# Gemini 2.5 Flash Lite API

Google's Gemini 2.5 Flash Lite, through an OpenAI-compatible API. Providers quote it on an open exchange, and each request goes to the offer with the lowest estimated charge that meets your rules.

- Providers compete for each request. The exchange ranks the offers that meet your rules by estimated charge. It fixes your maximum charge before the first token, and you pay for the tokens that the model uses.
- The OpenAI and Anthropic APIs. Use the OpenAI or Anthropic SDK that you have. Set the base URL and your key, and send gemini-2.5-flash-lite as the model.
- Your data rules. Send x-liquid-retention: none and only offers whose provider does not keep your content compete for the request.

## Facts

- Model name: gemini-2.5-flash-lite
- Maker: Google
- Context window: 1M tokens
- Input price: $0.100 per million tokens
- Output price: $0.399 per million tokens
- Providers: 1 independent provider
- Regions: us

## Providers

- [Architect](https://liquidinference.ai/providers/805445a7-0e40-4c1b-9baf-7b3b01e30e42.md): us, $0.100 input and $0.399 output per million tokens, $0.0100 cache read per million tokens, 1M tokens of context

## Scores

- HLE: 3.7, #253 of 273
- GPQA: 47.4, #214 of 250
- AA-LCR: 32.0, #195 of 237
- Terminal-Bench Hard: 2.3, #154 of 166
- LiveCodeBench: 40.0, #71 of 130
- AIME 2025: 35.3, #63 of 100
- MMLU-Pro: 72.4, #84 of 133
- τ²-Bench: 19.0, #152 of 169
- IFBench: 31.5, #160 of 178

Scores: Artificial Analysis (https://artificialanalysis.ai/)

## Request

```sh
curl https://router.inference.ai.exchange/v1/chat/completions \
  -H "Authorization: Bearer $LIQUID_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-2.5-flash-lite",
    "messages": [{"role":"user","content":"Say hello."}]
  }'
```

## Questions

### What is Gemini 2.5 Flash Lite?

Served by intent-router: each job goes to the cheapest healthy upstream for this model.

### How much does Gemini 2.5 Flash Lite cost?

Offers now ask $0.100 per million input tokens and $0.399 per million output tokens. A job pays for the tokens it uses. The exchange picks the cheapest eligible offer.

### What is the context length of Gemini 2.5 Flash Lite?

The largest offer takes 1,048,576 input tokens. A smaller offer can take less. The exchange skips an offer that cannot take your message.

### What can Gemini 2.5 Flash Lite do?

Its providers list Vision, Reasoning effort, JSON object, JSON schema, Frequency penalty, Logit bias, Log probabilities, Min-p sampling, Presence penalty, Repetition penalty, Seed, Stop sequences, Top-k sampling, Top-p sampling, Text, Tools.

### What inputs and outputs does Gemini 2.5 Flash Lite support?

Text · Images → Text.

### Which providers serve Gemini 2.5 Flash Lite?

1 independent provider quote it now, with 1 offer. The table above ranks them by the cost of a typical job.

### How do I call Gemini 2.5 Flash Lite?

Send "gemini-2.5-flash-lite" as the model in an OpenAI or Anthropic request. The API section links to setup steps for each client.

### When was Gemini 2.5 Flash Lite listed?

The exchange first listed it on 10/8/2026. This is not its release date.

## Related pages

- [This page in a browser](https://liquidinference.ai/models/gemini-2.5-flash-lite)
- [Gemma 4 26B a4b It:thinking](https://liquidinference.ai/models/gemma-4-26b-a4b-it%3Athinking.md)
- [Diffusiongemma](https://liquidinference.ai/models/diffusiongemma.md)
- [Gemma 3 27B It](https://liquidinference.ai/models/gemma-3-27b-it.md)
- [Gemma 3 4B It](https://liquidinference.ai/models/gemma-3-4b-it.md)
- [Gemma 4 12B It Semancer](https://liquidinference.ai/models/gemma-4-12b-it-semancer.md)
- [Gemma 4 12B It](https://liquidinference.ai/models/gemma-4-12b-it.md)
- [Set up a client](https://liquidinference.ai/connect/gemini-2.5-flash-lite)
- [All models](https://liquidinference.ai/models)
- [Providers](https://liquidinference.ai/providers.md)
- [Discover the best model for your budget](https://liquidinference.ai/discover)
- [Quickstart](https://liquidinference.ai/docs/quickstart.md)
- [llms.txt: the index of every page, as Markdown](https://liquidinference.ai/llms.txt)
- [llms-full.txt: every page in one file](https://liquidinference.ai/llms-full.txt)