Gemini

Frontier intelligence with action

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Gemini 3.7 Flash

Best for tackling complex agentic tasks at scale

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Gemini 3.5 Flash-Lite

Best for high-volume tasks that need efficiency and intelligence

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3.5 Pro coming soon

Gemini 3.1 Pro

Best for complex tasks and bringing creative concepts to life

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Gemini 3.1 Deep Think

Best for modern challenges across science, research and engineering

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Explore the latest

Introducing our latest series of models combining frontier intelligence with action. Build more capable, intelligent agents efficiently.

Models
Capabilities
Performance
Hands-on
Showcase
Safety
Ecosystem
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Models

Completing everyday tasks, or solving your most challenging problems. Discover the right model for what you need

Capabilities

Agentic coding

Tackle complex, development tasks with advanced reasoning at speed.

Advanced multimodal understanding

Transform text, images, video and audio into rich interactive user interfaces.

Long horizon tasks

Execute sophisticated workflows over extended timeframes.

Multi-step problem-solving

Leverage advanced tools to solve demanding, real-world problems.

Performance

Benchmark	Notes	Gemini 3.7 Flash	Gemini 3.6 Flash	Claude Sonnet 5	GPT-5.6 Terra	Muse Spark 1.2
Input price $/1M tokens		$0.75*	$0.75*	$2.00	$2.00	$1.25
Output price $/1M tokens		$3.75*	$3.75*	$10.00	$12.00	$4.25
Artificial Analysis Intelligence Index Composite model intelligence		56	52	55	57	57
FrontierCode 1.1 Main Production code quality	Score	43.6%	34.4%	42.7%	41.3%	—
DeepSWE v1.1 Long-horizon software engineering		65.3%	48.6%	53.8%	69.6%	54.9%
Code Arena Web development	Elo	1588	1538	1541	1523	1535
Terminal-bench 2.1 Agentic terminal coding		85.8%	78.0%	80.4%	87.4%	82.9%
Terminal-bench 3.0 General agent capabilities		14.9%	5.4%	14.6%	20.8%	—
AutomationBench Enterprise workflow automation	Private set	30.4%	17.0%	10.7%	23.6%	—
GDPVal-AA v2 Knowledge work	Elo	1525	1422	1598	1578	1628
Harvey LAB-AA Complex legal workflows		90.7%	85.1%	90.1%	85.2%	—
GDP.pdf Expert PDF document comprehension		34.0%	22.0%	28.0%	24.7%	16.0%
CharXiv Reasoning Information synthesis from complex charts	No tools	84.5%	85.2%	77.0%	85.9%	—
CharXiv Reasoning Information synthesis from complex charts	With tools	88.7%	89.4%	88.3%	—	—
LVBench Long video understanding		85.4%	84.2%	68.5%	78.9%	—
GDM-MRCR v2 (8-needle) Long context performance	128k (average)	97.0%	91.8%	81.5%	93.5%	—
OSWorld-2.0 Agentic computer use		47.9%	33.8%	—	50.2%	—
Agent's Last Exam Multimodal desktop and OS agent tasks	Pass rate	26.3%	24.2%	33.3%	28.0%	—
HLE-Verified Multidisciplinary expert reasoning		53.6%	51.2%	31.0%	51.1%	—
BioMysteryBench Bioinformatics research reasoning	Human solvable	87.1%	80.6%	87.5%	83.8%	—
BioMysteryBench Bioinformatics research reasoning	Human difficult	43.5%	41.2%	34.1%	49.4%	—
LABBench2 Biology real-world research tasks		82.1%	76.1%	80.1%	81.2%	—

Methodology: deepmind.com/models/evals-methodology/gemini-3-7-flash

* For 3.6 and 3.7 Flash, introductory price expires on December 31, 2026. Starting January 1, 2027, $1.50/1M input tokens and $7.50/1M output tokens will apply.

Hands-on

Explore what you can do with Gemini 3.7 Flash and 3.5 Flash-Lite

3D game built in Google Antigravity

From a simple text prompt to a fully playable 3D game. We used Gemini 3.7 Flash combined with Nano Banana to dynamically generate characters, items, and textures in real-time.

Interactive parallax landing pages

Stunning, interactive landing pages generated in a single shot. We used Gemini 3.7 Flash to orchestrate sub-agents, using Gemini Omni to create smooth, interactive parallax components.

Train a robotics model with multimodal ‘graph’ looping

Watch a robotics model learn faster. We combined Gemini 3.7 Flash's multimodal understanding with a 3-agent graph loop to speed up the training loop.

Interactive annual report

From a static PDF to an interactive data story. Watch how Gemini 3.7 Flash transforms complex annual reports into engaging web experiences complete with live charts and aggregated insights.

3.5 Flash-Lite vs. 3.5 Flash latency

3.5 Flash-Lite executes high volume tasks at a lower latency than 3.5 Flash.

One prompt, 25 web design options

Working alongside 3.6 Flash as the master agent, 3.5 Flash-Lite instantly generates 25 unique, ready-to-explore web design concepts.

Receipt analysis and translation at scale

3.5 Flash-Lite can scale receipt translation and summarization with its multimodal understanding.

Rapid game development

3.5 Flash-Lite builds a game by instantly generating and iterating through multiple options.

Showcase

“On Box's evaluation of real enterprise knowledge work, Gemini 3.7 Flash was both more accurate and significantly faster than the prior model, with its largest gains on the most challenging analytical tasks. This is the kind of progress that expands what AI can take on for organizations.”
**Yashodha Bhavnani, VP of AI Products, Box**

“The Gemini 3.7 Flash agent was 35% cheaper than 3.6 Flash, with a +8% observed prompt-cache hit rate and fewer tool errors.”
**Gregor Zunic, Co-founder & CTO, Browser Use**

“We’re excited by how well the new Gemini Flash model understands motion across time. For Cartwheel, that means more than recognizing what’s in a frame—it means following an action and reasoning about whether the motion is actually useful. We saw promising results on both fronts.”
**Andrew Carr, CoFounder and Chief Scientist, Cartwheel**

“Until now, getting high-quality answers from complex enterprise data has been expensive at scale. Models like Gemini 3.7 Flash are changing that by delivering better intelligence at dramatically lower cost. With Gemini 3.7 Flash on Databricks AI Gateway, enterprises can ask big questions of their data, like predicting next week’s revenue, identifying key customers, or deciding where to invest next.”
**Ivan Zhou, AI Research Manager, Databricks**

“Gemini 3.7 Flash’s multimodal capabilities shine on Emergent, accurately translating design inspiration and brand guidelines into full-stack web and mobile applications. It has never been easier for anyone, from small business owners to entrepreneurs, to bring their ideas to life.”
**Madhav Jha, Co-Founder and CTO, Emergent**

“Gemini 3.7 Flash is a significant improvement over prior Flash models on legal work. Based on our early testing, the model lifts all-pass by 2.6 pts compared to Gemini 3.6 Flash on Legal Agent Bench, with broad gains in quality across practice areas.”
**Niko Grupen, Head of Applied Research, Harvey**

“The new Gemini Flash model delivered Opus-level grounding performance, nearly matching information recall with materially higher precision. Combined with faster and more token-efficient outcomes, it makes for a very intriguing model.”
**Adithya Ramanathan, Head of Agent Development & Research, Hebbia**

“On a subset of Harbor-Index run inside our DeepAgents harness, the model scored in the same band as the strongest models we tested, and it was the only model in our comparison to make progress on some tasks that defeated all the others. For a model in this tier, that is an excellent result on multi-step agentic work.”
**Nick Hollon, Software Engineer, LangChain**

“Gemini 3.7 Flash achieves on-par performance with mid-sized models such as GPT-5.6-Terra on our benchmarks, but at around half the cost, making it a strong contender in that category.”
**Kyrill Hux, Co-Founder, Nunu.ai**

“Gemini 3.7 Flash very efficiently implemented and audited its work on tasks porting Figma designs into code, with precise visual parity that other frontier models struggle with. I'm genuinely in a design 'psychosis' moment with this model. It just works.”
**Luke Parker, Senior Software Engineer, OpenCode**

“Google keeps making the strongest case that multimodal agents are ready for production — with Gemini 3.7 Flash, sharing video with a model becomes both natural and dramatically more efficient. It's supported in Pydantic AI from day one, alongside Gemini Live, which powers our new realtime agents.”
**Douwe Maan, Lead Developer, Pydantic AI**

“On a complex neurodegenerative disorder study experimental plan, I found Gemini 3.7 Flash's answer original and remarkably consistent with the latest experimental data. Compared to other models, this is the most compelling and accurate answer I have received coming very very close to what I see in the lab."
**Piere Rodriguez Aliaga Ph.D., Basic Life Research Scientist, Stanford Department of Biology**

“Gemini 3.5 Flash-Lite delivers the intelligence, speed, and cost efficiency needed for Ashler’s agentic retrieval and tool-use tasks. It excels at analyzing fragmented infrastructure records while maintaining context across hundreds of deliverables, supporting our users as they build the next generation of power grids, transportation networks, and data centers.”
**Connor Goggins, Co-founder & CTO, Ashler**

“Google Gemini 3.5 Flash-Lite is a huge jump from Gemini 3.1 Flash-Lite, punching way above its weight class. Gemini 3.5 Flash-Lite has proven incredibly fast and reliable. Ultimately, the model unlocks direct accessibility, giving users a highly responsive option they can choose on demand for smooth, uninterrupted execution.”
**Ashwin Kannan, Principal AI Engineer, Palo Alto Networks**

“Gemini 3.5 Flash-Lite landed on the Pareto frontier in our receipt extraction benchmark, offering one of the best tradeoffs we’ve tested between accuracy, latency, and cost. That combination is critical at Ramp, where we need to process receipts quickly and reliably at scale.”
**Veeral Patel, Head of Applied AI, Ramp**

See how Shopify is using Gemini 3.5 Flash

Shopify is running subagents in parallel to analyze complex data over a long horizon for more accurate merchant growth forecasts at a global scale.

See how Macquarie Bank is using Gemini 3.5 Flash

Macquarie Bank is piloting how 3.5 Flash can accelerate customer onboarding by reasoning over complex 100+ page documents, retrieving relevant information and making reliable recommendations with low latency.

See how Salesforce is using Gemini 3.5 Flash

Salesforce is integrating 3.5 Flash into Agentforce to reliably automate complicated enterprise tasks by deploying multiple subagents that retain context and execute complex, multi-turn tool calling.

See how Ramp is using Gemini 3.5 Flash

3.5 Flash is helping Ramp enable smarter, more reliable OCR through multimodal understanding of complex invoices combined with reasoning over historical patterns.

See how Xero is using Gemini 3.5 Flash

Xero is deploying agents to autonomously manage complex, multi-week workflows, such as identifying suppliers and gathering information for 1099 tax forms, enabling small businesses to automate tedious admin tasks.

See how Databricks is using Gemini 3.5 Flash

Databricks is using agentic workflows to monitor and retrieve real-time information, reason across massive datasets to diagnose issues, identify fixes and propose solutions for data scientists.