logancyang_obsidian-copilot/docs/models-and-parameters.md

Models and Parameters

This guide explains how to manage chat models, embedding models, and the parameters that control how the AI behaves.

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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-flash-preview	OpenRouter	Vision, Reasoning
google/gemini-3.1-pro-preview	OpenRouter	Vision, Reasoning
openai/gpt-5.2	OpenRouter	Vision
openai/gpt-5-mini	OpenRouter	Vision
gpt-5.2	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	Google	Vision
gemini-2.5-flash	Google	Vision
gemini-3-flash-preview	Google	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:

1. Go to Settings → Copilot → Model
2. Click Add Model
3. Enter the model name exactly as the provider expects it (e.g., gpt-4-turbo-preview)
4. Select the provider
5. Optionally set a custom base URL (useful for proxies or alternate endpoints)
6. Save

Importing Models from Provider

You can automatically import the full list of available models from a provider:

1. Go to Settings → Copilot → Model
2. Find the Import models button for your provider
3. Copilot will fetch the provider's model list and add new ones

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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	Google
gemini-embedding-001	Google
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

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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.

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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).

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Related

• LLM Providers — Set up API keys for your provider
• Vault Search and Indexing — How embedding models are used