Model comparison
Gemini 2.5 Flash-Lite vs Mistral Large 3
Mistral Large 3 is the stronger model overall, scoring 39.1 to 37.0 on the Noometry Index. Gemini 2.5 Flash-Lite costs 2.1× less per token, which makes it the better buy when Mistral Large 3's lead doesn't matter for your workload.
Last verified . 20 shared benchmarks.
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Mistral AISummary
- They share 20 benchmarks with published results for both. Gemini 2.5 Flash-Lite scores higher in 2 categories and Mistral Large 3 in 7 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in long context, where Mistral Large 3 leads 43.1 to 33.3.
- The biggest single-benchmark swing is Vectara Hallucination Rate: 3.3% for Gemini 2.5 Flash-Lite and 14.5% for Mistral Large 3.
- Gemini 2.5 Flash-Lite is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.25 / $0.75 for Mistral Large 3.
- Gemini 2.5 Flash-Lite accepts more context: 1.05M tokens versus 262K.
- Mistral Large 3 has downloadable open weights; the other is API-only.
Side by side
| Gemini 2.5 Flash-Lite | Mistral Large 3 | |
|---|---|---|
| Provider | Mistral AI | |
| Noometry Index | 37.0 | 39.1 |
| Released | 2025-06-17 | 2025-12-02 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 262K |
| Max output | 66K | 8K |
| Input $ / M tokens | $0.10 | $0.25 |
| Output $ / M tokens | $0.40 | $0.75 |
| Results tracked | 33 | 24 |
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Category by category
Coding Gemini 2.5 Flash-Lite leads
Gemini 2.5 Flash-Lite: 38.5 (#173), Mistral Large 3: 34.4 (#237)
| Benchmark | Gemini 2.5 Flash-Lite | Mistral Large 3 |
|---|---|---|
| LMArena Coding | 1373 | 1448 |
| LMArena WebDev | — | 1230 |
| WeirdML | 35.2% | — |
| ALE-Bench | 325.9 | — |
Agentic & Tool Use Not comparable
Gemini 2.5 Flash-Lite: 28.0 (#96), Mistral Large 3: —
| Benchmark | Gemini 2.5 Flash-Lite | Mistral Large 3 |
|---|---|---|
| Berkeley Function Calling Leaderboard | 36.9% | — |
Reasoning Gemini 2.5 Flash-Lite leads
Gemini 2.5 Flash-Lite: 22.2 (#205), Mistral Large 3: 15.2 (#319)
| Benchmark | Gemini 2.5 Flash-Lite | Mistral Large 3 |
|---|---|---|
| Kagi LLM Benchmark | 40.5% | 50.9% |
| LMArena Hard Prompts | 1377 | 1429 |
| NYT Connections (extended) | — | 7.5% |
| Thematic Generalization | — | 23% |
| DTBench | 62.8% | — |
| LMCA | 18.1% | — |
| Epoch Capabilities Index | 133.94 | — |
Math Too close to call
Gemini 2.5 Flash-Lite: 38.0 (#144), Mistral Large 3: 38.7 (#129)
| Benchmark | Gemini 2.5 Flash-Lite | Mistral Large 3 |
|---|---|---|
| LMArena Math | 1373 | 1414 |
| Omni-MATH | 48% | — |
Knowledge Mistral Large 3 leads
Gemini 2.5 Flash-Lite: 32.5 (#210), Mistral Large 3: 36.0 (#177)
| Benchmark | Gemini 2.5 Flash-Lite | Mistral Large 3 |
|---|---|---|
| Vectara Hallucination Rate | 3.3% | 14.5% |
| LMArena Expert | 1373 | 1421 |
| MMLU-Pro | 53.7% | — |
| GPQA (HELM) | 30.9% | — |
Multimodal Mistral Large 3 leads
Gemini 2.5 Flash-Lite: 29.1 (#114), Mistral Large 3: 38.2 (#66)
| Benchmark | Gemini 2.5 Flash-Lite | Mistral Large 3 |
|---|---|---|
| LMArena Vision | 1198 | 1221 |
| VPCT | 30% | — |
Multilingual Mistral Large 3 leads
Gemini 2.5 Flash-Lite: 49.3 (#134), Mistral Large 3: 52.5 (#84)
| Benchmark | Gemini 2.5 Flash-Lite | Mistral Large 3 |
|---|---|---|
| LMArena Non-English | 1369 | 1413 |
| LMArena Chinese | 1404 | 1447 |
| LMArena French | 1388 | 1455 |
| LMArena German | 1389 | 1437 |
| LMArena Japanese | 1359 | 1394 |
| LMArena Korean | 1360 | 1384 |
| LMArena Russian | 1373 | 1411 |
| LMArena Spanish | 1396 | 1440 |
Instruction Following Mistral Large 3 leads
Gemini 2.5 Flash-Lite: 70.0 (#168), Mistral Large 3: 74.0 (#108)
| Benchmark | Gemini 2.5 Flash-Lite | Mistral Large 3 |
|---|---|---|
| LMArena Instruction Following | 1367 | 1403 |
| IFEval | 81% | — |
Long Context Mistral Large 3 leads
Gemini 2.5 Flash-Lite: 33.3 (#262), Mistral Large 3: 43.1 (#105)
| Benchmark | Gemini 2.5 Flash-Lite | Mistral Large 3 |
|---|---|---|
| LMArena Longer Query | 1373 | 1413 |
| Fiction.LiveBench | 47.2% | — |
Writing & Preference Mistral Large 3 leads
Gemini 2.5 Flash-Lite: 56.8 (#135), Mistral Large 3: 60.0 (#101)
| Benchmark | Gemini 2.5 Flash-Lite | Mistral Large 3 |
|---|---|---|
| LMArena Text | 1379 | 1428 |
| LMArena Creative Writing | 1367 | 1386 |
| LMArena Multi-Turn | 1366 | 1429 |
| EQ-Bench Creative Writing | — | 1412 |
| WildBench | 81.8% | — |
Frequently asked questions
Is Gemini 2.5 Flash-Lite better than Mistral Large 3?
Mistral Large 3 is the stronger model overall, scoring 39.1 to 37.0 on the Noometry Index. Gemini 2.5 Flash-Lite costs 2.1× less per token, which makes it the better buy when Mistral Large 3's lead doesn't matter for your workload.
Which is cheaper, Gemini 2.5 Flash-Lite or Mistral Large 3?
Gemini 2.5 Flash-Lite is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; Mistral Large 3 lists at $0.25 and $0.75.
Is Gemini 2.5 Flash-Lite or Mistral Large 3 better for coding?
Gemini 2.5 Flash-Lite scores higher on coding benchmarks: 38.5 versus 34.4 in the Noometry coding category.
Which has the bigger context window?
Gemini 2.5 Flash-Lite does, with 1.05M tokens against 262K.
How many benchmarks do Gemini 2.5 Flash-Lite and Mistral Large 3 share?
20 benchmarks have published results for both models. Gemini 2.5 Flash-Lite has 33 scored results on Noometry and Mistral Large 3 has 24.