Model comparison
GPT-5.3 Codex vs Qwen3.5-Flash
GPT-5.3 Codex is the stronger model overall, scoring 45.8 to 42.5 on the Noometry Index. Qwen3.5-Flash costs 27× 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-Flash 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 34.2.
- Qwen3.5-Flash is cheaper at $0.10 / $0.40 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Codex.
- Qwen3.5-Flash accepts more context: 1M tokens versus 400K.
Side by side
| GPT-5.3 Codex | Qwen3.5-Flash | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 45.8 | 42.5 |
| Released | 2026-02-05 | 2026-02-23 |
| Weights | Proprietary | Proprietary |
| Context window | 400K | 1M |
| Max output | 128K | 66K |
| Input $ / M tokens | $1.75 | $0.10 |
| Output $ / M tokens | $14 | $0.40 |
| Results tracked | 8 | 32 |
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Category by category
Coding GPT-5.3 Codex leads
GPT-5.3 Codex: 48.6 (#56), Qwen3.5-Flash: 34.2 (#242)
| Benchmark | GPT-5.3 Codex | Qwen3.5-Flash |
|---|---|---|
| LMArena WebDev | 1409 | 1244 |
| ALE-Bench | 1,655 | 221.8 |
| SWE-bench Verified | 74.8% | — |
| WeirdML | 79.3% | — |
| LMArena Coding | — | 1412 |
Agentic & Tool Use Not comparable
GPT-5.3 Codex: 48.0 (#9), Qwen3.5-Flash: —
| Benchmark | GPT-5.3 Codex | Qwen3.5-Flash |
|---|---|---|
| Vending-Bench 2 | 5,940 | 462.69 |
| Terminal-Bench | 78.4% | — |
| METR Time Horizons | 74.5% | — |
Reasoning Not comparable
GPT-5.3 Codex: —, Qwen3.5-Flash: 33.7 (#72)
| Benchmark | GPT-5.3 Codex | Qwen3.5-Flash |
|---|---|---|
| Epoch Capabilities Index | 156.77 | 143.98 |
| Chess Puzzles | — | 21% |
| LMArena Hard Prompts | — | 1403 |
| Mystery Game Puzzles | — | 20% |
| DTBench | — | 82.9% |
| LMCA | — | 29.1% |
Math Not comparable
GPT-5.3 Codex: —, Qwen3.5-Flash: 37.4 (#158)
| Benchmark | GPT-5.3 Codex | Qwen3.5-Flash |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 18.2% |
| OTIS Mock AIME 2024-2025 | — | 84.4% |
| LMArena Math | — | 1407 |
| FrontierMath (Feb 2025 set) | — | 6.2% |
| FrontierMath Tier 4 (v1) | — | 0% |
Knowledge Not comparable
GPT-5.3 Codex: —, Qwen3.5-Flash: 43.2 (#93)
| Benchmark | GPT-5.3 Codex | Qwen3.5-Flash |
|---|---|---|
| GPQA Diamond | — | 82.3% |
| SimpleQA Verified | — | 20.3% |
| Vectara Hallucination Rate | — | 10.5% |
| LMArena Expert | — | 1407 |
Multilingual Not comparable
GPT-5.3 Codex: —, Qwen3.5-Flash: 50.5 (#121)
| Benchmark | GPT-5.3 Codex | Qwen3.5-Flash |
|---|---|---|
| LMArena Non-English | — | 1385 |
| LMArena Chinese | — | 1446 |
| LMArena French | — | 1412 |
| LMArena German | — | 1390 |
| LMArena Japanese | — | 1368 |
| LMArena Korean | — | 1344 |
| LMArena Russian | — | 1379 |
| LMArena Spanish | — | 1400 |
Instruction Following Not comparable
GPT-5.3 Codex: —, Qwen3.5-Flash: 72.6 (#139)
| Benchmark | GPT-5.3 Codex | Qwen3.5-Flash |
|---|---|---|
| LMArena Instruction Following | — | 1374 |
Long Context Not comparable
GPT-5.3 Codex: —, Qwen3.5-Flash: 42.4 (#124)
| Benchmark | GPT-5.3 Codex | Qwen3.5-Flash |
|---|---|---|
| LMArena Longer Query | — | 1392 |
Writing & Preference Not comparable
GPT-5.3 Codex: —, Qwen3.5-Flash: 57.9 (#122)
| Benchmark | GPT-5.3 Codex | Qwen3.5-Flash |
|---|---|---|
| LMArena Text | — | 1397 |
| LMArena Creative Writing | — | 1343 |
| LMArena Multi-Turn | — | 1393 |
Frequently asked questions
Is GPT-5.3 Codex better than Qwen3.5-Flash?
GPT-5.3 Codex is the stronger model overall, scoring 45.8 to 42.5 on the Noometry Index. Qwen3.5-Flash costs 27× 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-Flash?
Qwen3.5-Flash is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; GPT-5.3 Codex lists at $1.75 and $14.
Is GPT-5.3 Codex or Qwen3.5-Flash better for coding?
GPT-5.3 Codex scores higher on coding benchmarks: 48.6 versus 34.2 in the Noometry coding category.
Which has the bigger context window?
Qwen3.5-Flash does, with 1M tokens against 400K.
How many benchmarks do GPT-5.3 Codex and Qwen3.5-Flash share?
4 benchmarks have published results for both models. GPT-5.3 Codex has 8 scored results on Noometry and Qwen3.5-Flash has 32.