Model comparison
Mixtral 8x7B vs Solar Pro4
Solar Pro4 is the stronger model overall, scoring 42.1 to 27.1 on the Noometry Index.
Last verified . 17 shared benchmarks.
Summary
- They share 17 benchmarks with published results for both. Mixtral 8x7B scores higher in 0 categories and Solar Pro4 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Solar Pro4 leads 39.8 to 11.0.
- Solar Pro4 is cheaper at $0.30 / $1.20 per million input/output tokens, against $0.70 / $0.70 for Mixtral 8x7B.
- Solar Pro4 accepts more context: 524K tokens versus 32K.
- Mixtral 8x7B has downloadable open weights; the other is API-only.
Side by side
| Mixtral 8x7B | Solar Pro4 | |
|---|---|---|
| Provider | Mistral AI | Upstage |
| Noometry Index | 27.1 | 42.1 |
| Released | 2023-12-11 | 2026-08-06 |
| Weights | Open | Proprietary |
| Context window | 32K | 524K |
| Max output | 32K | 131K |
| Input $ / M tokens | $0.70 | $0.30 |
| Output $ / M tokens | $0.70 | $1.20 |
| Results tracked | 38 | 18 |
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Category by category
Coding Solar Pro4 leads
Mixtral 8x7B: 32.8 (#269), Solar Pro4: 40.1 (#149)
| Benchmark | Mixtral 8x7B | Solar Pro4 |
|---|---|---|
| LMArena Coding | 1126 | 1437 |
| LMArena WebDev | — | 1371 |
| HumanEval+ | 39.6% | — |
| MBPP+ | 49.7% | — |
Reasoning Solar Pro4 leads
Mixtral 8x7B: 18.2 (#285), Solar Pro4: 28.5 (#104)
| Benchmark | Mixtral 8x7B | Solar Pro4 |
|---|---|---|
| LMArena Hard Prompts | 1115 | 1399 |
| DTBench | 49.6% | — |
| Adversarial NLI | 55.2% | — |
| Epoch Capabilities Index | 118.47 | — |
| ForecastBench | 56.3 | — |
| HellaSwag | 86.7% | — |
| PIQA | 83.6% | — |
| WinoGrande | 77.2% | — |
Math Solar Pro4 leads
Mixtral 8x7B: 18.8 (#289), Solar Pro4: 38.8 (#128)
| Benchmark | Mixtral 8x7B | Solar Pro4 |
|---|---|---|
| LMArena Math | 1147 | 1416 |
| Omni-MATH | 10.5% | — |
| MATH Level 5 | 10% | — |
| GSM8K | 74.4% | — |
Knowledge Solar Pro4 leads
Mixtral 8x7B: 11.0 (#301), Solar Pro4: 39.8 (#129)
| Benchmark | Mixtral 8x7B | Solar Pro4 |
|---|---|---|
| LMArena Expert | 1088 | 1427 |
| GPQA Diamond | 30.6% | — |
| MMLU-Pro | 33.5% | — |
| GPQA (HELM) | 29.6% | — |
| ARC (AI2) Challenge | 87.3% | — |
| MMLU | 70.6% | — |
| OpenBookQA | 85.8% | — |
| TriviaQA | 82.2% | — |
Multilingual Solar Pro4 leads
Mixtral 8x7B: 29.6 (#266), Solar Pro4: 48.7 (#139)
| Benchmark | Mixtral 8x7B | Solar Pro4 |
|---|---|---|
| LMArena Non-English | 1077 | 1361 |
| LMArena Chinese | 1055 | 1415 |
| LMArena French | 1166 | 1397 |
| LMArena German | 1114 | 1364 |
| LMArena Japanese | 931 | 1309 |
| LMArena Korean | 968 | 1382 |
| LMArena Russian | 1090 | 1360 |
| LMArena Spanish | 1111 | 1401 |
Instruction Following Solar Pro4 leads
Mixtral 8x7B: 51.0 (#297), Solar Pro4: 72.7 (#132)
| Benchmark | Mixtral 8x7B | Solar Pro4 |
|---|---|---|
| LMArena Instruction Following | 1109 | 1377 |
| IFEval | 57.5% | — |
Long Context Solar Pro4 leads
Mixtral 8x7B: 33.4 (#260), Solar Pro4: 42.1 (#130)
| Benchmark | Mixtral 8x7B | Solar Pro4 |
|---|---|---|
| LMArena Longer Query | 1103 | 1381 |
Writing & Preference Solar Pro4 leads
Mixtral 8x7B: 34.2 (#270), Solar Pro4: 56.5 (#138)
| Benchmark | Mixtral 8x7B | Solar Pro4 |
|---|---|---|
| LMArena Text | 1132 | 1386 |
| LMArena Creative Writing | 1109 | 1316 |
| LMArena Multi-Turn | 1115 | 1385 |
| WildBench | 67.3% | — |
Frequently asked questions
Is Mixtral 8x7B better than Solar Pro4?
Solar Pro4 is the stronger model overall, scoring 42.1 to 27.1 on the Noometry Index.
Which is cheaper, Mixtral 8x7B or Solar Pro4?
Solar Pro4 is cheaper. It lists at $0.30 per million input tokens and $1.20 per million output tokens; Mixtral 8x7B lists at $0.70 and $0.70.
Is Mixtral 8x7B or Solar Pro4 better for coding?
Solar Pro4 scores higher on coding benchmarks: 40.1 versus 32.8 in the Noometry coding category.
Which has the bigger context window?
Solar Pro4 does, with 524K tokens against 32K.
How many benchmarks do Mixtral 8x7B and Solar Pro4 share?
17 benchmarks have published results for both models. Mixtral 8x7B has 38 scored results on Noometry and Solar Pro4 has 18.