* feat(models): replace gemini-3-flash-preview with GA gemini-3.5-flash Swap the preview Gemini flash builtin for the now-GA gemini-3.5-flash across the Google and OpenRouter providers, enable it by default, and update the user-facing model docs. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * chore(models): drop older Gemini 2.5 builtins, keep latest per family Remove the Gemini 2.5 pro/flash builtins (Google + OpenRouter), leaving only the latest of each family: gemini-3.1-pro-preview, gemini-3.5-flash, and gemini-3.1-flash-lite. Reassign the default, required, and Google test model roles from gemini-2.5-flash to gemini-3.5-flash. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * chore(models): keep gemini-2.5-pro as the GA Gemini pro builtin gemini-3.1-pro is preview-only on the public Gemini API, so retain gemini-2.5-pro (Google + OpenRouter) to guarantee at least one GA Gemini pro model in the builtin list. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * chore(models): keep gemini-2.5-flash default, add gemini-3.5-flash alongside Restore gemini-2.5-flash (Google + OpenRouter) and its default, required, core, and Google test-model roles. gemini-3.5-flash stays as an additional enabled builtin rather than taking over the default. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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Models and Parameters
This guide explains how to manage chat models, embedding models, and the parameters that control how the AI behaves.
Chat Models
Built-In Models
Copilot comes with a set of built-in models across many providers. Some are always included ("core" models); others can be enabled or disabled.
| Model | Provider | Capabilities |
|---|---|---|
| copilot-plus-flash | Copilot Plus | Vision (Plus exclusive) |
| google/gemini-2.5-flash | OpenRouter | Vision |
| google/gemini-2.5-pro | OpenRouter | Vision |
| google/gemini-3.5-flash | OpenRouter | Vision, Reasoning |
| google/gemini-3.1-pro-preview | OpenRouter | Vision, Reasoning |
| openai/gpt-5.4 | OpenRouter | Vision |
| openai/gpt-5-mini | OpenRouter | Vision |
| gpt-5.4 | OpenAI | Vision |
| gpt-5-mini | OpenAI | Vision |
| gpt-4.1 | OpenAI | Vision |
| gpt-4.1-mini | OpenAI | Vision |
| claude-opus-4-6 | Anthropic | Vision, Reasoning |
| claude-sonnet-4-5-20250929 | Anthropic | Vision, Reasoning |
| gemini-2.5-pro | Vision | |
| gemini-2.5-flash | Vision | |
| gemini-3.5-flash | Vision, Reasoning | |
| grok-4-1-fast | XAI | Vision |
| deepseek-chat | DeepSeek | — |
| deepseek-reasoner | DeepSeek | Reasoning |
Model Capability Badges
Models may show capability badges:
- Reasoning — Extended internal thinking before responding; better for complex tasks
- Vision — Can process images (e.g., screenshots, diagrams embedded in notes)
- Web Search — Can access the internet directly (model-native feature)
Managing Models
Go to Settings → Copilot → Model to see the full model list.
- Enable/disable — Toggle individual models on or off to control what appears in the model selector
- Reorder — Drag models to change their order in the dropdown
- Delete — Remove custom models you've added
Adding Custom Models
If your provider offers a model that isn't in the built-in list, you can add it manually:
- Go to Settings → Copilot → Model
- Click Add Model
- Enter the model name exactly as the provider expects it (e.g.,
gpt-4-turbo-preview) - Select the provider
- Optionally set a custom base URL (useful for proxies or alternate endpoints)
- Save
Importing Models from Provider
You can automatically import the full list of available models from a provider:
- Go to Settings → Copilot → Model
- Find the Import models button for your provider
- Copilot will fetch the provider's model list and add new ones
Embedding Models
Embedding models convert text into numerical vectors, which powers semantic (meaning-based) search in Vault QA and the "Relevant Notes" feature.
Built-In Embedding Models
| Model | Provider |
|---|---|
| copilot-plus-small | Copilot Plus (Plus exclusive) |
| copilot-plus-large | Copilot Plus (Believer exclusive) |
| copilot-plus-multilingual | Copilot Plus (Plus exclusive) |
| openai/text-embedding-3-small | OpenRouter |
| text-embedding-3-small | OpenAI |
| text-embedding-3-large | OpenAI |
| embed-multilingual-light-v3.0 | Cohere |
| text-embedding-004 | |
| gemini-embedding-001 | |
| Qwen3-Embedding-0.6B | SiliconFlow |
Selecting an Embedding Model
Go to Settings → Copilot → QA → Embedding Model.
If you change embedding models, you must rebuild the vault index because the old vectors are incompatible with the new model. Copilot will prompt you to confirm before rebuilding.
What Embeddings Affect
- Vault QA mode — Uses embeddings to find relevant notes by meaning
- Semantic Search — The "Enable Semantic Search" toggle in QA settings
- Relevant Notes — Shows semantically similar notes in the sidebar
Model Parameters
These settings control how the AI responds. Global defaults live in Settings → Copilot → Model. You can override them per-session using the gear icon in the chat panel.
Temperature
Controls how random or creative the responses are.
- Range: 0.0–1.0
- Default: 0.1
- Low (0.0–0.2): Precise, factual, deterministic
- Medium (0.4–0.6): Balanced
- High (0.8–1.0): Creative, varied, less predictable
Max Tokens
Maximum number of tokens in the AI's response. A token is roughly ¾ of a word (so 1,000 tokens ≈ 750 words).
- Default: 6,000
- Higher values allow longer responses but cost more
Conversation Turns in Context
How many past conversation turns to include in each request. More turns = more context but larger requests.
- Default: 15 turns
- Reduce this if you hit context limits or want to lower costs
Auto-Compact Threshold
When the conversation reaches this many tokens, older messages are automatically summarized.
- Default: 128,000 tokens
- Range: 64,000–1,000,000 tokens
- See Chat Interface for details
Reasoning Effort
For reasoning-capable models (like deepseek-reasoner, claude-opus-4-6), controls how much internal reasoning the model does before responding.
- Options: minimal, low, medium, high, xhigh
- Default: low
- Higher effort = better results on complex tasks, slower responses
Verbosity
For models that support it, controls response length and detail.
- Options: low, medium, high
- Default: medium
Top P
An alternative to temperature for controlling randomness. Leave at default unless you have a specific reason to change it.
Frequency Penalty
Reduces the likelihood of the model repeating itself.
Default Model Selection
Your default model is the one Copilot uses when you open a new chat. Set it in: Settings → Copilot → Basic → Default Chat Model
The default is OpenRouter Gemini 2.5 Flash (requires OpenRouter API key).
Related
- LLM Providers — Set up API keys for your provider
- Vault Search and Indexing — How embedding models are used