Gemini 3.5 Flash Lite API: Endpoint & 15% Discount
Up to 15%Gemini 3.5 Flash Lite is available on LLM.API as an OpenAI-compatible chat endpoint—route Gemini Flash Lite quality through one key with transparent token pricing.
What is Gemini 3.5 Flash Lite?
On LLM.API, Gemini 3.5 Flash Lite (gemini-3.5-flash-lite) serves as a Gemini Flash Lite conversational model for products that need 1M tokens context windows and predictable token pricing. Fast Gemini model balancing multimodal reasoning, tool use, and cost.
Can you self-host Gemini 3.5 Flash Lite?
No. We found no public weights for Gemini 3.5 Flash Lite on Hugging Face, so there is nothing to download, quantize or serve on your own GPUs: no VRAM budget, no vLLM or GGUF build to plan for. The only way to run it is over an API.
Skip the deploy — use LLM.API as your endpoint
No GPUs, no quantization trade-offs. Same model, OpenAI-compatible, up to 15% below list price.
Providers
LLM.API routes Gemini 3.5 Flash Lite to the providers below, with discounted effective rates versus list price.
List price by provider
InputOutputProvider list prices; the LLM.API discount applies on top.
| Provider | Pricing | Context | Capabilities |
|---|---|---|---|
| in $0.3; out $2.5 per 1M tokens | 1M tokens | vision, tools, streaming, reasoning, web search, JSON, structured | |
| in $0.3; out $2.5 per 1M tokens | 1M tokens | vision, tools, streaming, reasoning, web search, JSON, structured | |
| in $0.3; out $2.5 per 1M tokens | 1M tokens | vision, tools, streaming, reasoning, web search, JSON, structured |
Prices and availability from the LLMAPI catalogue, updated nightly. Last updated 11 Oct 2026.
Try this model
Test Gemini 3.5 Flash Lite right here — free to start.
Suggestions for your first prompt
Code snippet
Call Gemini 3.5 Flash Lite through the OpenAI-compatible API — POST /v1/chat/completions.
Switching from OpenAI? Change 2 lines.
- base_url="https://api.openai.com/v1"
- api_key="YOUR_OPENAI_KEY"
+ base_url="https://api.llmapi.ai/v1"
+ api_key="YOUR_LLMAPI_KEY"Everything else stays the same — SDK, message format, tools, streaming. Set model to gemini-3.5-flash-lite and the call runs unchanged.
curl https://api.llmapi.ai/v1/chat/completions \
-H "Authorization: Bearer $LLMAPI_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gemini-3.5-flash-lite",
"messages": [
{"role": "user", "content": "Give me three crisp launch checklist items."}
],
"reasoning_effort": "medium"
}'from openai import OpenAI
client = OpenAI(
api_key="YOUR_LLMAPI_KEY",
base_url="https://api.llmapi.ai/v1",
)
resp = client.chat.completions.create(
model="gemini-3.5-flash-lite",
messages=[
{"role": "system", "content": "You are a precise product assistant."},
{"role": "user", "content": "Give me three crisp launch checklist items."},
],
reasoning_effort="medium",
)
print(resp.choices[0].message.content)import OpenAI from "openai";
const client = new OpenAI({
apiKey: process.env.LLMAPI_KEY,
baseURL: "https://api.llmapi.ai/v1",
});
const resp = await client.chat.completions.create({
model: "gemini-3.5-flash-lite",
messages: [
{ role: "user", content: "Give me three crisp launch checklist items." },
],
});
console.log(resp.choices[0].message.content);stream = client.chat.completions.create(
model="gemini-3.5-flash-lite",
messages=[{"role": "user", "content": "Write a haiku about latency."}],
stream=True,
)
for chunk in stream:
delta = chunk.choices[0].delta.content
if delta:
print(delta, end="", flush=True){
"model": "gemini-3.5-flash-lite",
"messages": [
{"role": "system", "content": "You are a precise product assistant."},
{"role": "user", "content": "Give me three crisp launch checklist items."}
],
"reasoning_effort": "medium"
}ENDPOINTS
Supported endpoints & features
Base URL https://api.llmapi.ai/v1 · model ID gemini-3.5-flash-lite · OpenAI-compatible.
POST /v1/chat/completionsChat Completions — supported
| Feature | Status | How to set it |
|---|---|---|
| Function calling (tools) | Supported | tools, tool_choice |
| Parallel tool calls | Not supported | parallel_tool_calls |
| JSON mode | Supported | response_format: {"type": "json_object"} |
| Structured outputs | Supported | response_format: {"type": "json_schema", …} |
| Streaming | Supported | stream: true |
| Vision (image input) | Supported | image_url content parts |
| Web search | Supported | web_search |
| Reasoning effort | minimal · low · medium · high | reasoning_effort: "medium" default medium |
ERRORS
Errors & fallback routing
| Code | What it means | What to do |
|---|---|---|
401 | Missing or invalid API key. | Send Authorization: Bearer YOUR_LLMAPI_KEY and check the key is active. |
429 | Rate limited, or the upstream provider is throttling the request. | Back off and retry with jitter; the gateway also retries the request on another provider where one is available. |
5xx | Upstream provider error or timeout. | Retry; fallback routing sends the retry to the next healthy provider for this model. |
When a provider fails or throttles, the request is routed to the next provider serving this model — the ones listed in the providers table above.
Gemini 3.5 Flash Lite in production
What the model is good at.
Multilingual drafting
Drafts and translates professional content across major business languages. Tuned to how teams typically call Gemini 3.5 Flash Lite.
Tool-ready dialogue
Works well in agent loops that call functions, browsers, or retrieval APIs. Tuned to how teams typically call Gemini 3.5 Flash Lite.
Instruction following
Follows detailed system and user instructions with strong adherence to format and tone. Grounded in the model's chat role rather than generic chat claims.
Safety-aware replies
Supports product policies with refusals and cautious handling of sensitive topics. Reflects Gemini Flash Lite positioning for this endpoint.
Structured outputs
Can produce JSON-friendly or schema-oriented responses when prompted carefully. Grounded in the model's chat role rather than generic chat claims.
What you get when you call Gemini 3.5 Flash Lite through LLM.API.
Unified AI Routing
Practical: Reach Gemini 3.5 Flash Lite and sibling models through one OpenAI-compatible endpoint.
One endpoint, every model.Cost Control
Compare provider price points and keep spend visible as you scale Gemini 3.5 Flash Lite.
More performance, less spend.Reliability Layer
Practical: Retry and route across configured providers when a single upstream blips.
Never go dark on users.Observability
Trace prompts, tokens, and errors for Gemini 3.5 Flash Lite alongside the rest of your stack.
See every token, everywhere.Drop-in SDKs
Production: Keep using familiar OpenAI client patterns with base URL https://api.llmapi.ai/v1.
Think tasks, not models.Model Breadth
Swap Gemini 3.5 Flash Lite for chat, media, or embedding alternatives without rewriting auth.
Scale from 1 to millions.
When to Use — When NOT to Use
Use it if...
- You need provider failover options exposed for this model id (Gemini 3.5 Flash Lite)
- You need a general-purpose text model for assistants, agents, or content workflows (Gemini 3.5 Flash Lite)
- You want OpenAI-compatible chat completions through a single LLM.API key (Gemini 3.5 Flash Lite)
- Your prompts benefit from the model's family strengths (reasoning, speed, or cost) (Gemini 3.5 Flash Lite)
Avoid if...
- You need guaranteed real-time hard latency SLAs without benchmarking the provider
- You need pure embedding, OCR, or media generation instead of chat
- You require on-prem only deployment with no cloud inference
- Your use case depends on unpublished proprietary benchmarks not listed here
BENCHMARKS
Gemini 3.5 Flash Lite benchmark scores
Intelligence index
Scale: 0-100 index points
Output speed
Scale: 0-400 tokens per second
Reference price per 1M tokens
Bars compare input and output list prices for this model.
Higher is better. The median covers every model tracked by Artificial Analysis.
Measured throughput; the full dial is 300 tokens per second.
Provider list prices, before the LLM.API discount.
Independent scores published by Artificial Analysis (source). Reference prices are provider list prices, not LLM.API pricing.
COMMUNITY
What developers say about Gemini models
Summarised from publicly published developer and community reviews of this model family. Opinions are the sources’, not LLM.API’s, and may not be specific to Gemini 3.5 Flash Lite.
- The Flash line is praised for speed and cost — reviewers regularly report code generated in seconds where slower models take minutes.
- The main caveat raised is confident hallucination on under-specified tasks, so reviewers recommend verification steps or a stronger model for critical output.
- Community reports highlight good long-context handling and strong multimodal input as the reasons teams keep Flash in the loop despite the accuracy caveats.
SOURCES
Frequently Asked Questions
Does Gemini 3.5 Flash Lite support streaming?
Yes—at least one listed provider advertises streaming.
How is Gemini 3.5 Flash Lite priced on LLM.API?
Listed pricing metadata shows: In $0.3 / 1M tokens · Out $2.5 / 1M tokens. LLM.API may offer discounted effective rates (illustrative ~30% callout vs list when available).. Confirm live rates in the LLM.API dashboard or docs before production budgeting.
What is the context length for Gemini 3.5 Flash Lite?
Reported context for Gemini 3.5 Flash Lite is 1M tokens. Always verify the active provider row if multiple providers are listed.
When should I choose Gemini 3.5 Flash Lite?
You need a general-purpose text model for assistants, agents, or content workflows — especially when you specifically need Gemini 3.5 Flash Lite.
What are limitations of Gemini 3.5 Flash Lite?
Like other API models, Gemini 3.5 Flash Lite can be wrong, incomplete, or uneven on edge cases. Validate outputs for high-stakes use. Media/OCR/STT models additionally depend on input quality.
Which providers serve Gemini 3.5 Flash Lite?
LLM.API currently lists: google-ai-studio, google-vertex. Availability can vary by region and account.
Can I use tools or structured outputs with Gemini 3.5 Flash Lite?
Tool and/or structured-output flags appear on one or more providers for this model—confirm in the providers table.
What modalities does Gemini 3.5 Flash Lite support?
Gemini 3.5 Flash Lite accepts text, image, video, audio and produces text according to its architecture metadata on LLM.API.
Where is the canonical page for Gemini 3.5 Flash Lite?
https://llmapi.ai/models/google-gemini-3-5-flash-lite/
How do I call Gemini 3.5 Flash Lite via API?
Send OpenAI-compatible requests to https://api.llmapi.ai/v1 with model "gemini-3.5-flash-lite" and your LLM.API key. See the code snippet on this page.
Is Gemini 3.5 Flash Lite a chat model?
Yes—Gemini 3.5 Flash Lite is exposed as a chat/completions-style endpoint on LLM.API.
What is Gemini 3.5 Flash Lite?
Fast Gemini model balancing multimodal reasoning, tool use, and cost. On LLM.API it is addressed as `gemini-3.5-flash-lite`.
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