Model comparison
GPT-5.3 Codex vs Qwen3 14B
GPT-5.3 Codex is the stronger model overall, scoring 45.8 to 35.5 on the Noometry Index. Qwen3 14B costs 7.9× 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 2 categories and Qwen3 14B 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 29.6.
- Qwen3 14B is cheaper at $0.35 / $1.40 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Codex.
- GPT-5.3 Codex accepts more context: 400K tokens versus 131K.
- Qwen3 14B has downloadable open weights; the other is API-only.
Side by side
| GPT-5.3 Codex | Qwen3 14B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 45.8 | 35.5 |
| Released | 2026-02-05 | 2025-04 |
| Weights | Proprietary | Open |
| Context window | 400K | 131K |
| Max output | 128K | 8K |
| Input $ / M tokens | $1.75 | $0.35 |
| Output $ / M tokens | $14 | $1.40 |
| Results tracked | 8 | 12 |
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Category by category
Coding GPT-5.3 Codex leads
GPT-5.3 Codex: 48.6 (#56), Qwen3 14B: 37.3 (#195)
| Benchmark | GPT-5.3 Codex | Qwen3 14B |
|---|---|---|
| SWE-bench Verified | 74.8% | — |
| LMArena WebDev | 1409 | — |
| SciCode | — | 31.6% |
| WeirdML | 79.3% | — |
| ALE-Bench | 1,655 | — |
Agentic & Tool Use GPT-5.3 Codex leads
GPT-5.3 Codex: 48.0 (#9), Qwen3 14B: 29.6 (#83)
| Benchmark | GPT-5.3 Codex | Qwen3 14B |
|---|---|---|
| Terminal-Bench | 78.4% | — |
| Berkeley Function Calling Leaderboard | — | 41% |
| METR Time Horizons | 74.5% | — |
| Vending-Bench 2 | 5,940 | — |
Reasoning Not comparable
GPT-5.3 Codex: —, Qwen3 14B: 18.5 (#280)
| Benchmark | GPT-5.3 Codex | Qwen3 14B |
|---|---|---|
| Epoch Capabilities Index | 156.77 | 138.23 |
| Kagi LLM Benchmark | — | 49.1% |
| CritPt | — | 0% |
| Chess Puzzles | — | 4% |
| DTBench | — | 64% |
| LMCA | — | 18.2% |
Math Not comparable
GPT-5.3 Codex: —, Qwen3 14B: 38.6 (#133)
| Benchmark | GPT-5.3 Codex | Qwen3 14B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 66.4% |
Knowledge Not comparable
GPT-5.3 Codex: —, Qwen3 14B: 39.3 (#134)
| Benchmark | GPT-5.3 Codex | Qwen3 14B |
|---|---|---|
| GPQA Diamond | — | 63.8% |
| Vectara Hallucination Rate | — | 5.4% |
Long Context Not comparable
GPT-5.3 Codex: —, Qwen3 14B: 38.1 (#204)
| Benchmark | GPT-5.3 Codex | Qwen3 14B |
|---|---|---|
| Fiction.LiveBench | — | 62.5% |
Frequently asked questions
Is GPT-5.3 Codex better than Qwen3 14B?
GPT-5.3 Codex is the stronger model overall, scoring 45.8 to 35.5 on the Noometry Index. Qwen3 14B costs 7.9× 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 14B?
Qwen3 14B is cheaper. It lists at $0.35 per million input tokens and $1.40 per million output tokens; GPT-5.3 Codex lists at $1.75 and $14.
Is GPT-5.3 Codex or Qwen3 14B better for coding?
GPT-5.3 Codex scores higher on coding benchmarks: 48.6 versus 37.3 in the Noometry coding category.
Which has the bigger context window?
GPT-5.3 Codex does, with 400K tokens against 131K.
How many benchmarks do GPT-5.3 Codex and Qwen3 14B share?
1 benchmark has published results for both models. GPT-5.3 Codex has 8 scored results on Noometry and Qwen3 14B has 12.