logancyang_obsidian-copilot/docs/models-and-parameters.md
Logan Yang 05a0d03fd9
feat(models): add GA gemini-3.5-flash builtin (#2492)
* 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>
2026-05-20 18:00:00 -07:00

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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 Google Vision
gemini-2.5-flash Google Vision
gemini-3.5-flash 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

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 → QAEmbedding 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: 0.01.0
  • Default: 0.1
  • Low (0.00.2): Precise, factual, deterministic
  • Medium (0.40.6): Balanced
  • High (0.81.0): 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: 64,0001,000,000 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).