Model comparison
GPT-5.3 Codex vs Qwen3.5 122B-A10B
GPT-5.3 Codex is the stronger model overall, scoring 45.8 to 42.1 on the Noometry Index. Qwen3.5 122B-A10B costs 4.4× less per token, which makes it the better buy when GPT-5.3 Codex's lead doesn't matter for your workload.
Last verified . 1 shared benchmarks.
Alibaba (Qwen)Summary
- They share 1 benchmark with published results for both. GPT-5.3 Codex scores higher in 1 category and Qwen3.5 122B-A10B in 0 categories; one gap is clear of the uncertainty.
- The widest gap is in coding, where GPT-5.3 Codex leads 48.6 to 39.1.
- Qwen3.5 122B-A10B is cheaper at $0.40 / $3.20 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Codex.
- GPT-5.3 Codex accepts more context: 400K tokens versus 262K.
- Qwen3.5 122B-A10B has downloadable open weights; the other is API-only.
Side by side
| GPT-5.3 Codex | Qwen3.5 122B-A10B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 45.8 | 42.1 |
| Released | 2026-02-05 | 2026-02-23 |
| Weights | Proprietary | Open |
| Context window | 400K | 262K |
| Max output | 128K | 66K |
| Input $ / M tokens | $1.75 | $0.40 |
| Output $ / M tokens | $14 | $3.20 |
| Results tracked | 8 | 27 |
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Category by category
Coding GPT-5.3 Codex leads
GPT-5.3 Codex: 48.6 (#56), Qwen3.5 122B-A10B: 39.1 (#162)
| Benchmark | GPT-5.3 Codex | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena WebDev | 1409 | 1360 |
| SWE-bench Verified | 74.8% | — |
| SciCode | — | 35.6% |
| WeirdML | 79.3% | — |
| LMArena Coding | — | 1436 |
| ALE-Bench | 1,655 | — |
Agentic & Tool Use Not comparable
GPT-5.3 Codex: 48.0 (#9), Qwen3.5 122B-A10B: —
| Benchmark | GPT-5.3 Codex | Qwen3.5 122B-A10B |
|---|---|---|
| Terminal-Bench | 78.4% | — |
| METR Time Horizons | 74.5% | — |
| Vending-Bench 2 | 5,940 | — |
Reasoning Not comparable
GPT-5.3 Codex: —, Qwen3.5 122B-A10B: 27.2 (#123)
| Benchmark | GPT-5.3 Codex | Qwen3.5 122B-A10B |
|---|---|---|
| NYT Connections (extended) | — | 51.7% |
| CritPt | — | 0.9% |
| Thematic Generalization | — | 51.2% |
| LMArena Hard Prompts | — | 1421 |
| Mystery Game Puzzles | — | 17% |
| DTBench | — | 84.3% |
| LMCA | — | 32.2% |
| Epoch Capabilities Index | 156.77 | — |
Math Not comparable
GPT-5.3 Codex: —, Qwen3.5 122B-A10B: 39.1 (#112)
| Benchmark | GPT-5.3 Codex | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Math | — | 1432 |
Knowledge Not comparable
GPT-5.3 Codex: —, Qwen3.5 122B-A10B: 38.8 (#142)
| Benchmark | GPT-5.3 Codex | Qwen3.5 122B-A10B |
|---|---|---|
| Vectara Hallucination Rate | — | 11.2% |
| LMArena Expert | — | 1432 |
Multimodal Not comparable
GPT-5.3 Codex: —, Qwen3.5 122B-A10B: 39.6 (#57)
| Benchmark | GPT-5.3 Codex | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Vision | — | 1245 |
Multilingual Not comparable
GPT-5.3 Codex: —, Qwen3.5 122B-A10B: 51.6 (#107)
| Benchmark | GPT-5.3 Codex | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Non-English | — | 1400 |
| LMArena Chinese | — | 1462 |
| LMArena French | — | 1442 |
| LMArena German | — | 1426 |
| LMArena Japanese | — | 1367 |
| LMArena Korean | — | 1352 |
| LMArena Russian | — | 1400 |
| LMArena Spanish | — | 1424 |
Instruction Following Not comparable
GPT-5.3 Codex: —, Qwen3.5 122B-A10B: 73.8 (#115)
| Benchmark | GPT-5.3 Codex | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Instruction Following | — | 1399 |
Long Context Not comparable
GPT-5.3 Codex: —, Qwen3.5 122B-A10B: 43.0 (#109)
| Benchmark | GPT-5.3 Codex | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Longer Query | — | 1410 |
Writing & Preference Not comparable
GPT-5.3 Codex: —, Qwen3.5 122B-A10B: 60.0 (#105)
| Benchmark | GPT-5.3 Codex | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Text | — | 1417 |
| LMArena Creative Writing | — | 1368 |
| LMArena Multi-Turn | — | 1416 |
Frequently asked questions
Is GPT-5.3 Codex better than Qwen3.5 122B-A10B?
GPT-5.3 Codex is the stronger model overall, scoring 45.8 to 42.1 on the Noometry Index. Qwen3.5 122B-A10B costs 4.4× less per token, which makes it the better buy when GPT-5.3 Codex's lead doesn't matter for your workload.
Which is cheaper, GPT-5.3 Codex or Qwen3.5 122B-A10B?
Qwen3.5 122B-A10B is cheaper. It lists at $0.40 per million input tokens and $3.20 per million output tokens; GPT-5.3 Codex lists at $1.75 and $14.
Is GPT-5.3 Codex or Qwen3.5 122B-A10B better for coding?
GPT-5.3 Codex scores higher on coding benchmarks: 48.6 versus 39.1 in the Noometry coding category.
Which has the bigger context window?
GPT-5.3 Codex does, with 400K tokens against 262K.
How many benchmarks do GPT-5.3 Codex and Qwen3.5 122B-A10B share?
1 benchmark has published results for both models. GPT-5.3 Codex has 8 scored results on Noometry and Qwen3.5 122B-A10B has 27.