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- Mar 3, 202690% CONFIDENCEfrom the source
Gemini 3.1 Flash-Lite Released
- Google introduced Gemini 3.1 Flash-Lite on 3 March 2026, "our fastest and most cost-efficient Gemini 3 series model", built for high-volume developer workloads[1]
- It is faster than 2.5 Flash, with a 2.5X faster time to first answer token and a 45% increase in output speed at similar or better quality[1]
Notable features
- Priced at $0.25 per million input tokens and $1.50 per million output tokens[1]
- Suited to translation, content moderation, generating user interfaces and building simulations[1]
- In preview via the Gemini API in Google AI Studio and Vertex AI[1]
Benchmarks[3]
| Benchmark | Gemini 3.1 Flash-Lite | Gemini 2.5 Flash | Gemini 2.5 Flash-Lite | GPT-5 mini | Claude 4.5 Haiku | Grok 4.1 Fast |
|---|---|---|---|---|---|---|
| Input price ($/1M tokens, no caching, Lower is better) | $0.25 | $0.30 | $0.10 | $0.25 | $1.00 | $0.20 |
| Output price ($/1M tokens, Lower is better) | $1.50 | $2.50 | $0.40 | $2.00 | $5.00 | $0.50 |
| Output speed (Tokens / s) | 363 | 249 | 366 | 71 | 108 | 145 |
| Humanity’s Last Exam (Academic reasoning (full set, text + MM), No tools) | 16.0% | 11.0% | 6.9% | 16.7% | 9.7% | 17.6% |
| GPQA Diamond (Scientific knowledge, No tools) | 86.9% | 82.8% | 66.7% | 82.3% | 73.0% | 84.3% |
| MMMU-Pro (Multimodal understanding and reasoning, No tools) | 76.8% | 66.7% | 51.0% | 74.1% | 58.0% | 63.0% |
| CharXiv Reasoning (Information synthesis from complex charts) | 73.2% | 63.7% | 55.5% | 75.5% | 61.7% | 31.6% |
| Video-MMMU (Knowledge acquisition from videos) | 84.8% | 79.2% | 60.7% | 82.5% | — | 74.6% |
| SimpleQA Verified (Parametric knowledge) | 43.3% | 28.1% | 11.5% | 9.5% | 5.5% | 19.5% |
| FACTS Benchmark Suite (Factuality benchmark across grounding, parametric, search, and MM.) | 40.6% | 50.4% | 17.9% | 33.7% | 18.6% | 42.1% |
| MMMLU (Multilingual Q&A) | 88.9% | 86.6% | 84.5% | 84.9% | 83.0% | 86.8% |
| LiveCodeBench (Code generation (UI: 1/1/2025-5/1/2025)) | 72.0% | 62.6% | 34.3% | 80.4% | 53.2% | 76.5% |
| MRCR v2 (8-needle) (Long context performance, 128k (average)) | 60.1% | 54.3% | 30.6% | 52.5% | 35.3% | 54.6% |
| MRCR v2 (8-needle) (Long context performance, 1M (pointwise)) | 12.3% | 21.0% | 5.4% | — | — | 6.1% |
References 385% CONFIDENCEOverall confidence: 85%How well the pin's source and references back up its dates.Weighted average of how firmly 3 references, the source included, support the pin's start and end times; a reference counts half as much for every 180 days older than the newestShow all pins at 75% confidence or better
The first entry is always the pin's source. Overall confidence is a weighted average of how firmly each reference supports the start and end times used above; a reference counts half as much for every 180 days older than the newest.
- [1]90%blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-3-1-flash-liteblog.google· Posted Sep 30, 2026· Starts Mar 3, 2026 ✓· 41% of score
Google's post "Gemini 3.1 Flash-Lite: Built for intelligence at scale" is dated 3 March 2026 and says it is rolling out in preview that day to developers through the Gemini API and to enterprises through Vertex AI.
- [2]75%Gemini (language model) - Wikipediaen.wikipedia.org· Added Sep 30, 2026· 41% of score
The Wikipedia article lists Gemini 3.1 Flash-Lite as released on 3 March 2026.
- [3]95%Gemini 3.1 Flash-Lite - Model Carddeepmind.google· Published Mar 3, 2026· 18% of score
DeepMind's model card gives the benchmark table against the model's predecessor and named rivals.
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