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Gemini 3.5 Flash Lite

Gemini 3.5 Flash Lite upgrades the agentic capability of the Flash-Lite tier, outperforming Gemini 3.1 Flash-Lite across thinking levels on coding, long context, and real-world task execution, with built-in computer use and a minimal default thinking level for high-throughput work. Your use is subject to Google's Terms & Privacy Policies.

ReasoningTool UseImplicit CachingFile InputVision (Image)Web Search
Use with AI GatewayView docs
import { streamText } from 'ai'


const result = streamText({
  model: 'google/gemini-3.5-flash-lite',
  prompt: 'Why is the sky blue?'
})
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Frequently Asked Questions

  • What changed in Gemini 3.5 Flash Lite compared to Gemini 3.1 Flash-Lite?

    Gemini 3.5 Flash Lite outperforms Gemini 3.1 Flash-Lite across thinking levels, most visibly on agentic work. It scores 54% on Terminal-Bench 2.1 against 31%, 72.2% on GDM-MRCR v2 against 60.1%, and 1140 on GDPval-AA v2 against 642. Computer use also ships as a built-in tool.

  • Why is Gemini 3.5 Flash Lite described as a subagent model?

    The upgraded agentic capability lets it handle a scoped part of a larger task reliably. A master agent on a heavier model decomposes the work, then dispatches bounded steps such as field extraction, batch translation, or JSON parsing to Gemini 3.5 Flash Lite, where per-step cost stays low enough to fan out widely.

  • How do thinking levels affect cost on Gemini 3.5 Flash Lite?

    Gemini 3.5 Flash Lite defaults to minimal. Higher levels add reasoning compute that counts toward output tokens, so each step up raises per-request cost. Use minimal and low for high-volume, latency-sensitive execution, and higher levels for multi-step subagent workloads.

  • Does Gemini 3.5 Flash Lite beat Gemini 3 Flash on any tasks?

    Yes, on several agentic and coding evaluations. Gemini 3.5 Flash Lite scores 54.2% on SWE-Bench Pro against 49.6% for Gemini 3 Flash, and 74.0% on OSWorld-Verified against 65.1%. Compare on your own workload before you move production traffic between tiers.

  • Does Gemini 3.5 Flash Lite support computer use?

    Yes, as a built-in tool. That lets a subagent step drive a browser or an application surface instead of only processing text, which is what makes scoped delegation practical at this tier.

  • Which inputs does Gemini 3.5 Flash Lite accept?

    Gemini 3.5 Flash Lite accepts multimodal input within a context window of 1M tokens and returns text, up to 65K tokens. See the Specs table on this page for the current modality list.

  • How much does Gemini 3.5 Flash Lite cost on AI Gateway?

    Current rates are $0.3 per million input tokens and $2.50 per million output tokens, listed on this page and subject to provider updates. AI Gateway reflects provider pricing with no markup and charges no platform fee on inference.

  • How do I call Gemini 3.5 Flash Lite on AI Gateway?

    Set the model to google/gemini-3.5-flash-lite using the AI SDK, the OpenAI-compatible Chat Completions endpoint, the Responses API, or another supported interface. AI Gateway handles provider routing, retries, and failover automatically.

  • When should I use google/gemini-3.6-flash instead?

    Use google/gemini-3.6-flash for the planning layer, hard coding tasks, and multimodal knowledge work. Use Gemini 3.5 Flash Lite for the high-volume steps underneath it, where the number of calls rather than the difficulty of any one call drives your bill.

  • How does Zero Data Retention work with Gemini 3.5 Flash Lite through AI Gateway?

    Yes, Zero Data Retention is available for this model. Zero Data Retention is offered on a per-provider basis. See https://vercel.com/docs/ai-gateway/capabilities/zdr for details.