Gemini 2.5 Flash-Lite
Gemini 2.5 Flash-Lite is a model developed by Google DeepMind, designed to handle various tasks including reasoning, science, mathematics, code generation, and more. It features advanced capabilities in multilingual performance and long context understanding. It is optimized for low latency use cases, supporting multimodal input with a 1 million-token context length.
Benchmark results
| Benchmark | Score | Tags | Source |
|---|---|---|---|
| Aider-Polyglot | 26.7% | self-reported llm-stats | link → |
| AIME 2025 | 49.8% | self-reported llm-stats | link → |
| Arc | 2.5% | self-reported llm-stats | link → |
| FACTS Grounding | 84.1% | self-reported llm-stats | link → |
| Global-MMLU-Lite | 81.1% | self-reported llm-stats | link → |
| GPQA | 64.6% | self-reported llm-stats | link → |
| Humanity's Last Exam | 5.1% | self-reported llm-stats | link → |
| LiveCodeBench | 33.7% | self-reported llm-stats | link → |
| MMMU | 72.9% | self-reported llm-stats | link → |
| MRCR v2 | 16.6% | self-reported llm-stats | link → |
| SimpleQA | 10.7% | self-reported llm-stats | link → |
| SWE-Bench Verified | 31.6% | self-reported llm-stats | link → |
| Vibe-Eval | 51.3% | self-reported llm-stats | link → |