# GPT-5.1-Codex vs Qwen3-Next 80B-A3B Instruct

> Qwen3-Next 80B-A3B Instruct is the stronger model overall, scoring 43.0 to 38.6 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gpt-5-1-codex-vs-qwen3-next-80b-a3b-instruct
- Last updated: 2026-10-12
- Shared benchmarks: 0

## Summary

- The widest gap is in math, where Qwen3-Next 80B-A3B Instruct leads 38.8 to 30.3.
- Qwen3-Next 80B-A3B Instruct is cheaper at $0.50 / $2 per million input/output tokens, against $1.25 / $10 for GPT-5.1-Codex.
- GPT-5.1-Codex accepts more context: 400K tokens versus 131K.
- Qwen3-Next 80B-A3B Instruct has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-5.1-Codex | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 38.6 | 43.0 |
| Rank | 186 | 102 |
| Context | 400K | 131K |
| Input $/M | $1.25 | $0.50 |
| Output $/M | $10 | $2 |
| Weights | Proprietary | Open |

## Coding

- GPT-5.1-Codex: 41.9 (#116)
- Qwen3-Next 80B-A3B Instruct: 42.5 (#98)

| Benchmark | GPT-5.1-Codex | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| SWE-bench Verified (bash only) | 66% | — |
| LMArena WebDev | 1337 | — |
| LMArena Coding | — | 1440 |
| ALE-Bench | 1,245 | — |

## Agentic & Tool Use

- GPT-5.1-Codex: 38.0 (#33)
- Qwen3-Next 80B-A3B Instruct: —

| Benchmark | GPT-5.1-Codex | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| Terminal-Bench | 60.4% | — |
| METR Time Horizons | 70.8% | — |

## Reasoning

- GPT-5.1-Codex: —
- Qwen3-Next 80B-A3B Instruct: 31.1 (#81)

| Benchmark | GPT-5.1-Codex | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| Kagi LLM Benchmark | — | 66.7% |
| LMArena Hard Prompts | — | 1428 |

## Math

- GPT-5.1-Codex: 30.3 (#235)
- Qwen3-Next 80B-A3B Instruct: 38.8 (#126)

| Benchmark | GPT-5.1-Codex | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| ProofBench | 9% | — |
| Omni-MATH | — | 46.7% |
| LMArena Math | — | 1440 |

## Knowledge

- GPT-5.1-Codex: —
- Qwen3-Next 80B-A3B Instruct: 41.8 (#106)

| Benchmark | GPT-5.1-Codex | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| MMLU-Pro | — | 78.6% |
| Vectara Hallucination Rate | — | 9.3% |
| GPQA (HELM) | — | 63% |
| LMArena Expert | — | 1417 |

## Multilingual

- GPT-5.1-Codex: —
- Qwen3-Next 80B-A3B Instruct: 52.1 (#93)

| Benchmark | GPT-5.1-Codex | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Non-English | — | 1407 |
| LMArena Chinese | — | 1460 |
| LMArena French | — | 1413 |
| LMArena German | — | 1417 |
| LMArena Japanese | — | 1395 |
| LMArena Korean | — | 1364 |
| LMArena Russian | — | 1404 |
| LMArena Spanish | — | 1435 |

## Instruction Following

- GPT-5.1-Codex: —
- Qwen3-Next 80B-A3B Instruct: 70.8 (#159)

| Benchmark | GPT-5.1-Codex | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| IFEval | — | 81% |
| LMArena Instruction Following | — | 1389 |

## Long Context

- GPT-5.1-Codex: —
- Qwen3-Next 80B-A3B Instruct: 37.0 (#223)

| Benchmark | GPT-5.1-Codex | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| Fiction.LiveBench | — | 55.6% |
| LMArena Longer Query | — | 1403 |

## Writing & Preference

- GPT-5.1-Codex: —
- Qwen3-Next 80B-A3B Instruct: 58.0 (#121)

| Benchmark | GPT-5.1-Codex | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Text | — | 1417 |
| LMArena Creative Writing | — | 1334 |
| WildBench | — | 80.7% |
| LMArena Multi-Turn | — | 1416 |

## FAQ

### Is GPT-5.1-Codex better than Qwen3-Next 80B-A3B Instruct?

Qwen3-Next 80B-A3B Instruct is the stronger model overall, scoring 43.0 to 38.6 on the Noometry Index.

### Which is cheaper, GPT-5.1-Codex or Qwen3-Next 80B-A3B Instruct?

Qwen3-Next 80B-A3B Instruct is cheaper. It lists at $0.50 per million input tokens and $2 per million output tokens; GPT-5.1-Codex lists at $1.25 and $10.

### Is GPT-5.1-Codex or Qwen3-Next 80B-A3B Instruct better for coding?

They score almost the same on coding (41.9 vs 42.5); test both on your own repository before choosing.

### Which has the bigger context window?

GPT-5.1-Codex does, with 400K tokens against 131K.

### How many benchmarks do GPT-5.1-Codex and Qwen3-Next 80B-A3B Instruct share?

0 benchmarks have published results for both models. GPT-5.1-Codex has 6 scored results on Noometry and Qwen3-Next 80B-A3B Instruct has 25.