Model comparison
Gemini 3.5 Flash vs Mistral 7B
Gemini 3.5 Flash is the stronger model overall, scoring 54.2 to 23.0 on the Noometry Index. Mistral 7B costs 14× 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 Mistral 7B 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 7.4.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 95.6% for Gemini 3.5 Flash and 0.3% for Mistral 7B.
- Mistral 7B is cheaper at $0.25 / $0.25 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 8K.
- Mistral 7B has downloadable open weights; the other is API-only.
Side by side
| Gemini 3.5 Flash | Mistral 7B | |
|---|---|---|
| Provider | Mistral AI | |
| Noometry Index | 54.2 | 23.0 |
| Released | 2026-05-19 | 2023-09-27 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 8K |
| Max output | 66K | 8K |
| Input $ / M tokens | $1.50 | $0.25 |
| Output $ / M tokens | $9 | $0.25 |
| Results tracked | 54 | 37 |
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Category by category
Coding Gemini 3.5 Flash leads
Gemini 3.5 Flash: 49.4 (#49), Mistral 7B: 26.4 (#326)
| Benchmark | Gemini 3.5 Flash | Mistral 7B |
|---|---|---|
| LMArena Coding | 1492 | 1082 |
| SWE-bench Verified | 79.3% | — |
| DeepSWE | 37.4% | — |
| LMArena WebDev | 1499 | — |
| SciCode | 53.1% | — |
| WeirdML | 62.6% | — |
| BigCodeBench Instruct | — | 19.5% |
| BigCodeBench Complete | — | 27.3% |
| ALE-Bench | 911.02 | — |
| HumanEval+ | — | 36% |
| MBPP+ | — | 42.1% |
Agentic & Tool Use Not comparable
Gemini 3.5 Flash: 24.7 (#114), Mistral 7B: —
| Benchmark | Gemini 3.5 Flash | Mistral 7B |
|---|---|---|
| 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), Mistral 7B: 13.1 (#336)
| Benchmark | Gemini 3.5 Flash | Mistral 7B |
|---|---|---|
| Chess Puzzles | 50% | 0% |
| LMArena Hard Prompts | 1488 | 1067 |
| DTBench | 94.7% | 42.5% |
| Epoch Capabilities Index | 154.46 | 112.21 |
| ARC-AGI-2 | 72.1% | — |
| SimpleBench | 76.7% | — |
| NYT Connections (extended) | 92.6% | — |
| ARC-AGI-1 | 92.5% | — |
| CritPt | 13.1% | — |
| EnigmaEval | 25.4% | — |
| EBR-Bench | 4.8% | — |
| Mystery Game Puzzles | 32% | — |
| LMCA | 47.1% | — |
| Surface Evolver Bench | 58.1% | — |
| Adversarial NLI | — | 47.1% |
| BIG-Bench Hard | — | 56.1% |
| ForecastBench | 59 | — |
| HellaSwag | — | 81% |
| PIQA | — | 83% |
| WinoGrande | — | 75.3% |
Math Gemini 3.5 Flash leads
Gemini 3.5 Flash: 60.7 (#36), Mistral 7B: 8.1 (#325)
| Benchmark | Gemini 3.5 Flash | Mistral 7B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 95.6% | 0.3% |
| LMArena Math | 1504 | 1085 |
| FrontierMath (Tiers 1-3) | 62.8% | — |
| FrontierMath Tier 4 | 26.8% | — |
| MathArena Final-Answer Competitions | 76.3% | — |
| ProofBench | 31% | — |
| MATH Level 5 | — | 3.7% |
| FrontierMath (Feb 2025 set) | 39% | — |
| FrontierMath Tier 4 (v1) | 14.6% | — |
| GSM8K | — | 54.4% |
Knowledge Gemini 3.5 Flash leads
Gemini 3.5 Flash: 66.3 (#11), Mistral 7B: 7.4 (#311)
| Benchmark | Gemini 3.5 Flash | Mistral 7B |
|---|---|---|
| GPQA Diamond | 92.8% | 15.2% |
| LMArena Expert | 1495 | 1036 |
| SimpleQA Verified | 66.2% | — |
| ARC (AI2) Challenge | — | 78.6% |
| BoolQ | — | 87.4% |
| MMLU | — | 62.5% |
| OpenBookQA | — | 79.8% |
| TriviaQA | — | 75.2% |
Multimodal Not comparable
Gemini 3.5 Flash: 45.7 (#15), Mistral 7B: —
| Benchmark | Gemini 3.5 Flash | Mistral 7B |
|---|---|---|
| LMArena Vision | 1310 | — |
| Blueprint-Bench 2 | 33.6% | — |
| LMArena Document | 1463 | — |
Multilingual Gemini 3.5 Flash leads
Gemini 3.5 Flash: 57.0 (#13), Mistral 7B: 25.8 (#283)
| Benchmark | Gemini 3.5 Flash | Mistral 7B |
|---|---|---|
| LMArena Non-English | 1476 | 1012 |
| LMArena Chinese | 1526 | 1009 |
| LMArena French | 1490 | 1037 |
| LMArena German | 1492 | 987 |
| LMArena Japanese | 1486 | 878 |
| LMArena Russian | 1493 | 1018 |
| LMArena Spanish | 1480 | 1026 |
| LMArena Korean | 1451 | — |
Instruction Following Gemini 3.5 Flash leads
Gemini 3.5 Flash: 77.0 (#30), Mistral 7B: 54.2 (#280)
| Benchmark | Gemini 3.5 Flash | Mistral 7B |
|---|---|---|
| LMArena Instruction Following | 1467 | 1060 |
Long Context Gemini 3.5 Flash leads
Gemini 3.5 Flash: 45.4 (#38), Mistral 7B: 32.2 (#271)
| Benchmark | Gemini 3.5 Flash | Mistral 7B |
|---|---|---|
| LMArena Longer Query | 1482 | 1060 |
Writing & Preference Gemini 3.5 Flash leads
Gemini 3.5 Flash: 65.5 (#47), Mistral 7B: 30.7 (#286)
| Benchmark | Gemini 3.5 Flash | Mistral 7B |
|---|---|---|
| LMArena Text | 1482 | 1090 |
| LMArena Creative Writing | 1470 | 1068 |
| LMArena Multi-Turn | 1481 | 1062 |
| EQ-Bench 4 | 1087 | — |
Frequently asked questions
Is Gemini 3.5 Flash better than Mistral 7B?
Gemini 3.5 Flash is the stronger model overall, scoring 54.2 to 23.0 on the Noometry Index. Mistral 7B costs 14× 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 Mistral 7B?
Mistral 7B is cheaper. It lists at $0.25 per million input tokens and $0.25 per million output tokens; Gemini 3.5 Flash lists at $1.50 and $9.
Is Gemini 3.5 Flash or Mistral 7B better for coding?
Gemini 3.5 Flash scores higher on coding benchmarks: 49.4 versus 26.4 in the Noometry coding category.
Which has the bigger context window?
Gemini 3.5 Flash does, with 1.05M tokens against 8K.
How many benchmarks do Gemini 3.5 Flash and Mistral 7B share?
21 benchmarks have published results for both models. Gemini 3.5 Flash has 54 scored results on Noometry and Mistral 7B has 37.