Model comparison
GPT-5.3 Codex vs Qwen3.5 27B
GPT-5.3 Codex is the stronger model overall, scoring 45.8 to 41.9 on the Noometry Index. Qwen3.5 27B costs 5.8× less per token, which makes it the better buy when GPT-5.3 Codex's lead doesn't matter for your workload.
Last verified . 4 shared benchmarks.
Alibaba (Qwen)Summary
- They share 4 benchmarks with published results for both. GPT-5.3 Codex scores higher in 1 category and Qwen3.5 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 38.9.
- The biggest single-benchmark swing is WeirdML: 79.3% for GPT-5.3 Codex and 39.5% for Qwen3.5 27B.
- Qwen3.5 27B is cheaper at $0.30 / $2.40 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 27B has downloadable open weights; the other is API-only.
Side by side
| GPT-5.3 Codex | Qwen3.5 27B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 45.8 | 41.9 |
| Released | 2026-02-05 | 2026-02-23 |
| Weights | Proprietary | Open |
| Context window | 400K | 262K |
| Max output | 128K | 66K |
| Input $ / M tokens | $1.75 | $0.30 |
| Output $ / M tokens | $14 | $2.40 |
| Results tracked | 8 | 28 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GPT-5.3 Codex leads
GPT-5.3 Codex: 48.6 (#56), Qwen3.5 27B: 38.9 (#168)
| Benchmark | GPT-5.3 Codex | Qwen3.5 27B |
|---|---|---|
| LMArena WebDev | 1409 | 1358 |
| WeirdML | 79.3% | 39.5% |
| ALE-Bench | 1,655 | 349.45 |
| SWE-bench Verified | 74.8% | — |
| LMArena Coding | — | 1427 |
Agentic & Tool Use Not comparable
GPT-5.3 Codex: 48.0 (#9), Qwen3.5 27B: —
| Benchmark | GPT-5.3 Codex | Qwen3.5 27B |
|---|---|---|
| Vending-Bench 2 | 5,940 | 201.98 |
| Terminal-Bench | 78.4% | — |
| METR Time Horizons | 74.5% | — |
Reasoning Not comparable
GPT-5.3 Codex: —, Qwen3.5 27B: 27.5 (#117)
| Benchmark | GPT-5.3 Codex | Qwen3.5 27B |
|---|---|---|
| NYT Connections (extended) | — | 47.9% |
| Thematic Generalization | — | 45.5% |
| LMArena Hard Prompts | — | 1414 |
| DTBench | — | 82.4% |
| LMCA | — | 34% |
| Epoch Capabilities Index | 156.77 | — |
Math Not comparable
GPT-5.3 Codex: —, Qwen3.5 27B: 38.8 (#127)
| Benchmark | GPT-5.3 Codex | Qwen3.5 27B |
|---|---|---|
| MathArena Final-Answer Competitions | — | 56.7% |
| LMArena Math | — | 1429 |
Knowledge Not comparable
GPT-5.3 Codex: —, Qwen3.5 27B: 38.0 (#150)
| Benchmark | GPT-5.3 Codex | Qwen3.5 27B |
|---|---|---|
| Vectara Hallucination Rate | — | 12.1% |
| LMArena Expert | — | 1428 |
Multimodal Not comparable
GPT-5.3 Codex: —, Qwen3.5 27B: 39.4 (#59)
| Benchmark | GPT-5.3 Codex | Qwen3.5 27B |
|---|---|---|
| LMArena Vision | — | 1241 |
Multilingual Not comparable
GPT-5.3 Codex: —, Qwen3.5 27B: 50.8 (#115)
| Benchmark | GPT-5.3 Codex | Qwen3.5 27B |
|---|---|---|
| LMArena Non-English | — | 1390 |
| LMArena Chinese | — | 1478 |
| LMArena French | — | 1410 |
| LMArena German | — | 1393 |
| LMArena Japanese | — | 1345 |
| LMArena Korean | — | 1358 |
| LMArena Russian | — | 1390 |
| LMArena Spanish | — | 1407 |
Instruction Following Not comparable
GPT-5.3 Codex: —, Qwen3.5 27B: 73.5 (#119)
| Benchmark | GPT-5.3 Codex | Qwen3.5 27B |
|---|---|---|
| LMArena Instruction Following | — | 1393 |
Long Context Not comparable
GPT-5.3 Codex: —, Qwen3.5 27B: 43.1 (#106)
| Benchmark | GPT-5.3 Codex | Qwen3.5 27B |
|---|---|---|
| LMArena Longer Query | — | 1413 |
Writing & Preference Not comparable
GPT-5.3 Codex: —, Qwen3.5 27B: 59.3 (#111)
| Benchmark | GPT-5.3 Codex | Qwen3.5 27B |
|---|---|---|
| LMArena Text | — | 1409 |
| LMArena Creative Writing | — | 1362 |
| LMArena Multi-Turn | — | 1410 |
Frequently asked questions
Is GPT-5.3 Codex better than Qwen3.5 27B?
GPT-5.3 Codex is the stronger model overall, scoring 45.8 to 41.9 on the Noometry Index. Qwen3.5 27B costs 5.8× 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 27B?
Qwen3.5 27B is cheaper. It lists at $0.30 per million input tokens and $2.40 per million output tokens; GPT-5.3 Codex lists at $1.75 and $14.
Is GPT-5.3 Codex or Qwen3.5 27B better for coding?
GPT-5.3 Codex scores higher on coding benchmarks: 48.6 versus 38.9 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 27B share?
4 benchmarks have published results for both models. GPT-5.3 Codex has 8 scored results on Noometry and Qwen3.5 27B has 28.