# Gemini 3.6 Flash & 3.5 Flash-Lite: Developer guide > Source: > Published: 2026-07-21 16:08:54+00:00 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