 92% |
| LMCA | — | 46.2% |
Math Not comparable
GPT-5.3 Codex: —, Qwen3.8 Max: 73.2 (#20)
| Benchmark | GPT-5.3 Codex | Qwen3.8 Max |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 74.7% |
| FrontierMath Tier 4 | — | 46.3% |
| OTIS Mock AIME 2024-2025 | — | 100% |
| ProofBench | — | 58% |
| LMArena Math | — | 1499 |
Knowledge Not comparable
GPT-5.3 Codex: —, Qwen3.8 Max: 61.7 (#27)
| Benchmark | GPT-5.3 Codex | Qwen3.8 Max |
|---|---|---|
| GPQA Diamond | — | 92.7% |
| SimpleQA Verified | — | 47.3% |
| LMArena Expert | — | 1507 |
Multimodal Not comparable
GPT-5.3 Codex: —, Qwen3.8 Max: 37.2 (#75)
| Benchmark | GPT-5.3 Codex | Qwen3.8 Max |
|---|---|---|
| LMArena Vision | — | 1314 |
| Furniture Assembly | — | 20% |
Multilingual Not comparable
GPT-5.3 Codex: —, Qwen3.8 Max: 56.7 (#18)
| Benchmark | GPT-5.3 Codex | Qwen3.8 Max |
|---|---|---|
| LMArena Non-English | — | 1472 |
| LMArena Chinese | — | 1538 |
| LMArena French | — | 1503 |
| LMArena German | — | 1483 |
| LMArena Japanese | — | 1467 |
| LMArena Korean | — | 1461 |
| LMArena Russian | — | 1481 |
| LMArena Spanish | — | 1492 |
Instruction Following Not comparable
GPT-5.3 Codex: —, Qwen3.8 Max: 77.6 (#17)
| Benchmark | GPT-5.3 Codex | Qwen3.8 Max |
|---|---|---|
| LMArena Instruction Following | — | 1479 |
Long Context Not comparable
GPT-5.3 Codex: —, Qwen3.8 Max: 45.6 (#31)
| Benchmark | GPT-5.3 Codex | Qwen3.8 Max |
|---|---|---|
| LMArena Longer Query | — | 1489 |
Writing & Preference Not comparable
GPT-5.3 Codex: —, Qwen3.8 Max: 67.1 (#30)
| Benchmark | GPT-5.3 Codex | Qwen3.8 Max |
|---|---|---|
| LMArena Text | — | 1483 |
| LMArena Creative Writing | — | 1479 |
| LMArena Multi-Turn | — | 1489 |
Frequently asked questions
Is GPT-5.3 Codex better than Qwen3.8 Max?
Qwen3.8 Max is the stronger model overall, scoring 56.8 to 45.8 on the Noometry Index.
Which is cheaper, GPT-5.3 Codex or Qwen3.8 Max?
Qwen3.8 Max is cheaper. It lists at $2 per million input tokens and $6 per million output tokens; GPT-5.3 Codex lists at $1.75 and $14.
Is GPT-5.3 Codex or Qwen3.8 Max better for coding?
Qwen3.8 Max scores higher on coding benchmarks: 53.5 versus 48.6 in the Noometry coding category.
Which has the bigger context window?
Qwen3.8 Max does, with 1M tokens against 400K.
How many benchmarks do GPT-5.3 Codex and Qwen3.8 Max share?
2 benchmarks have published results for both models. GPT-5.3 Codex has 8 scored results on Noometry and Qwen3.8 Max has 39.