Model comparison
Mixtral 8x7B vs Qwen3.6 27B
Qwen3.6 27B is the stronger model overall, scoring 42.2 to 27.1 on the Noometry Index. Mixtral 8x7B costs 1.9× less per token, which makes it the better buy when Qwen3.6 27B's lead doesn't matter for your workload.
Last verified . 3 shared benchmarks.
Mistral AI
Alibaba (Qwen)Summary
- They share 3 benchmarks with published results for both. Mixtral 8x7B scores higher in 0 categories and Qwen3.6 27B in 5 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3.6 27B leads 52.4 to 11.0.
- The biggest single-benchmark swing is GPQA Diamond: 30.6% for Mixtral 8x7B and 85.9% for Qwen3.6 27B.
- Mixtral 8x7B is cheaper at $0.70 / $0.70 per million input/output tokens, against $0.60 / $3.60 for Qwen3.6 27B.
- Qwen3.6 27B accepts more context: 262K tokens versus 32K.
Side by side
| Mixtral 8x7B | Qwen3.6 27B | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 27.1 | 42.2 |
| Released | 2023-12-11 | 2026-04-22 |
| Weights | Open | Open |
| Context window | 32K | 262K |
| Max output | 32K | 66K |
| Input $ / M tokens | $0.70 | $0.60 |
| Output $ / M tokens | $0.70 | $3.60 |
| Results tracked | 38 | 11 |
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Category by category
Coding Qwen3.6 27B leads
Mixtral 8x7B: 32.8 (#269), Qwen3.6 27B: 39.1 (#163)
| Benchmark | Mixtral 8x7B | Qwen3.6 27B |
|---|---|---|
| SciCode | — | 37.3% |
| LMArena Coding | 1126 | — |
| HumanEval+ | 39.6% | — |
| MBPP+ | 49.7% | — |
Reasoning Qwen3.6 27B leads
Mixtral 8x7B: 18.2 (#285), Qwen3.6 27B: 25.0 (#153)
| Benchmark | Mixtral 8x7B | Qwen3.6 27B |
|---|---|---|
| DTBench | 49.6% | 78.1% |
| Epoch Capabilities Index | 118.47 | 146.5 |
| CritPt | — | 0.9% |
| Chess Puzzles | — | 22% |
| LMArena Hard Prompts | 1115 | — |
| Mystery Game Puzzles | — | 7% |
| LMCA | — | 34.5% |
| Adversarial NLI | 55.2% | — |
| ForecastBench | 56.3 | — |
| HellaSwag | 86.7% | — |
| PIQA | 83.6% | — |
| WinoGrande | 77.2% | — |
Math Qwen3.6 27B leads
Mixtral 8x7B: 18.8 (#289), Qwen3.6 27B: 48.5 (#62)
| Benchmark | Mixtral 8x7B | Qwen3.6 27B |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 35.1% |
| OTIS Mock AIME 2024-2025 | — | 91.1% |
| Omni-MATH | 10.5% | — |
| LMArena Math | 1147 | — |
| MATH Level 5 | 10% | — |
| GSM8K | 74.4% | — |
Knowledge Qwen3.6 27B leads
Mixtral 8x7B: 11.0 (#301), Qwen3.6 27B: 52.4 (#63)
| Benchmark | Mixtral 8x7B | Qwen3.6 27B |
|---|---|---|
| GPQA Diamond | 30.6% | 85.9% |
| MMLU-Pro | 33.5% | — |
| GPQA (HELM) | 29.6% | — |
| LMArena Expert | 1088 | — |
| ARC (AI2) Challenge | 87.3% | — |
| MMLU | 70.6% | — |
| OpenBookQA | 85.8% | — |
| TriviaQA | 82.2% | — |
Multilingual Not comparable
Mixtral 8x7B: 29.6 (#266), Qwen3.6 27B: —
| Benchmark | Mixtral 8x7B | Qwen3.6 27B |
|---|---|---|
| LMArena Non-English | 1077 | — |
| LMArena Chinese | 1055 | — |
| LMArena French | 1166 | — |
| LMArena German | 1114 | — |
| LMArena Japanese | 931 | — |
| LMArena Korean | 968 | — |
| LMArena Russian | 1090 | — |
| LMArena Spanish | 1111 | — |
Instruction Following Not comparable
Mixtral 8x7B: 51.0 (#297), Qwen3.6 27B: —
| Benchmark | Mixtral 8x7B | Qwen3.6 27B |
|---|---|---|
| IFEval | 57.5% | — |
| LMArena Instruction Following | 1109 | — |
Long Context Not comparable
Mixtral 8x7B: 33.4 (#260), Qwen3.6 27B: —
| Benchmark | Mixtral 8x7B | Qwen3.6 27B |
|---|---|---|
| LMArena Longer Query | 1103 | — |
Writing & Preference Qwen3.6 27B leads
Mixtral 8x7B: 34.2 (#270), Qwen3.6 27B: 50.3 (#181)
| Benchmark | Mixtral 8x7B | Qwen3.6 27B |
|---|---|---|
| LMArena Text | 1132 | — |
| LMArena Creative Writing | 1109 | — |
| WildBench | 67.3% | — |
| EQ-Bench 4 | — | 1026 |
| LMArena Multi-Turn | 1115 | — |
Frequently asked questions
Is Mixtral 8x7B better than Qwen3.6 27B?
Qwen3.6 27B is the stronger model overall, scoring 42.2 to 27.1 on the Noometry Index. Mixtral 8x7B costs 1.9× less per token, which makes it the better buy when Qwen3.6 27B's lead doesn't matter for your workload.
Which is cheaper, Mixtral 8x7B or Qwen3.6 27B?
Mixtral 8x7B is cheaper. It lists at $0.70 per million input tokens and $0.70 per million output tokens; Qwen3.6 27B lists at $0.60 and $3.60.
Is Mixtral 8x7B or Qwen3.6 27B better for coding?
Qwen3.6 27B scores higher on coding benchmarks: 39.1 versus 32.8 in the Noometry coding category.
Which has the bigger context window?
Qwen3.6 27B does, with 262K tokens against 32K.
How many benchmarks do Mixtral 8x7B and Qwen3.6 27B share?
3 benchmarks have published results for both models. Mixtral 8x7B has 38 scored results on Noometry and Qwen3.6 27B has 11.