Model comparison
GPT-5-Codex vs Qwen3 14B
GPT-5-Codex is the stronger model overall, scoring 37.3 to 35.0 on the Noometry Index. Qwen3 14B costs 5.6× less per token, which makes it the better buy when GPT-5-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-Codex scores higher in 3 categories and Qwen3 14B in 0 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-5-Codex leads 30.0 to 18.1.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 70.3% for GPT-5-Codex and 49.1% for Qwen3 14B.
- Qwen3 14B is cheaper at $0.35 / $1.40 per million input/output tokens, against $1.25 / $10 for GPT-5-Codex.
- GPT-5-Codex accepts more context: 400K tokens versus 131K.
- Qwen3 14B has downloadable open weights; the other is API-only.
Side by side
| GPT-5-Codex | Qwen3 14B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 37.3 | 35.0 |
| Released | 2025-09-15 | 2025-04 |
| Weights | Proprietary | Open |
| Context window | 400K | 131K |
| Max output | 128K | 8K |
| Input $ / M tokens | $1.25 | $0.35 |
| Output $ / M tokens | $10 | $1.40 |
| Results tracked | 3 | 12 |
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Category by category
Coding GPT-5-Codex leads
GPT-5-Codex: 41.9 (#100), Qwen3 14B: 36.7 (#191)
Agentic & Tool Use GPT-5-Codex leads
GPT-5-Codex: 30.8 (#66), Qwen3 14B: 29.4 (#78)
| Benchmark | GPT-5-Codex | Qwen3 14B |
|---|---|---|
| Terminal-Bench | 44.3% | — |
| Berkeley Function Calling Leaderboard | — | 41% |
Reasoning GPT-5-Codex leads
GPT-5-Codex: 30.0 (#80), Qwen3 14B: 18.1 (#272)
| Benchmark | GPT-5-Codex | Qwen3 14B |
|---|---|---|
| Kagi LLM Benchmark | 70.3% | 49.1% |
| CritPt | — | 0% |
| Chess Puzzles | — | 4% |
| DTBench | — | 64% |
| LMCA | — | 18.2% |
| Epoch Capabilities Index | — | 138.23 |
Math Not comparable
GPT-5-Codex: —, Qwen3 14B: 37.0 (#102)
| Benchmark | GPT-5-Codex | Qwen3 14B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 66.4% |
Knowledge Not comparable
GPT-5-Codex: —, Qwen3 14B: 39.2 (#124)
| Benchmark | GPT-5-Codex | Qwen3 14B |
|---|---|---|
| GPQA Diamond | — | 63.8% |
| Vectara Hallucination Rate | — | 5.4% |
Long Context Not comparable
GPT-5-Codex: —, Qwen3 14B: 38.0 (#201)
| Benchmark | GPT-5-Codex | Qwen3 14B |
|---|---|---|
| Fiction.LiveBench | — | 62.5% |
Frequently asked questions
Is GPT-5-Codex better than Qwen3 14B?
GPT-5-Codex is the stronger model overall, scoring 37.3 to 35.0 on the Noometry Index. Qwen3 14B costs 5.6× less per token, which makes it the better buy when GPT-5-Codex's lead doesn't matter for your workload.
Which is cheaper, GPT-5-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-Codex lists at $1.25 and $10.
Is GPT-5-Codex or Qwen3 14B better for coding?
GPT-5-Codex scores higher on coding benchmarks: 41.9 versus 36.7 in the Noometry coding category.
Which has the bigger context window?
GPT-5-Codex does, with 400K tokens against 131K.
How many benchmarks do GPT-5-Codex and Qwen3 14B share?
1 benchmark has published results for both models. GPT-5-Codex has 3 scored results on Noometry and Qwen3 14B has 12.