Model comparison
GPT-5.3 Codex vs Qwen3.5-9B
GPT-5.3 Codex is the stronger model overall, scoring 45.8 to 33.8 on the Noometry Index. Qwen3.5-9B costs 43× less per token, which makes it the better buy when GPT-5.3 Codex'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. GPT-5.3 Codex scores higher in 2 categories and Qwen3.5-9B in 0 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in agentic & tool use, where GPT-5.3 Codex leads 48.0 to 14.5.
- The biggest single-benchmark swing is Terminal-Bench: 78.4% for GPT-5.3 Codex and 9.2% for Qwen3.5-9B.
- Qwen3.5-9B is cheaper at $0.10 / $0.15 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.
- Qwen3.5-9B has downloadable open weights; the other is API-only.
Side by side
| GPT-5.3 Codex | Qwen3.5-9B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 45.8 | 33.8 |
| Released | 2026-02-05 | 2026-02-23 |
| Weights | Proprietary | Open |
| Context window | 400K | 262K |
| Max output | 128K | 66K |
| Input $ / M tokens | $1.75 | $0.10 |
| Output $ / M tokens | $14 | $0.15 |
| Results tracked | 8 | 10 |
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Category by category
Coding GPT-5.3 Codex leads
GPT-5.3 Codex: 48.6 (#56), Qwen3.5-9B: 35.9 (#217)
| Benchmark | GPT-5.3 Codex | Qwen3.5-9B |
|---|---|---|
| SWE-bench Verified | 74.8% | — |
| LMArena WebDev | 1409 | — |
| SciCode | — | 27.5% |
| WeirdML | 79.3% | — |
| ALE-Bench | 1,655 | — |
Agentic & Tool Use GPT-5.3 Codex leads
GPT-5.3 Codex: 48.0 (#9), Qwen3.5-9B: 14.5 (#151)
| Benchmark | GPT-5.3 Codex | Qwen3.5-9B |
|---|---|---|
| Terminal-Bench | 78.4% | 9.2% |
| METR Time Horizons | 74.5% | — |
| Vending-Bench 2 | 5,940 | — |
Reasoning Not comparable
GPT-5.3 Codex: —, Qwen3.5-9B: 23.1 (#182)
| Benchmark | GPT-5.3 Codex | Qwen3.5-9B |
|---|---|---|
| Epoch Capabilities Index | 156.77 | 139.46 |
| CritPt | — | 0.3% |
| Chess Puzzles | — | 12% |
| DTBench | — | 71.2% |
| LMCA | — | 24.5% |
Math Not comparable
GPT-5.3 Codex: —, Qwen3.5-9B: 34.8 (#192)
| Benchmark | GPT-5.3 Codex | Qwen3.5-9B |
|---|---|---|
| MathArena Final-Answer Competitions | — | 48.5% |
| OTIS Mock AIME 2024-2025 | — | 61.7% |
Knowledge Not comparable
GPT-5.3 Codex: —, Qwen3.5-9B: 46.0 (#84)
| Benchmark | GPT-5.3 Codex | Qwen3.5-9B |
|---|---|---|
| GPQA Diamond | — | 79% |
Frequently asked questions
Is GPT-5.3 Codex better than Qwen3.5-9B?
GPT-5.3 Codex is the stronger model overall, scoring 45.8 to 33.8 on the Noometry Index. Qwen3.5-9B costs 43× 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 Qwen3.5-9B?
Qwen3.5-9B is cheaper. It lists at $0.10 per million input tokens and $0.15 per million output tokens; GPT-5.3 Codex lists at $1.75 and $14.
Is GPT-5.3 Codex or Qwen3.5-9B better for coding?
GPT-5.3 Codex scores higher on coding benchmarks: 48.6 versus 35.9 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 Qwen3.5-9B share?
2 benchmarks have published results for both models. GPT-5.3 Codex has 8 scored results on Noometry and Qwen3.5-9B has 10.