Model comparison
Gemini 3.5 Flash vs Mixtral 8x7B
Gemini 3.5 Flash is the stronger model overall, scoring 54.2 to 27.1 on the Noometry Index. Mixtral 8x7B costs 4.8× less per token, which makes it the better buy when Gemini 3.5 Flash's lead doesn't matter for your workload.
Last verified . 21 shared benchmarks.
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Mistral AISummary
- They share 21 benchmarks with published results for both. Gemini 3.5 Flash scores higher in 8 categories and Mixtral 8x7B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Gemini 3.5 Flash leads 66.3 to 11.0.
- The biggest single-benchmark swing is GPQA Diamond: 92.8% for Gemini 3.5 Flash and 30.6% for Mixtral 8x7B.
- Mixtral 8x7B is cheaper at $0.70 / $0.70 per million input/output tokens, against $1.50 / $9 for Gemini 3.5 Flash.
- Gemini 3.5 Flash accepts more context: 1.05M tokens versus 32K.
- Mixtral 8x7B has downloadable open weights; the other is API-only.
Side by side
| Gemini 3.5 Flash | Mixtral 8x7B | |
|---|---|---|
| Provider | Mistral AI | |
| Noometry Index | 54.2 | 27.1 |
| Released | 2026-05-19 | 2023-12-11 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 32K |
| Max output | 66K | 32K |
| Input $ / M tokens | $1.50 | $0.70 |
| Output $ / M tokens | $9 | $0.70 |
| Results tracked | 54 | 38 |
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Category by category
Coding Gemini 3.5 Flash leads
Gemini 3.5 Flash: 49.4 (#49), Mixtral 8x7B: 32.8 (#269)
| Benchmark | Gemini 3.5 Flash | Mixtral 8x7B |
|---|---|---|
| LMArena Coding | 1492 | 1126 |
| SWE-bench Verified | 79.3% | — |
| DeepSWE | 37.4% | — |
| LMArena WebDev | 1499 | — |
| SciCode | 53.1% | — |
| WeirdML | 62.6% | — |
| ALE-Bench | 911.02 | — |
| HumanEval+ | — | 39.6% |
| MBPP+ | — | 49.7% |
Agentic & Tool Use Not comparable
Gemini 3.5 Flash: 24.7 (#114), Mixtral 8x7B: —
| Benchmark | Gemini 3.5 Flash | Mixtral 8x7B |
|---|---|---|
| APEX-Agents | 27.5% | — |
| GBAEval | 6.7% | — |
| GDP.pdf | 14% | — |
| Vending-Bench 2 | 5,396 | — |
Reasoning Gemini 3.5 Flash leads
Gemini 3.5 Flash: 62.8 (#18), Mixtral 8x7B: 18.2 (#285)
| Benchmark | Gemini 3.5 Flash | Mixtral 8x7B |
|---|---|---|
| LMArena Hard Prompts | 1488 | 1115 |
| DTBench | 94.7% | 49.6% |
| Epoch Capabilities Index | 154.46 | 118.47 |
| ForecastBench | 59 | 56.3 |
| ARC-AGI-2 | 72.1% | — |
| SimpleBench | 76.7% | — |
| NYT Connections (extended) | 92.6% | — |
| ARC-AGI-1 | 92.5% | — |
| CritPt | 13.1% | — |
| Chess Puzzles | 50% | — |
| EnigmaEval | 25.4% | — |
| EBR-Bench | 4.8% | — |
| Mystery Game Puzzles | 32% | — |
| LMCA | 47.1% | — |
| Surface Evolver Bench | 58.1% | — |
| Adversarial NLI | — | 55.2% |
| HellaSwag | — | 86.7% |
| PIQA | — | 83.6% |
| WinoGrande | — | 77.2% |
Math Gemini 3.5 Flash leads
Gemini 3.5 Flash: 60.7 (#36), Mixtral 8x7B: 18.8 (#289)
| Benchmark | Gemini 3.5 Flash | Mixtral 8x7B |
|---|---|---|
| LMArena Math | 1504 | 1147 |
| FrontierMath (Tiers 1-3) | 62.8% | — |
| FrontierMath Tier 4 | 26.8% | — |
| MathArena Final-Answer Competitions | 76.3% | — |
| OTIS Mock AIME 2024-2025 | 95.6% | — |
| ProofBench | 31% | — |
| Omni-MATH | — | 10.5% |
| MATH Level 5 | — | 10% |
| FrontierMath (Feb 2025 set) | 39% | — |
| FrontierMath Tier 4 (v1) | 14.6% | — |
| GSM8K | — | 74.4% |
Knowledge Gemini 3.5 Flash leads
Gemini 3.5 Flash: 66.3 (#11), Mixtral 8x7B: 11.0 (#301)
| Benchmark | Gemini 3.5 Flash | Mixtral 8x7B |
|---|---|---|
| GPQA Diamond | 92.8% | 30.6% |
| LMArena Expert | 1495 | 1088 |
| SimpleQA Verified | 66.2% | — |
| MMLU-Pro | — | 33.5% |
| GPQA (HELM) | — | 29.6% |
| ARC (AI2) Challenge | — | 87.3% |
| MMLU | — | 70.6% |
| OpenBookQA | — | 85.8% |
| TriviaQA | — | 82.2% |
Multimodal Not comparable
Gemini 3.5 Flash: 45.7 (#15), Mixtral 8x7B: —
| Benchmark | Gemini 3.5 Flash | Mixtral 8x7B |
|---|---|---|
| LMArena Vision | 1310 | — |
| Blueprint-Bench 2 | 33.6% | — |
| LMArena Document | 1463 | — |
Multilingual Gemini 3.5 Flash leads
Gemini 3.5 Flash: 57.0 (#13), Mixtral 8x7B: 29.6 (#266)
| Benchmark | Gemini 3.5 Flash | Mixtral 8x7B |
|---|---|---|
| LMArena Non-English | 1476 | 1077 |
| LMArena Chinese | 1526 | 1055 |
| LMArena French | 1490 | 1166 |
| LMArena German | 1492 | 1114 |
| LMArena Japanese | 1486 | 931 |
| LMArena Korean | 1451 | 968 |
| LMArena Russian | 1493 | 1090 |
| LMArena Spanish | 1480 | 1111 |
Instruction Following Gemini 3.5 Flash leads
Gemini 3.5 Flash: 77.0 (#30), Mixtral 8x7B: 51.0 (#297)
| Benchmark | Gemini 3.5 Flash | Mixtral 8x7B |
|---|---|---|
| LMArena Instruction Following | 1467 | 1109 |
| IFEval | — | 57.5% |
Long Context Gemini 3.5 Flash leads
Gemini 3.5 Flash: 45.4 (#38), Mixtral 8x7B: 33.4 (#260)
| Benchmark | Gemini 3.5 Flash | Mixtral 8x7B |
|---|---|---|
| LMArena Longer Query | 1482 | 1103 |
Writing & Preference Gemini 3.5 Flash leads
Gemini 3.5 Flash: 65.5 (#47), Mixtral 8x7B: 34.2 (#270)
| Benchmark | Gemini 3.5 Flash | Mixtral 8x7B |
|---|---|---|
| LMArena Text | 1482 | 1132 |
| LMArena Creative Writing | 1470 | 1109 |
| LMArena Multi-Turn | 1481 | 1115 |
| WildBench | — | 67.3% |
| EQ-Bench 4 | 1087 | — |
Frequently asked questions
Is Gemini 3.5 Flash better than Mixtral 8x7B?
Gemini 3.5 Flash is the stronger model overall, scoring 54.2 to 27.1 on the Noometry Index. Mixtral 8x7B costs 4.8× less per token, which makes it the better buy when Gemini 3.5 Flash's lead doesn't matter for your workload.
Which is cheaper, Gemini 3.5 Flash or Mixtral 8x7B?
Mixtral 8x7B is cheaper. It lists at $0.70 per million input tokens and $0.70 per million output tokens; Gemini 3.5 Flash lists at $1.50 and $9.
Is Gemini 3.5 Flash or Mixtral 8x7B better for coding?
Gemini 3.5 Flash scores higher on coding benchmarks: 49.4 versus 32.8 in the Noometry coding category.
Which has the bigger context window?
Gemini 3.5 Flash does, with 1.05M tokens against 32K.
How many benchmarks do Gemini 3.5 Flash and Mixtral 8x7B share?
21 benchmarks have published results for both models. Gemini 3.5 Flash has 54 scored results on Noometry and Mixtral 8x7B has 38.