# GPT-5.2 Codex vs Qwen3 14B

> GPT-5.2 Codex is the stronger model overall, scoring 42.2 to 35.0 on the Noometry Index. Qwen3 14B costs 7.9× less per token, which makes it the better buy when GPT-5.2 Codex's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gpt-5-2-codex-vs-qwen3-14b
- Last updated: 2026-10-10
- Shared benchmarks: 0

## Summary

- The widest gap is in agentic & tool use, where GPT-5.2 Codex leads 40.7 to 29.4.
- Qwen3 14B is cheaper at $0.35 / $1.40 per million input/output tokens, against $1.75 / $14 for GPT-5.2 Codex.
- GPT-5.2 Codex accepts more context: 400K tokens versus 131K.
- Qwen3 14B has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-5.2 Codex | Qwen3 14B |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 42.2 | 35.0 |
| Rank | 107 | 222 |
| Context | 400K | 131K |
| Input $/M | $1.75 | $0.35 |
| Output $/M | $14 | $1.40 |
| Weights | Proprietary | Open |

## Coding

- GPT-5.2 Codex: 45.4 (#66)
- Qwen3 14B: 36.7 (#191)

| Benchmark | GPT-5.2 Codex | Qwen3 14B |
|---|---|---|
| SWE-bench Verified (bash only) | 72.8% | — |
| LMArena WebDev | 1339 | — |
| SWE-bench Multilingual | 66.3% | — |
| SciCode | — | 31.6% |
| ALE-Bench | 1,300 | — |

## Agentic & Tool Use

- GPT-5.2 Codex: 40.7 (#20)
- Qwen3 14B: 29.4 (#78)

| Benchmark | GPT-5.2 Codex | Qwen3 14B |
|---|---|---|
| Terminal-Bench | 66.5% | — |
| Berkeley Function Calling Leaderboard | — | 41% |

## Reasoning

- GPT-5.2 Codex: —
- Qwen3 14B: 18.1 (#272)

| Benchmark | GPT-5.2 Codex | Qwen3 14B |
|---|---|---|
| Kagi LLM Benchmark | — | 49.1% |
| CritPt | — | 0% |
| Chess Puzzles | — | 4% |
| DTBench | — | 64% |
| LMCA | — | 18.2% |
| Epoch Capabilities Index | — | 138.23 |

## Math

- GPT-5.2 Codex: —
- Qwen3 14B: 37.0 (#102)

| Benchmark | GPT-5.2 Codex | Qwen3 14B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 66.4% |

## Knowledge

- GPT-5.2 Codex: —
- Qwen3 14B: 39.2 (#124)

| Benchmark | GPT-5.2 Codex | Qwen3 14B |
|---|---|---|
| GPQA Diamond | — | 63.8% |
| Vectara Hallucination Rate | — | 5.4% |

## Long Context

- GPT-5.2 Codex: —
- Qwen3 14B: 38.0 (#201)

| Benchmark | GPT-5.2 Codex | Qwen3 14B |
|---|---|---|
| Fiction.LiveBench | — | 62.5% |

## FAQ

### Is GPT-5.2 Codex better than Qwen3 14B?

GPT-5.2 Codex is the stronger model overall, scoring 42.2 to 35.0 on the Noometry Index. Qwen3 14B costs 7.9× less per token, which makes it the better buy when GPT-5.2 Codex's lead doesn't matter for your workload.

### Which is cheaper, GPT-5.2 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-5.2 Codex lists at $1.75 and $14.

### Is GPT-5.2 Codex or Qwen3 14B better for coding?

GPT-5.2 Codex scores higher on coding benchmarks: 45.4 versus 36.7 in the Noometry coding category.

### Which has the bigger context window?

GPT-5.2 Codex does, with 400K tokens against 131K.

### How many benchmarks do GPT-5.2 Codex and Qwen3 14B share?

0 benchmarks have published results for both models. GPT-5.2 Codex has 5 scored results on Noometry and Qwen3 14B has 12.