Model comparison
Mixtral 8x22B vs Qwen3-Next 80B-A3B Instruct
Qwen3-Next 80B-A3B Instruct is the stronger model overall, scoring 43.0 to 27.1 on the Noometry Index.
Last verified . 22 shared benchmarks.
Mistral AI
Alibaba (Qwen)Summary
- They share 22 benchmarks with published results for both. Mixtral 8x22B scores higher in 0 categories and Qwen3-Next 80B-A3B Instruct in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3-Next 80B-A3B Instruct leads 41.8 to 15.1.
- The biggest single-benchmark swing is MMLU-Pro: 46% for Mixtral 8x22B and 78.6% for Qwen3-Next 80B-A3B Instruct.
- Qwen3-Next 80B-A3B Instruct is cheaper at $0.50 / $2 per million input/output tokens, against $2 / $6 for Mixtral 8x22B.
- Qwen3-Next 80B-A3B Instruct accepts more context: 131K tokens versus 64K.
Side by side
| Mixtral 8x22B | Qwen3-Next 80B-A3B Instruct | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 27.1 | 43.0 |
| Released | 2024-04-17 | 2025-09 |
| Weights | Open | Open |
| Context window | 64K | 131K |
| Max output | 64K | 33K |
| Input $ / M tokens | $2 | $0.50 |
| Output $ / M tokens | $6 | $2 |
| Results tracked | 34 | 25 |
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Category by category
Coding Qwen3-Next 80B-A3B Instruct leads
Mixtral 8x22B: 24.2 (#329), Qwen3-Next 80B-A3B Instruct: 42.5 (#98)
| Benchmark | Mixtral 8x22B | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Coding | 1166 | 1440 |
| WeirdML | 3.2% | — |
| BigCodeBench Instruct | 40.6% | — |
| BigCodeBench Complete | 50.2% | — |
| HumanEval+ | 72% | — |
| MBPP+ | 64.3% | — |
Agentic & Tool Use Not comparable
Mixtral 8x22B: 23.1 (#127), Qwen3-Next 80B-A3B Instruct: —
| Benchmark | Mixtral 8x22B | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| Cybench | 7.5% | — |
Reasoning Qwen3-Next 80B-A3B Instruct leads
Mixtral 8x22B: 19.9 (#248), Qwen3-Next 80B-A3B Instruct: 31.1 (#81)
| Benchmark | Mixtral 8x22B | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Hard Prompts | 1150 | 1428 |
| Kagi LLM Benchmark | — | 66.7% |
| DTBench | 55.1% | — |
| Epoch Capabilities Index | 122.03 | — |
| ForecastBench | 56.3 | — |
Math Qwen3-Next 80B-A3B Instruct leads
Mixtral 8x22B: 22.9 (#275), Qwen3-Next 80B-A3B Instruct: 38.8 (#126)
| Benchmark | Mixtral 8x22B | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| Omni-MATH | 16.3% | 46.7% |
| LMArena Math | 1184 | 1440 |
| MATH Level 5 | 24.2% | — |
Knowledge Qwen3-Next 80B-A3B Instruct leads
Mixtral 8x22B: 15.1 (#293), Qwen3-Next 80B-A3B Instruct: 41.8 (#106)
| Benchmark | Mixtral 8x22B | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| MMLU-Pro | 46% | 78.6% |
| GPQA (HELM) | 33.4% | 63% |
| LMArena Expert | 1113 | 1417 |
| GPQA Diamond | 34.1% | — |
| Vectara Hallucination Rate | — | 9.3% |
| MMLU | 77.8% | — |
Multilingual Qwen3-Next 80B-A3B Instruct leads
Mixtral 8x22B: 32.8 (#255), Qwen3-Next 80B-A3B Instruct: 52.1 (#93)
| Benchmark | Mixtral 8x22B | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Non-English | 1128 | 1407 |
| LMArena Chinese | 1116 | 1460 |
| LMArena French | 1166 | 1413 |
| LMArena German | 1141 | 1417 |
| LMArena Japanese | 1037 | 1395 |
| LMArena Korean | 1057 | 1364 |
| LMArena Russian | 1158 | 1404 |
| LMArena Spanish | 1151 | 1435 |
Instruction Following Qwen3-Next 80B-A3B Instruct leads
Mixtral 8x22B: 57.7 (#266), Qwen3-Next 80B-A3B Instruct: 70.8 (#159)
| Benchmark | Mixtral 8x22B | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| IFEval | 72.4% | 81% |
| LMArena Instruction Following | 1147 | 1389 |
Long Context Qwen3-Next 80B-A3B Instruct leads
Mixtral 8x22B: 34.7 (#247), Qwen3-Next 80B-A3B Instruct: 37.0 (#223)
| Benchmark | Mixtral 8x22B | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Longer Query | 1144 | 1403 |
| Fiction.LiveBench | — | 55.6% |
Writing & Preference Qwen3-Next 80B-A3B Instruct leads
Mixtral 8x22B: 36.9 (#262), Qwen3-Next 80B-A3B Instruct: 58.0 (#121)
| Benchmark | Mixtral 8x22B | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Text | 1162 | 1417 |
| LMArena Creative Writing | 1141 | 1334 |
| WildBench | 71.1% | 80.7% |
| LMArena Multi-Turn | 1130 | 1416 |
Frequently asked questions
Is Mixtral 8x22B better than Qwen3-Next 80B-A3B Instruct?
Qwen3-Next 80B-A3B Instruct is the stronger model overall, scoring 43.0 to 27.1 on the Noometry Index.
Which is cheaper, Mixtral 8x22B 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; Mixtral 8x22B lists at $2 and $6.
Is Mixtral 8x22B or Qwen3-Next 80B-A3B Instruct better for coding?
Qwen3-Next 80B-A3B Instruct scores higher on coding benchmarks: 42.5 versus 24.2 in the Noometry coding category.
Which has the bigger context window?
Qwen3-Next 80B-A3B Instruct does, with 131K tokens against 64K.
How many benchmarks do Mixtral 8x22B and Qwen3-Next 80B-A3B Instruct share?
22 benchmarks have published results for both models. Mixtral 8x22B has 34 scored results on Noometry and Qwen3-Next 80B-A3B Instruct has 25.