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Documentation Index

Fetch the complete documentation index at: https://docs.hyprcore.ai/llms.txt

Use this file to discover all available pages before exploring further.

Speech models turn audio into text. Post-processing LLMs turn that text into something polished—a clean dictation, a meeting summary, an answer to a question. Hyprcore lets you pick whichever LLM you trust.

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Configure in one place

Open Settings → Models → Post-processing. Pick a provider and a model. The same selection drives:
  • Dictation post-processing
  • Meeting summaries and templates
  • Session chat answers
  • Action item extraction
You can override per-feature if you want, but most people pick one default and move on.

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Provider options

ProviderModelsWhere it runsCost
Hyprcore CloudClaude, GPT, Gemini (managed)Hyprcore servers, OpenRouter under the hoodPlan credits
Anthropic ClaudeSonnet, HaikuAnthropic APIBYOK
OpenAIGPT-4o, GPT-4o-miniOpenAI APIBYOK
Google GeminiFlash, ProGoogle APIBYOK
Groq LlamaLlama Scout, MaverickGroqBYOK
Apple IntelligenceOn-device foundation modelsYour Mac (Apple Silicon, macOS 15.1+)Free
OllamaWhatever you’ve pulledYour MacFree
LM StudioWhatever you’ve loadedYour MacFree

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Picking a model for the job

  • Dictation cleanup. Small/fast wins. GPT-4o-mini, Claude Haiku, Gemini Flash, or Apple Intelligence all do great. Avoid big slow models—they make every dictation sluggish.
  • Meeting summaries. Bigger models produce noticeably better summaries. Claude Sonnet, GPT-4o, or Gemini Pro. Worth the credits.
  • Session chat. Same as summaries—use a big model.
  • Code-heavy meetings. Claude Sonnet handles code in transcripts the most reliably.

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Bring your own key

For BYOK providers:
  1. Open Settings → Models → Post-processing.
  2. Pick the provider.
  3. Click Add API key.
  4. Paste your key.
Hyprcore stores keys in macOS Keychain—they’re encrypted at rest and never leave your Mac unless you make a request to the provider.

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Local LLMs (Ollama, LM Studio)

For maximum privacy, run an LLM locally:
1

Install Ollama or LM Studio

Both are free, separate apps. Install whichever you prefer.
2

Pull a model

For Ollama: ollama pull llama3.1:8b (or another model). For LM Studio: search and download from the LM Studio app.
3

Start the server

Ollama runs at http://localhost:11434 by default. LM Studio’s local server is at http://localhost:1234.
4

Point Hyprcore at it

Settings → Models → Post-processing → Provider: Ollama (or LM Studio) and pick the model. Hyprcore tests the connection.
Local LLMs are slower and dumber than the big cloud models. Llama 3.1 8B is a reasonable baseline for cleanup; for summaries, run a 70B if your hardware can handle it.

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Apple Intelligence

If you’re on macOS 15.1 or later with an Apple Silicon Mac and Apple Intelligence enabled, Hyprcore can route post-processing through Apple’s on-device foundation models. They’re free, fast, and fully private—but smaller, so quality is limited compared to Claude or GPT. Best uses: short dictation cleanup, simple summaries.