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Investing in multi-agent AI safety research DiffusionGemma: 4x faster text generation Fluid, natural voice translation with Gemini 3.5 Live Translate Measuring the impact of learning with AI in Sierra Leone and beyond Powering the future of robotics in Europe Introducing Gemma 4 12B: a unified, encoder-free multimodal model Strengthening Singapore’s AI Future: A New National Partnership Simulate real-world places with Project Genie and Street View Introducing Gemini Omni Gemini for Science: AI experiments and tools for a new era of discovery Making it easier to understand how content was created and edited Gemini 3.5: frontier intelligence with action Co-Scientist: A multi-agent AI partner to accelerate research How WeatherNext helped the National Hurricane Center better predict Hurricane Melissa’s historic landfall in Jamaica Fast-tracking genetic leads to reverse cellular aging Finding the molecular switches behind new infectious diseases Opening new paths in aging research Accelerating discovery of liver disease mechanisms Uniting biological toolkits for a new approach to ALS Uncovering repurposed medicines to fight liver fibrosis Google Antigravity We’re launching the Google DeepMind Accelerator program in Asia Pacific to tackle environmental risks. Reimagining the mouse pointer for the AI era AlphaEvolve: How our Gemini-powered coding agent is scaling impact across fields Enabling a new model for healthcare with AI co-clinician Announcing our partnership with the Republic of Korea Decoupled DiLoCo: A new frontier for resilient, distributed AI training Partnering with industry leaders to accelerate AI transformation Gemini 3.1 Flash TTS: the next generation of expressive AI speech Gemini Robotics-ER 1.6: Powering real-world robotics tasks through enhanced embodied reasoning Gemma 4: Byte for byte, the most capable open models Gemini 3.1 Flash Live: Making audio AI more natural and reliable Protecting people from harmful manipulation Lyria 3 Pro: Create longer tracks in more Google products Measuring progress toward AGI: A cognitive framework From games to biology and beyond: 10 years of AlphaGo’s impact Nano Banana 2: Combining Pro capabilities with lightning-fast speed Gemini 3.1 Pro: A smarter model for your most complex tasks A new way to express yourself: Gemini can now create music Accelerating discovery in India through AI-powered science and education Gemini 3 Deep Think: Advancing science, research and engineering Accelerating Mathematical and Scientific Discovery with Gemini Deep Think Project Genie: Experimenting with infinite, interactive worlds D4RT: Teaching AI to see the world in four dimensions Veo 3.1 Ingredients to Video: More consistency, creativity and control Google's year in review: 8 areas with research breakthroughs in 2025 Gemma Scope 2: helping the AI safety community deepen understanding of complex language model behavior Google DeepMind supports U.S. Department of Energy on Genesis: a national mission to accelerate innovation and scientific discovery Gemini 3 Flash: frontier intelligence built for speed Improved Gemini audio models for powerful voice interactions Deepening our partnership with the UK AI Security Institute Strengthening our partnership with the UK government to support prosperity and security in the AI era FACTS Benchmark Suite: Systematically evaluating the factuality of large language models Engineering more resilient crops for a warming climate AlphaFold: Five years of impact Revealing a key protein behind heart disease How we’re bringing AI image verification to the Gemini app Build with Nano Banana Pro, our Gemini 3 Pro Image model Introducing Nano Banana Pro We’re expanding our presence in Singapore to advance AI in the Asia-Pacific region Start building with Gemini 3 A new era of intelligence with Gemini 3 Google Antigravity WeatherNext 2: Our most advanced weather forecasting model SIMA 2: An Agent that Plays, Reasons, and Learns With You in Virtual 3D Worlds Teaching AI to see the world more like we do How AI is giving Northern Ireland teachers time back Mapping, modeling, and understanding nature with AI Accelerating discovery with the AI for Math Initiative MedGemma: Our most capable open models for health AI development VaultGemma: The world's most capable differentially private LLM Bringing AI to the next generation of fusion energy Introducing Veo 3.1 and advanced capabilities in Flow How a Gemma model helped discover a new potential cancer therapy pathway Introducing the Gemini 2.5 Computer Use model Introducing CodeMender: an AI agent for code security Gemini Robotics 1.5 brings AI agents into the physical world Strengthening our Frontier Safety Framework Discovering new solutions to century-old problems in fluid dynamics Gemini achieves gold-medal level at the International Collegiate Programming Contest World Finals Using AI to perceive the universe in greater depth Image editing in Gemini just got a major upgrade Introducing Gemma 3 270M: The compact model for hyper-efficient AI How AI is helping advance the science of bioacoustics to save endangered species Genie 3: A new frontier for world models Rethinking how we measure AI intelligence Try Deep Think in the Gemini app AlphaEarth Foundations helps map our planet in unprecedented detail Aeneas transforms how historians connect the past Gemini 2.5 Flash-Lite is now stable and generally available Exploring the context of online images with Backstory Advanced version of Gemini with Deep Think officially achieves gold-medal standard at the International Mathematical Olympiad T5Gemma: A new collection of encoder-decoder Gemma models Introducing Gemma 3n: The developer guide AlphaGenome: AI for better understanding the genome Gemini Robotics On-Device brings AI to local robotic devices We’re expanding our Gemini 2.5 family of models Gemini 2.5: Updates to our family of thinking models Behind “ANCESTRA”: combining Veo with live-action filmmaking How we're supporting better tropical cyclone prediction with AI
Gemini 3.1 Flash-Lite: Built for intelligence at scale
The Gemini Team · 2026-03-04 · via Google DeepMind News

Get best-in-class intelligence for your highest-volume workloads.

General summary

Gemini 3.1 Flash-Lite is now available in preview to developers via the Gemini API in Google AI Studio and for enterprises via Vertex AI. Priced at $0.25/1M input tokens and $1.50/1M output tokens, it's cost-efficient and faster than 2.5 Flash. Use 3.1 Flash-Lite for tasks like translation content moderation generating user interfaces and creating simulations.

Summaries were generated by Google AI. Generative AI is experimental.

Basic explainer

Google made a new AI model called Gemini 3.1 Flash-Lite. It's super fast and cheap to use, so more people can use it. This AI is good at things like translating languages and checking content. Some companies are already using it to solve tough problems because it's both smart and efficient.

Summaries were generated by Google AI. Generative AI is experimental.

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[[duration]] minutes

Today, we're introducing Gemini 3.1 Flash-Lite, our fastest and most cost-efficient Gemini 3 series model. Built for high-volume developer workloads at scale, 3.1 Flash-Lite delivers high quality for its price and model tier.

Starting today, 3.1 Flash-Lite is rolling out in preview to developers via the Gemini API in Google AI Studio and for enterprises via Vertex AI.

Cost-efficiency without compromise

Priced at just $0.25/1M input tokens and $1.50/1M output tokens, 3.1 Flash-Lite delivers enhanced performance at a fraction of the cost of larger models. It outperforms 2.5 Flash with a 2.5X faster Time to First Answer Token and 45% increase in output speed, according to the Artificial Analysis benchmark while maintaining similar or better quality. This low latency is needed for high-frequency workflows, making it an ideal model for developers to build responsive, real-time experiences.

The image shows two bar charts titled "Speed & Cost Efficiency," comparing the "Output speed (higher is better)" and "Price (lower is better)" of Gemini 3.1 Flash-Lite against several other models, including Gemini 2.5 Flash-Lite, GPT-5 mini, Claude 4.5 Haiku, and Grok 4.1 Fast.

Gemini 3.1 Flash-Lite outperforms 2.5 Flash in speed and quality.

3.1 Flash-Lite achieves an impressive Elo score of 1432 on the Arena.ai Leaderboard and outperforms other models of similar tier across reasoning and multimodal understanding benchmarks, including 86.9% on GPQA Diamond and 76.8% on MMMU Pro–even surpassing larger Gemini models from prior generations like 2.5 Flash.

The image displays a comparison table of several AI models, including "Gemini 3.1 Flash-Lite," "Gemini 2.5 Dynamic," "Gemini 2.5 Flash-Lite," "GPT-5 mini," "Claude 4.5 Haiku," and "Grok 4.1 Fast," across various metrics such as input/output price, output speed, and different academic, reasoning, and factual benchmarks.

Adaptive intelligence at scale for developers

Beyond its raw performance, Gemini 3.1 Flash-Lite comes standard with thinking levels in AI Studio and Vertex AI, giving developers the control and flexibility to select how much the model “thinks” for a task, which is critical for managing high-frequency workloads. 3.1 Flash-Lite can tackle tasks at scale, like high-volume translation and content moderation, where cost is a priority. And it can also handle more complex workloads where more in-depth reasoning is needed, like generating user interfaces and dashboards, creating simulations or following instructions.

3.1 Flash-Lite can analyze and sort large numbers of content like images quickly.

Early-access developers on AI Studio and Vertex AI, and companies like Latitude, Cartwheel and Whering are already using 3.1 Flash-Lite to solve complex problems at scale. Early testers highlighted 3.1 Flash-Lite’s efficiency and reasoning capabilities, saying it can handle complex inputs with the precision of a larger-tier model, plus follow instructions and maintain adherence.

We look forward to seeing what you build with 3.1 Flash-Lite and the rest of the Gemini 3 series models.

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