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Add gemini 3 flash blog
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Sameer Kankute
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docs/my-website/blog/gemini_3_flash/index.md
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docs/my-website/blog/gemini_3_flash/index.md
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---
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slug: gemini_3_flash
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title: "DAY 0 Support: Gemini 3 Flash on LiteLLM"
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date: 2025-11-19T10:00:00
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authors:
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- name: Sameer Kankute
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title: SWE @ LiteLLM (LLM Translation)
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url: https://www.linkedin.com/in/sameer-kankute/
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image_url: https://media.licdn.com/dms/image/v2/D4D03AQHB_loQYd5gjg/profile-displayphoto-shrink_800_800/profile-displayphoto-shrink_800_800/0/1719137160975?e=1765411200&v=beta&t=c8396f--_lH6Fb_pVvx_jGholPfcl0bvwmNynbNdnII
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- name: Krrish Dholakia
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title: "CEO, LiteLLM"
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url: https://www.linkedin.com/in/krish-d/
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image_url: https://pbs.twimg.com/profile_images/1298587542745358340/DZv3Oj-h_400x400.jpg
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- name: Ishaan Jaff
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title: "CTO, LiteLLM"
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url: https://www.linkedin.com/in/reffajnaahsi/
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image_url: https://pbs.twimg.com/profile_images/1613813310264340481/lz54oEiB_400x400.jpg
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tags: [gemini, day 0 support, llms]
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hide_table_of_contents: false
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---
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import Tabs from '@theme/Tabs';
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import TabItem from '@theme/TabItem';
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# Gemini 3 Flash Day 0 Support
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LiteLLM now supports `gemini-3-flash` and all the new API changes along with it.
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## What's New
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### 1. New Thinking Levels: `thinkingLevel` with MINIMAL & MEDIUM
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Gemini 3 Flash introduces granular thinking control with `thinkingLevel` instead of `thinkingBudget`.
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- **MINIMAL**: Ultra-lightweight thinking for fast responses
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- **MEDIUM**: Balanced thinking for complex reasoning
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- **HIGH**: Maximum reasoning depth
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### 2. Thought Signatures
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Like `gemini-3-pro`, this model also includes thought signatures for tool calls. LiteLLM handles signature extraction and embedding internally. [Learn more about thought signatures](../gemini_3/index.md#thought-signatures).
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---
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## Supported Endpoints
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LiteLLM provides **full end-to-end support** for Gemini 3 Flash on:
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- ✅ `/v1/chat/completions` - OpenAI-compatible chat completions endpoint
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- ✅ `/v1/responses` - OpenAI Responses API endpoint (streaming and non-streaming)
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- ✅ [`/v1/messages`](../../docs/anthropic_unified) - Anthropic-compatible messages endpoint
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- ✅ `/v1/generateContent` – [Google Gemini API](https://cloud.google.com/vertex-ai/docs/generative-ai/model-reference/gemini#rest) compatible endpoint (for code, see: `client.models.generate_content(...)`)
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All endpoints support:
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- Streaming and non-streaming responses
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- Function calling with thought signatures
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- Multi-turn conversations
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- All Gemini 3-specific features
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- Converstion of provider specific thinking related param to thinkingLevel
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## Quick Start
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<Tabs>
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<TabItem value="sdk" label="SDK">
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**Basic Usage with MEDIUM thinking (NEW)**
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```python
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from litellm import completion
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# No need to make any changes to your code as we map openai reasoning param to thinkingLevel
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response = completion(
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model="gemini-3-flash",
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messages=[{"role": "user", "content": "Solve this complex math problem: 25 * 4 + 10"}],
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reasoning_effort="medium", # NEW: MEDIUM thinking level
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)
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print(response.choices[0].message.content)
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```
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</TabItem>
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<TabItem value="proxy" label="PROXY">
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**1. Setup config.yaml**
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```yaml
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model_list:
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- model_name: gemini-3-flash
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litellm_params:
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model: gemini/gemini-3-flash
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api_key: os.environ/GEMINI_API_KEY
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```
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**2. Start proxy**
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```bash
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litellm --config /path/to/config.yaml
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```
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**3. Call with MEDIUM thinking**
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```bash
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curl http://localhost:4000/v1/chat/completions \
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-H "Content-Type: application/json" \
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-H "Authorization: Bearer <YOUR-LITELLM-KEY>" \
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-d '{
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"model": "gemini-3-flash-reasoning",
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"messages": [{"role": "user", "content": "Complex reasoning task"}],
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"reasoning_effort": "medium"
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}'
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```
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</TabItem>
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</Tabs>
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---
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## All `reasoning_effort` Levels
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<Tabs>
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<TabItem value="minimal" label="MINIMAL">
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**Ultra-fast, minimal reasoning**
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```python
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from litellm import completion
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response = completion(
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model="gemini-3-flash",
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messages=[{"role": "user", "content": "What's 2+2?"}],
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reasoning_effort="minimal",
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)
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```
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</TabItem>
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<TabItem value="low" label="LOW">
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**Simple instruction following**
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```python
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response = completion(
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model="gemini-3-flash",
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messages=[{"role": "user", "content": "Write a haiku about coding"}],
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reasoning_effort="low",
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)
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```
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</TabItem>
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<TabItem value="medium" label="MEDIUM (NEW)">
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**Balanced reasoning for complex tasks** ✨
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```python
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response = completion(
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model="gemini-3-flash",
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messages=[{"role": "user", "content": "Analyze this dataset and find patterns"}],
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reasoning_effort="medium", # NEW!
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)
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```
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</TabItem>
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<TabItem value="high" label="HIGH">
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**Maximum reasoning depth**
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```python
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response = completion(
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model="gemini-3-flash",
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messages=[{"role": "user", "content": "Prove this mathematical theorem"}],
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reasoning_effort="high",
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)
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```
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</TabItem>
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</Tabs>
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---
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## Key Features
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✅ **Thinking Levels**: MINIMAL, LOW, MEDIUM, HIGH
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✅ **Thought Signatures**: Track reasoning with unique identifiers
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✅ **Seamless Integration**: Works with existing OpenAI-compatible client
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✅ **Backward Compatible**: Gemini 2.5 models continue using `thinkingBudget`
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---
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## Installation
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```bash
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pip install litellm --upgrade
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```
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```python
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import litellm
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from litellm import completion
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response = completion(
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model="gemini-3-flash",
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messages=[{"role": "user", "content": "Your question here"}],
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reasoning_effort="medium", # Use MEDIUM thinking
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)
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print(response)
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```
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## `reasoning_effort` Mapping for Gemini 3+
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| reasoning_effort | thinking_level |
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|------------------|----------------|
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| `minimal` | `minimal` |
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| `low` | `low` |
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| `medium` | `medium` |
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| `high` | `high` |
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| `disable` | `minimal` |
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| `none` | `minimal` |
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