Model comparison
GPT-5.2 Codex vs Qwen3-Next 80B-A3B Instruct
GPT-5.2 Codex and Qwen3-Next 80B-A3B Instruct score almost the same on the Noometry Index (42.6 vs 43.0), so choose on price, context window or the category you care about most.
Last verified . 0 shared benchmarks.
Alibaba (Qwen)Summary
- The widest gap is in coding, where GPT-5.2 Codex leads 45.5 to 42.5.
- Qwen3-Next 80B-A3B Instruct is cheaper at $0.50 / $2 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-Next 80B-A3B Instruct has downloadable open weights; the other is API-only.
Side by side
| GPT-5.2 Codex | Qwen3-Next 80B-A3B Instruct | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 42.6 | 43.0 |
| Released | 2025-12-18 | 2025-09 |
| Weights | Proprietary | Open |
| Context window | 400K | 131K |
| Max output | 128K | 33K |
| Input $ / M tokens | $1.75 | $0.50 |
| Output $ / M tokens | $14 | $2 |
| Results tracked | 5 | 25 |
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Category by category
Coding GPT-5.2 Codex leads
GPT-5.2 Codex: 45.5 (#71), Qwen3-Next 80B-A3B Instruct: 42.5 (#98)
| Benchmark | GPT-5.2 Codex | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| SWE-bench Verified (bash only) | 72.8% | — |
| LMArena WebDev | 1339 | — |
| SWE-bench Multilingual | 66.3% | — |
| LMArena Coding | — | 1440 |
| ALE-Bench | 1,300 | — |
Agentic & Tool Use Not comparable
GPT-5.2 Codex: 41.0 (#22), Qwen3-Next 80B-A3B Instruct: —
| Benchmark | GPT-5.2 Codex | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| Terminal-Bench | 66.5% | — |
Reasoning Not comparable
GPT-5.2 Codex: —, Qwen3-Next 80B-A3B Instruct: 31.1 (#81)
| Benchmark | GPT-5.2 Codex | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| Kagi LLM Benchmark | — | 66.7% |
| LMArena Hard Prompts | — | 1428 |
Math Not comparable
GPT-5.2 Codex: —, Qwen3-Next 80B-A3B Instruct: 38.8 (#126)
| Benchmark | GPT-5.2 Codex | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| Omni-MATH | — | 46.7% |
| LMArena Math | — | 1440 |
Knowledge Not comparable
GPT-5.2 Codex: —, Qwen3-Next 80B-A3B Instruct: 41.8 (#106)
| Benchmark | GPT-5.2 Codex | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| MMLU-Pro | — | 78.6% |
| Vectara Hallucination Rate | — | 9.3% |
| GPQA (HELM) | — | 63% |
| LMArena Expert | — | 1417 |
Multilingual Not comparable
GPT-5.2 Codex: —, Qwen3-Next 80B-A3B Instruct: 52.1 (#93)
| Benchmark | GPT-5.2 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 Not comparable
GPT-5.2 Codex: —, Qwen3-Next 80B-A3B Instruct: 70.8 (#159)
| Benchmark | GPT-5.2 Codex | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| IFEval | — | 81% |
| LMArena Instruction Following | — | 1389 |
Long Context Not comparable
GPT-5.2 Codex: —, Qwen3-Next 80B-A3B Instruct: 37.0 (#223)
| Benchmark | GPT-5.2 Codex | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| Fiction.LiveBench | — | 55.6% |
| LMArena Longer Query | — | 1403 |
Writing & Preference Not comparable
GPT-5.2 Codex: —, Qwen3-Next 80B-A3B Instruct: 58.0 (#121)
| Benchmark | GPT-5.2 Codex | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Text | — | 1417 |
| LMArena Creative Writing | — | 1334 |
| WildBench | — | 80.7% |
| LMArena Multi-Turn | — | 1416 |
Frequently asked questions
Is GPT-5.2 Codex better than Qwen3-Next 80B-A3B Instruct?
GPT-5.2 Codex and Qwen3-Next 80B-A3B Instruct score almost the same on the Noometry Index (42.6 vs 43.0), so choose on price, context window or the category you care about most.
Which is cheaper, GPT-5.2 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-5.2 Codex lists at $1.75 and $14.
Is GPT-5.2 Codex or Qwen3-Next 80B-A3B Instruct better for coding?
GPT-5.2 Codex scores higher on coding benchmarks: 45.5 versus 42.5 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-Next 80B-A3B Instruct share?
0 benchmarks have published results for both models. GPT-5.2 Codex has 5 scored results on Noometry and Qwen3-Next 80B-A3B Instruct has 25.