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