Gemini 3.6 Flash & 3.5 Flash-Lite: Developer guide

Google has made Gemini 3.6 Flash and Gemini 3.5 Flash-Lite generally available for production use. Gemini 3.6 Flash offers stronger performance on complex agentic and multimodal tasks with reduced token usage at a lower price than 3.5 Flash, while Gemini 3.5 Flash-Lite is the fastest, lowest-cost model in the 3.5 family for high-throughput execution.

Gemini 3.6 Flash gemini-3.6-flash and Gemini 3.5 Flash-Lite gemini-3.5-flash-lite are generally available GA and ready for production use. - Gemini 3.6 Flash : Stronger performance on complex agentic and multimodal tasks while reducing token usage, at a lower price point than 3.5 Flash. - Gemini 3.5 Flash-Lite : The fastest, lowest-cost model in the 3.5 family. Outperforms prior Flash-Lite generations for high-throughput execution. This guide explains what's new in each model, what API changes affect your code, and how to migrate. Tip : You can automate this migration with a coding agent that supports skills https://ai.google.dev/gemini-api/docs/coding-agents gemini-interactions-api like Antigravity . Run /gemini-interactions-api migrate my app to Gemini 3.6 Flash New models | Model | Model ID | Default thinking level | Pricing | Description | | Gemini 3.6 Flash | gemini-3.6-flash | medium | $1.50/1M input tokens and $7.50/1M output tokens | Balances speed with intelligence for agentic and multimodal tasks. | | Gemini 3.5 Flash-Lite | gemini-3.5-flash-lite | minimal | $0.30/1M input tokens and $2.50/1M output tokens | The fastest, lowest-cost 3.5 model for high-throughput execution. | Both models support the 1M token context window, 64k max output tokens, thinking, and the full suite of built-in tools including Computer Use https://ai.google.dev/gemini-api/docs/computer-use . For complete specs, see the model pages: For detailed pricing, see the pricing page https://ai.google.dev/gemini-api/docs/pricing . Quickstart What's new in Gemini 3.6 Flash - Token and turn reduction: Completes multi-step workflows with fewer reasoning steps, conversational turns, and tool calls than Gemini 3.5. It also reduces execution loop spiraling. - Improved code generation: Produces higher quality production-ready code with fewer unwanted edits and fewer debugging loops. - Better instruction following : Reduces unwanted file changes during diagnostic tasks. - Strong multimodal and spatial reasoning: Improved performance on chart interpretation, visual blueprint conversion, and multi-element web layout generation. - Upfront programmatic inspection: Prefers running diagnostic code scripts before making changes more frequently than Gemini 3.5 Flash. This improves accuracy on complex tasks, but can add extra exploratory steps on simple frontend work. - Computer Use support: Supported as native tool for agentic UI automation. - UI styling preference : Better at creating functional code, though human evaluators preferred earlier models for visual layout and styling. You can mitigate this by providing explicit design guidelines. - Default thinking effort medium : Uses the same medium default thinking level as Gemini 3.5 Flash. - Reduced pricing : Lower output token costs $7.50/1M vs. $9.00/1M for 3.5 Flash . Input tokens remain at $1.50/1M. What's new in Gemini 3.5 Flash-Lite - Reduced task execution latency: Highest throughput in the 3.5 family for high-volume data parsing and document extraction. - Enhanced reasoning and multimodal performance: Strong migration path from Gemini 2.5 Flash, with higher scores on reasoning tasks like HLE 18.0% vs. 11.0% and multimodal benchmarks like CharXIV 74.5% vs. 63.7% . - Subagent orchestration and tool reliability: Improves tool execution reliability for code execution, search, and MCP workflows. Increase the thinking level for autonomous planning and complex subagent tasks. - Improved document understanding: Improves accuracy on document parsing and structured data extraction. Experiment with both minimal and high thinking levels depending on document complexity. - Interactive web coding and tabular data processing: Performs strongly on frontend JavaScript and tabular data processing by planning via lightweight code execution. - Chatbot and persona persistence: Stronger multi-turn instruction following and persona consistency over Gemini 3.1 Flash-Lite. - Computer Use support: Supported as native tool for agentic UI automation. Choosing the right Flash or Flash-Lite model Use this table to select the right model and migration path for your workloads. Both models require removing deprecated sampling parameters temperature , top p , top k and prefilled model turns. See API changes for details. | Model | Primary use cases | Recommended migration target | Gemini 3.6 Flash gemini-3.6-flash | Code generation, spatial/multimodal reasoning, multi-step agentic workflows | Gemini 3.5 Flash , Gemini 3 Flash Preview , or Gemini 3.1 Pro | Gemini 3.5 Flash-Lite gemini-3.5-flash-lite | Autonomous subagent execution, high-volume data analysis and document extraction, structured JSON parsing | Gemini 3.1 Flash-Lite or Gemini 2.5 Flash | Updated Antigravity agent Due to its improved performance, Gemini 3.6 Flash is now the new default model powering the Antigravity agent https://ai.google.dev/gemini-api/docs/antigravity-agent in Gemini Managed Agents. This can be changed by setting a new field on the API. API changes and parameter updates Starting with Gemini 3.6 Flash and Gemini 3.5 Flash-Lite, the following API changes apply to these models and all future Gemini model releases. - Sampling parameter deprecation : temperature , top p , and top k are deprecated. The API ignores these parameters and returns an error in future model generations. - Prefilled model turn validation : Prefilling model turns is no longer supported. If the last non-empty turn in the request is a model turn, the API returns a 400 error. Below are detailed explanations and code samples for each API change. 1. Sampling parameter deprecation temperature , top p , top k temperature , top p , and top k are deprecated and ignored. In future model generations, supplying these parameters returns an HTTP 400 error. Remove these parameters from all requests. To improve determinism, define a system instruction with explicit rules for your specific use case. 2. Prefilled model turn validation {: prefilled-model-turn-validation} API requests ending with a non-empty model role turn are disallowed and return an HTTP 400 Error . ⚠️ Avoid In legacy generateContent or raw REST payloads, ending with a model role turn is now disallowed: ✅ Recommended Migration Interactions API In the Interactions API, model turns are not manually prefilled. If your application previously prefilled a model turn to suppress preambles or force JSON formatting, use system instruction or Structured outputs https://ai.google.dev/gemini-api/docs/structured-output instead. Migration checklist Tip : You can automate this migration with a coding agent that supports skills https://ai.google.dev/gemini-api/docs/coding-agents gemini-interactions-api like Antigravity . Run /gemini-interactions-api migrate my app to Gemini 3.6 Flash Migrate to gemini-3.6-flash - Update Model ID: Change your target model string to gemini-3.6-flash . - Remove deprecated sampling parameters: - Strip temperature , top p , and top k from generation configs. - Replace thinking budget with the string enum thinking level set to "medium" or "high" . - Remove candidate count unsupported in Gemini 3.x . - Enforce turn validation rules: - Standardize multi-turn conversations on server-side previous interaction id . - Remove prefilled model turns. - Audit function calling: - Place multimodal assets inside the response payload. - Format inline instructions using \n\n . - If you see Malformed Function Call errors tied to pre-tool text, see Workarounds for pre-tool text requirements https://ai.google.dev/gemini-api/docs/function-calling workarounds-for-pre-tool-text-requirements . - Only if using generateContent API: Ensure all FunctionResponse objects include call id and name . - Baseline Gemini 3.x requirements: For SDK updates and thought signature preservation, see the Gemini 3.5 Migration Checklist https://ai.google.dev/gemini-api/docs/whats-new-gemini-3.5 migration . Migrate to gemini-3.5-flash-lite - Update Model ID: Change your target model string to gemini-3.5-flash-lite . - Configure thinking effort level: - For high-volume extraction, routing, or classification: leave thinking level at "minimal" default for maximum throughput. - For autonomous subagents with tool calls, code execution, or multi-step reasoning: set thinking level to "medium" or "high" to prevent premature tool termination. - Remove deprecated parameters and validate function calling: Apply the same rules as for 3.6 Flash above. - Baseline Gemini 3.x requirements: Refer to the Gemini 3.5 Migration Checklist https://ai.google.dev/gemini-api/docs/whats-new-gemini-3.5 migration . Next steps