Model comparison
Gemini 1.5 Flash (May 2024) vs Mistral Medium
Mistral Medium is the stronger model overall, scoring 36.3 to 33.2 on the Noometry Index.
Last verified . 24 shared benchmarks.
Google
Mistral AISummary
- They share 24 benchmarks with published results for both. Gemini 1.5 Flash (May 2024) scores higher in 3 categories and Mistral Medium in 7 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Mistral Medium leads 60.0 to 48.7.
- The biggest single-benchmark swing is DTBench: 53.8% for Gemini 1.5 Flash (May 2024) and 75.5% for Mistral Medium.
- Mistral Medium has downloadable open weights; the other is API-only.
Side by side
| Gemini 1.5 Flash (May 2024) | Mistral Medium | |
|---|---|---|
| Provider | Mistral AI | |
| Noometry Index | 33.2 | 36.3 |
| Released | 2024-05-14 | 2023-12-11 |
| Weights | Proprietary | Open |
| Context window | — | 262K |
| Max output | — | 262K |
| Input $ / M tokens | — | $1.50 |
| Output $ / M tokens | — | $7.50 |
| Results tracked | 42 | 36 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Too close to call
Gemini 1.5 Flash (May 2024): 34.4 (#236), Mistral Medium: 34.2 (#243)
| Benchmark | Gemini 1.5 Flash (May 2024) | Mistral Medium |
|---|---|---|
| WeirdML | 24.9% | 43.7% |
| LMArena Coding | 1261 | 1434 |
| FrontierCode | — | 8% |
| SciCode | — | 40.2% |
| BigCodeBench Instruct | 43.5% | — |
| BigCodeBench Complete | 55.1% | — |
| ALE-Bench | — | 763.98 |
| HumanEval+ | 75.6% | — |
| MBPP+ | 67.5% | — |
Agentic & Tool Use Mistral Medium leads
Gemini 1.5 Flash (May 2024): 26.6 (#102), Mistral Medium: 28.3 (#90)
| Benchmark | Gemini 1.5 Flash (May 2024) | Mistral Medium |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 37.7% |
| BALROG | 14.6% | — |
Reasoning Mistral Medium leads
Gemini 1.5 Flash (May 2024): 21.7 (#215), Mistral Medium: 24.0 (#167)
| Benchmark | Gemini 1.5 Flash (May 2024) | Mistral Medium |
|---|---|---|
| LMArena Hard Prompts | 1257 | 1426 |
| DTBench | 53.8% | 75.5% |
| Kagi LLM Benchmark | — | 50% |
| CritPt | — | 0% |
| LMCA | — | 26.1% |
| Surface Evolver Bench | — | 26.9% |
| Epoch Capabilities Index | 129.36 | — |
| ForecastBench | 53.9 | — |
| PIQA | 87.5% | — |
Math Mistral Medium leads
Gemini 1.5 Flash (May 2024): 22.1 (#281), Mistral Medium: 28.1 (#245)
| Benchmark | Gemini 1.5 Flash (May 2024) | Mistral Medium |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 16.3% | 32.2% |
| LMArena Math | 1269 | 1408 |
| MATH Level 5 | 61.9% | 81.6% |
| FrontierMath (Feb 2025 set) | 0% | 0.3% |
| ProofBench | — | 9% |
| Omni-MATH | 30.4% | — |
| GSM8K | 82.4% | — |
Knowledge Gemini 1.5 Flash (May 2024) leads
Gemini 1.5 Flash (May 2024): 26.2 (#260), Mistral Medium: 25.0 (#265)
| Benchmark | Gemini 1.5 Flash (May 2024) | Mistral Medium |
|---|---|---|
| GPQA Diamond | 47.3% | 59.5% |
| LMArena Expert | 1233 | 1408 |
| Humanity's Last Exam | — | 4.5% |
| MMLU-Pro | 67.8% | — |
| Vectara Hallucination Rate | — | 22.7% |
| GPQA (HELM) | 43.7% | — |
| BoolQ | 85.8% | — |
| MMLU | 77.9% | — |
Multimodal Too close to call
Gemini 1.5 Flash (May 2024): 36.0 (#81), Mistral Medium: 35.3 (#88)
| Benchmark | Gemini 1.5 Flash (May 2024) | Mistral Medium |
|---|---|---|
| LMArena Vision | 1141 | 1172 |
| Video-MME | 70.3% | — |
| GeoBench | 76% | — |
Multilingual Mistral Medium leads
Gemini 1.5 Flash (May 2024): 42.9 (#189), Mistral Medium: 52.1 (#91)
| Benchmark | Gemini 1.5 Flash (May 2024) | Mistral Medium |
|---|---|---|
| LMArena Non-English | 1278 | 1408 |
| LMArena Chinese | 1295 | 1447 |
| LMArena French | 1258 | 1459 |
| LMArena German | 1262 | 1432 |
| LMArena Japanese | 1252 | 1378 |
| LMArena Korean | 1221 | 1380 |
| LMArena Russian | 1288 | 1411 |
| LMArena Spanish | 1243 | 1433 |
Instruction Following Mistral Medium leads
Gemini 1.5 Flash (May 2024): 66.8 (#205), Mistral Medium: 73.7 (#116)
| Benchmark | Gemini 1.5 Flash (May 2024) | Mistral Medium |
|---|---|---|
| LMArena Instruction Following | 1258 | 1398 |
| IFEval | 83.1% | — |
Long Context Mistral Medium leads
Gemini 1.5 Flash (May 2024): 39.0 (#187), Mistral Medium: 42.9 (#114)
| Benchmark | Gemini 1.5 Flash (May 2024) | Mistral Medium |
|---|---|---|
| LMArena Longer Query | 1284 | 1406 |
Writing & Preference Mistral Medium leads
Gemini 1.5 Flash (May 2024): 48.7 (#196), Mistral Medium: 60.0 (#103)
| Benchmark | Gemini 1.5 Flash (May 2024) | Mistral Medium |
|---|---|---|
| LMArena Text | 1287 | 1424 |
| LMArena Creative Writing | 1285 | 1391 |
| LMArena Multi-Turn | 1253 | 1418 |
| Short-Story Creative Writing | — | 77.3% |
| WildBench | 79.2% | — |
Frequently asked questions
Is Gemini 1.5 Flash (May 2024) better than Mistral Medium?
Mistral Medium is the stronger model overall, scoring 36.3 to 33.2 on the Noometry Index.
Is Gemini 1.5 Flash (May 2024) or Mistral Medium better for coding?
They score almost the same on coding (34.4 vs 34.2); test both on your own repository before choosing.
How many benchmarks do Gemini 1.5 Flash (May 2024) and Mistral Medium share?
24 benchmarks have published results for both models. Gemini 1.5 Flash (May 2024) has 42 scored results on Noometry and Mistral Medium has 36.