# GPT-5.2 Codex vs Qwen2.5 7B Instruct

> GPT-5.2 Codex is the stronger model overall, scoring 42.2 to 28.6 on the Noometry Index. Qwen2.5 7B Instruct costs 16× 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-qwen2-5-7b-instruct
- 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 23.5.
- Qwen2.5 7B Instruct is cheaper at $0.17 / $0.70 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.
- Qwen2.5 7B Instruct has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-5.2 Codex | Qwen2.5 7B Instruct |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 42.2 | 28.6 |
| Rank | 107 | 314 |
| Context | 400K | 131K |
| Input $/M | $1.75 | $0.17 |
| Output $/M | $14 | $0.70 |
| Weights | Proprietary | Open |

## Coding

- GPT-5.2 Codex: 45.4 (#66)
- Qwen2.5 7B Instruct: 35.9 (#204)

| Benchmark | GPT-5.2 Codex | Qwen2.5 7B Instruct |
|---|---|---|
| SWE-bench Verified (bash only) | 72.8% | — |
| LMArena WebDev | 1339 | — |
| SWE-bench Multilingual | 66.3% | — |
| BigCodeBench Instruct | — | 37.6% |
| BigCodeBench Complete | — | 46.1% |
| ALE-Bench | 1,300 | — |

## Agentic & Tool Use

- GPT-5.2 Codex: 40.7 (#20)
- Qwen2.5 7B Instruct: 23.5 (#117)

| Benchmark | GPT-5.2 Codex | Qwen2.5 7B Instruct |
|---|---|---|
| Terminal-Bench | 66.5% | — |
| BALROG | — | 7.8% |

## Reasoning

- GPT-5.2 Codex: —
- Qwen2.5 7B Instruct: 14.3 (#317)

| Benchmark | GPT-5.2 Codex | Qwen2.5 7B Instruct |
|---|---|---|
| Chess Puzzles | — | 0% |
| DTBench | — | 47.7% |
| LMCA | — | 6.4% |
| Epoch Capabilities Index | — | 118.44 |

## Math

- GPT-5.2 Codex: —
- Qwen2.5 7B Instruct: 11.8 (#300)

| Benchmark | GPT-5.2 Codex | Qwen2.5 7B Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 2.5% |
| Omni-MATH | — | 29.4% |

## Knowledge

- GPT-5.2 Codex: —
- Qwen2.5 7B Instruct: 17.0 (#281)

| Benchmark | GPT-5.2 Codex | Qwen2.5 7B Instruct |
|---|---|---|
| GPQA Diamond | — | 35.5% |
| MMLU-Pro | — | 53.9% |
| GPQA (HELM) | — | 34.1% |
| MMLU | — | 72.9% |

## Instruction Following

- GPT-5.2 Codex: —
- Qwen2.5 7B Instruct: 63.4 (#226)

| Benchmark | GPT-5.2 Codex | Qwen2.5 7B Instruct |
|---|---|---|
| IFEval | — | 74.1% |

## Writing & Preference

- GPT-5.2 Codex: —
- Qwen2.5 7B Instruct: 48.8 (#194)

| Benchmark | GPT-5.2 Codex | Qwen2.5 7B Instruct |
|---|---|---|
| WildBench | — | 73.1% |

## FAQ

### Is GPT-5.2 Codex better than Qwen2.5 7B Instruct?

GPT-5.2 Codex is the stronger model overall, scoring 42.2 to 28.6 on the Noometry Index. Qwen2.5 7B Instruct costs 16× 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 Qwen2.5 7B Instruct?

Qwen2.5 7B Instruct is cheaper. It lists at $0.17 per million input tokens and $0.70 per million output tokens; GPT-5.2 Codex lists at $1.75 and $14.

### Is GPT-5.2 Codex or Qwen2.5 7B Instruct better for coding?

GPT-5.2 Codex scores higher on coding benchmarks: 45.4 versus 35.9 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 Qwen2.5 7B Instruct share?

0 benchmarks have published results for both models. GPT-5.2 Codex has 5 scored results on Noometry and Qwen2.5 7B Instruct has 15.