# GPT-5-Codex vs Qwen3.8 27B

> Qwen3.8 27B is the stronger model overall, scoring 45.3 to 37.3 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gpt-5-codex-vs-qwen3-8-27b
- Last updated: 2026-10-10
- Shared benchmarks: 0

## Summary

- The widest gap is in coding, where Qwen3.8 27B leads 50.3 to 41.9.
- Qwen3.8 27B is cheaper at $0.99 / $1.49 per million input/output tokens, against $1.25 / $10 for GPT-5-Codex.
- GPT-5-Codex accepts more context: 400K tokens versus 262K.
- Qwen3.8 27B has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-5-Codex | Qwen3.8 27B |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 37.3 | 45.3 |
| Rank | 190 | 64 |
| Context | 400K | 262K |
| Input $/M | $1.25 | $0.99 |
| Output $/M | $10 | $1.49 |
| Weights | Proprietary | Open |

## Coding

- GPT-5-Codex: 41.9 (#100)
- Qwen3.8 27B: 50.3 (#42)

| Benchmark | GPT-5-Codex | Qwen3.8 27B |
|---|---|---|
| LMArena WebDev | — | 1592 |
| SciCode | — | 46.6% |
| WeirdML | 54.5% | — |
| LMArena Coding | — | 1487 |

## Agentic & Tool Use

- GPT-5-Codex: 30.8 (#66)
- Qwen3.8 27B: —

| Benchmark | GPT-5-Codex | Qwen3.8 27B |
|---|---|---|
| Terminal-Bench | 44.3% | — |

## Reasoning

- GPT-5-Codex: 30.0 (#80)
- Qwen3.8 27B: 31.5 (#71)

| Benchmark | GPT-5-Codex | Qwen3.8 27B |
|---|---|---|
| Kagi LLM Benchmark | 70.3% | — |
| NYT Connections (extended) | — | 54.5% |
| CritPt | — | 5.4% |
| LMArena Hard Prompts | — | 1459 |
| DTBench | — | 88% |
| LMCA | — | 41.4% |
| Surface Evolver Bench | — | 45% |
| Epoch Capabilities Index | — | 149.38 |

## Math

- GPT-5-Codex: —
- Qwen3.8 27B: 35.7 (#139)

| Benchmark | GPT-5-Codex | Qwen3.8 27B |
|---|---|---|
| ProofBench | — | 16% |
| LMArena Math | — | 1453 |

## Knowledge

- GPT-5-Codex: —
- Qwen3.8 27B: 40.9 (#105)

| Benchmark | GPT-5-Codex | Qwen3.8 27B |
|---|---|---|
| LMArena Expert | — | 1482 |

## Multimodal

- GPT-5-Codex: —
- Qwen3.8 27B: 40.5 (#36)

| Benchmark | GPT-5-Codex | Qwen3.8 27B |
|---|---|---|
| LMArena Vision | — | 1270 |

## Multilingual

- GPT-5-Codex: —
- Qwen3.8 27B: 54.0 (#54)

| Benchmark | GPT-5-Codex | Qwen3.8 27B |
|---|---|---|
| LMArena Non-English | — | 1431 |
| LMArena Chinese | — | 1504 |
| LMArena French | — | 1468 |
| LMArena German | — | 1435 |
| LMArena Japanese | — | 1392 |
| LMArena Korean | — | 1389 |
| LMArena Russian | — | 1421 |
| LMArena Spanish | — | 1444 |

## Instruction Following

- GPT-5-Codex: —
- Qwen3.8 27B: 75.8 (#54)

| Benchmark | GPT-5-Codex | Qwen3.8 27B |
|---|---|---|
| LMArena Instruction Following | — | 1436 |

## Long Context

- GPT-5-Codex: —
- Qwen3.8 27B: 44.3 (#66)

| Benchmark | GPT-5-Codex | Qwen3.8 27B |
|---|---|---|
| LMArena Longer Query | — | 1448 |

## Writing & Preference

- GPT-5-Codex: —
- Qwen3.8 27B: 65.9 (#41)

| Benchmark | GPT-5-Codex | Qwen3.8 27B |
|---|---|---|
| LMArena Text | — | 1441 |
| LMArena Creative Writing | — | 1382 |
| EQ-Bench Creative Writing | — | 1671 |
| LMArena Multi-Turn | — | 1443 |

## FAQ

### Is GPT-5-Codex better than Qwen3.8 27B?

Qwen3.8 27B is the stronger model overall, scoring 45.3 to 37.3 on the Noometry Index.

### Which is cheaper, GPT-5-Codex or Qwen3.8 27B?

Qwen3.8 27B is cheaper. It lists at $0.99 per million input tokens and $1.49 per million output tokens; GPT-5-Codex lists at $1.25 and $10.

### Is GPT-5-Codex or Qwen3.8 27B better for coding?

Qwen3.8 27B scores higher on coding benchmarks: 50.3 versus 41.9 in the Noometry coding category.

### Which has the bigger context window?

GPT-5-Codex does, with 400K tokens against 262K.

### How many benchmarks do GPT-5-Codex and Qwen3.8 27B share?

0 benchmarks have published results for both models. GPT-5-Codex has 3 scored results on Noometry and Qwen3.8 27B has 28.