Model comparison
GPT-5-Codex vs Qwen3.6 27B
Qwen3.6 27B is the stronger model overall, scoring 41.9 to 37.3 on the Noometry Index.
Last verified . 0 shared benchmarks.
Alibaba (Qwen)Summary
- The widest gap is in reasoning, where GPT-5-Codex leads 30.0 to 24.4.
- Qwen3.6 27B is cheaper at $0.60 / $3.60 per million input/output tokens, against $1.25 / $10 for GPT-5-Codex.
- GPT-5-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-Codex | Qwen3.6 27B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 37.3 | 41.9 |
| Released | 2025-09-15 | 2026-04-22 |
| Weights | Proprietary | Open |
| Context window | 400K | 262K |
| Max output | 128K | 66K |
| Input $ / M tokens | $1.25 | $0.60 |
| Output $ / M tokens | $10 | $3.60 |
| Results tracked | 3 | 11 |
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Category by category
Coding GPT-5-Codex leads
GPT-5-Codex: 41.9 (#100), Qwen3.6 27B: 38.5 (#162)
Agentic & Tool Use Not comparable
GPT-5-Codex: 30.8 (#66), Qwen3.6 27B: —
| Benchmark | GPT-5-Codex | Qwen3.6 27B |
|---|---|---|
| Terminal-Bench | 44.3% | — |
Reasoning GPT-5-Codex leads
GPT-5-Codex: 30.0 (#80), Qwen3.6 27B: 24.4 (#148)
| Benchmark | GPT-5-Codex | Qwen3.6 27B |
|---|---|---|
| Kagi LLM Benchmark | 70.3% | — |
| CritPt | — | 0.9% |
| Chess Puzzles | — | 22% |
| Mystery Game Puzzles | — | 7% |
| DTBench | — | 78.1% |
| LMCA | — | 34.5% |
| Epoch Capabilities Index | — | 146.47 |
Math Not comparable
GPT-5-Codex: —, Qwen3.6 27B: 47.5 (#56)
| Benchmark | GPT-5-Codex | Qwen3.6 27B |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 35.1% |
| OTIS Mock AIME 2024-2025 | — | 91.1% |
Knowledge Not comparable
GPT-5-Codex: —, Qwen3.6 27B: 52.4 (#58)
| Benchmark | GPT-5-Codex | Qwen3.6 27B |
|---|---|---|
| GPQA Diamond | — | 85.9% |
Writing & Preference Not comparable
GPT-5-Codex: —, Qwen3.6 27B: 50.3 (#180)
| Benchmark | GPT-5-Codex | Qwen3.6 27B |
|---|---|---|
| EQ-Bench 4 | — | 1026 |
Frequently asked questions
Is GPT-5-Codex better than Qwen3.6 27B?
Qwen3.6 27B is the stronger model overall, scoring 41.9 to 37.3 on the Noometry Index.
Which is cheaper, GPT-5-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-Codex lists at $1.25 and $10.
Is GPT-5-Codex or Qwen3.6 27B better for coding?
GPT-5-Codex scores higher on coding benchmarks: 41.9 versus 38.5 in the Noometry coding category.
Which has the bigger context window?
GPT-5-Codex does, with 400K tokens against 262K.
How many benchmarks do GPT-5-Codex and Qwen3.6 27B share?
0 benchmarks have published results for both models. GPT-5-Codex has 3 scored results on Noometry and Qwen3.6 27B has 11.