Model comparison
Mixtral 8x22B vs Qwen1.5 4b Chat
Qwen1.5 4b Chat is the stronger model overall, scoring 28.8 to 27.1 on the Noometry Index.
Last verified . 13 shared benchmarks.
Mistral AI
Alibaba (Qwen)Summary
- They share 13 benchmarks with published results for both. Mixtral 8x22B scores higher in 5 categories and Qwen1.5 4b Chat in 3 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Mixtral 8x22B leads 36.9 to 23.8.
Side by side
| Mixtral 8x22B | Qwen1.5 4b Chat | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 27.1 | 28.8 |
| Released | 2024-04-17 | — |
| Weights | Open | Open |
| Context window | 64K | — |
| Max output | 64K | — |
| Input $ / M tokens | $2 | — |
| Output $ / M tokens | $6 | — |
| Results tracked | 34 | 13 |
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Category by category
Coding Qwen1.5 4b Chat leads
Mixtral 8x22B: 24.2 (#329), Qwen1.5 4b Chat: 29.1 (#308)
| Benchmark | Mixtral 8x22B | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Coding | 1166 | 999 |
| 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), Qwen1.5 4b Chat: —
| Benchmark | Mixtral 8x22B | Qwen1.5 4b Chat |
|---|---|---|
| Cybench | 7.5% | — |
Reasoning Mixtral 8x22B leads
Mixtral 8x22B: 19.9 (#248), Qwen1.5 4b Chat: 18.5 (#279)
| Benchmark | Mixtral 8x22B | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Hard Prompts | 1150 | 976 |
| DTBench | 55.1% | — |
| Epoch Capabilities Index | 122.03 | — |
| ForecastBench | 56.3 | — |
Math Qwen1.5 4b Chat leads
Mixtral 8x22B: 22.9 (#275), Qwen1.5 4b Chat: 30.4 (#234)
| Benchmark | Mixtral 8x22B | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Math | 1184 | 1026 |
| Omni-MATH | 16.3% | — |
| MATH Level 5 | 24.2% | — |
Knowledge Qwen1.5 4b Chat leads
Mixtral 8x22B: 15.1 (#293), Qwen1.5 4b Chat: 26.7 (#255)
| Benchmark | Mixtral 8x22B | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Expert | 1113 | 980 |
| GPQA Diamond | 34.1% | — |
| MMLU-Pro | 46% | — |
| GPQA (HELM) | 33.4% | — |
| MMLU | 77.8% | — |
Multilingual Mixtral 8x22B leads
Mixtral 8x22B: 32.8 (#255), Qwen1.5 4b Chat: 24.1 (#290)
| Benchmark | Mixtral 8x22B | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Non-English | 1128 | 979 |
| LMArena Chinese | 1116 | 1024 |
| LMArena German | 1141 | 902 |
| LMArena Russian | 1158 | 952 |
| LMArena French | 1166 | — |
| LMArena Japanese | 1037 | — |
| LMArena Korean | 1057 | — |
| LMArena Spanish | 1151 | — |
Instruction Following Mixtral 8x22B leads
Mixtral 8x22B: 57.7 (#266), Qwen1.5 4b Chat: 49.0 (#300)
| Benchmark | Mixtral 8x22B | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Instruction Following | 1147 | 978 |
| IFEval | 72.4% | — |
Long Context Mixtral 8x22B leads
Mixtral 8x22B: 34.7 (#247), Qwen1.5 4b Chat: 30.1 (#290)
| Benchmark | Mixtral 8x22B | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Longer Query | 1144 | 988 |
Writing & Preference Mixtral 8x22B leads
Mixtral 8x22B: 36.9 (#262), Qwen1.5 4b Chat: 23.8 (#309)
| Benchmark | Mixtral 8x22B | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Text | 1162 | 997 |
| LMArena Creative Writing | 1141 | 969 |
| LMArena Multi-Turn | 1130 | 977 |
| WildBench | 71.1% | — |
Frequently asked questions
Is Mixtral 8x22B better than Qwen1.5 4b Chat?
Qwen1.5 4b Chat is the stronger model overall, scoring 28.8 to 27.1 on the Noometry Index.
Is Mixtral 8x22B or Qwen1.5 4b Chat better for coding?
Qwen1.5 4b Chat scores higher on coding benchmarks: 29.1 versus 24.2 in the Noometry coding category.
How many benchmarks do Mixtral 8x22B and Qwen1.5 4b Chat share?
13 benchmarks have published results for both models. Mixtral 8x22B has 34 scored results on Noometry and Qwen1.5 4b Chat has 13.