Model comparison
GPT-5.3 Codex vs Qwen3.6 27B
GPT-5.3 Codex is the stronger model overall, scoring 45.8 to 42.2 on the Noometry Index. Qwen3.6 27B costs 3.6× 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 Qwen3.6 27B 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.
- Qwen3.6 27B is cheaper at $0.60 / $3.60 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.
- Qwen3.6 27B has downloadable open weights; the other is API-only.
Side by side
| GPT-5.3 Codex | Qwen3.6 27B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 45.8 | 42.2 |
| Released | 2026-02-05 | 2026-04-22 |
| Weights | Proprietary | Open |
| Context window | 400K | 262K |
| Max output | 128K | 66K |
| Input $ / M tokens | $1.75 | $0.60 |
| Output $ / M tokens | $14 | $3.60 |
| Results tracked | 8 | 11 |
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Category by category
Coding GPT-5.3 Codex leads
GPT-5.3 Codex: 48.6 (#56), Qwen3.6 27B: 39.1 (#163)
| Benchmark | GPT-5.3 Codex | Qwen3.6 27B |
|---|---|---|
| SWE-bench Verified | 74.8% | — |
| LMArena WebDev | 1409 | — |
| SciCode | — | 37.3% |
| WeirdML | 79.3% | — |
| ALE-Bench | 1,655 | — |
Agentic & Tool Use Not comparable
GPT-5.3 Codex: 48.0 (#9), Qwen3.6 27B: —
| Benchmark | GPT-5.3 Codex | Qwen3.6 27B |
|---|---|---|
| Terminal-Bench | 78.4% | — |
| METR Time Horizons | 74.5% | — |
| Vending-Bench 2 | 5,940 | — |
Reasoning Not comparable
GPT-5.3 Codex: —, Qwen3.6 27B: 25.0 (#153)
| Benchmark | GPT-5.3 Codex | Qwen3.6 27B |
|---|---|---|
| Epoch Capabilities Index | 156.77 | 146.5 |
| CritPt | — | 0.9% |
| Chess Puzzles | — | 22% |
| Mystery Game Puzzles | — | 7% |
| DTBench | — | 78.1% |
| LMCA | — | 34.5% |
Math Not comparable
GPT-5.3 Codex: —, Qwen3.6 27B: 48.5 (#62)
| Benchmark | GPT-5.3 Codex | Qwen3.6 27B |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 35.1% |
| OTIS Mock AIME 2024-2025 | — | 91.1% |
Knowledge Not comparable
GPT-5.3 Codex: —, Qwen3.6 27B: 52.4 (#63)
| Benchmark | GPT-5.3 Codex | Qwen3.6 27B |
|---|---|---|
| GPQA Diamond | — | 85.9% |
Writing & Preference Not comparable
GPT-5.3 Codex: —, Qwen3.6 27B: 50.3 (#181)
| Benchmark | GPT-5.3 Codex | Qwen3.6 27B |
|---|---|---|
| EQ-Bench 4 | — | 1026 |
Frequently asked questions
Is GPT-5.3 Codex better than Qwen3.6 27B?
GPT-5.3 Codex is the stronger model overall, scoring 45.8 to 42.2 on the Noometry Index. Qwen3.6 27B costs 3.6× 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 Qwen3.6 27B?
Qwen3.6 27B is cheaper. It lists at $0.60 per million input tokens and $3.60 per million output tokens; GPT-5.3 Codex lists at $1.75 and $14.
Is GPT-5.3 Codex or Qwen3.6 27B 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 Qwen3.6 27B share?
1 benchmark has published results for both models. GPT-5.3 Codex has 8 scored results on Noometry and Qwen3.6 27B has 11.