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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.

Hyprcore is designed to be extensible. If you have a fine-tuned Whisper model, want to plug in a community variant like Moonshine or SenseVoice, or run an LLM fully on-device, you can.

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Custom Whisper models

Hyprcore auto-discovers any Whisper GGML .bin model placed in your models directory.
1

Get a model

Download a Whisper GGML .bin file from anywhere—Hugging Face is the most common source. Many fine-tuned variants exist for specific languages or domains.
2

Drop it in the models directory

The directory is ~/Library/Application Support/ai.hyprcore.desktop/models/. Place the .bin file directly inside.
3

Restart Hyprcore

On the next launch, your model appears in Settings → Models under “Custom Models”. The display name comes from the filename: my-model.bin becomes “My Model”.
Custom models are user-provided and unsupported. If a model crashes Hyprcore, swap it out and report it via Discord—but don’t expect official help. The model has to be valid Whisper GGML format; otherwise it just won’t load.

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Specialized speech models

Hyprcore ships several specialized models beyond Whisper and Parakeet:
  • NVIDIA Canary. Multilingual NeMo model with strong English / Spanish / French / German accuracy.
  • Moonshine. Small and fast English-only models, optimized for low-latency dictation.
  • SenseVoice. Multi-language model with emotion recognition.
  • Breeze. Optimized for Traditional Chinese.
  • GigaAM. Russian-language models.
These appear as alternative download targets in Settings → Models. Pick whichever fits the language or use case you record most.

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Ollama for LLMs

For a fully local LLM:
1

Install Ollama

ollama.com/download. It runs as a background service.
2

Pull a model

From a terminal:
ollama pull llama3.1:8b      # 4.7 GB, decent quality
ollama pull qwen2.5:14b      # 9 GB, good for summaries
ollama pull llama3.1:70b     # 40 GB, near-cloud quality
3

Configure in Hyprcore

Settings → Models → Post-processing → Provider: Ollama. The dropdown lists every model you’ve pulled. Pick one and Hyprcore will test the connection.
Ollama also serves embedding models for semantic search: 
ollama pull nomic-embed-text       # fast and good
ollama pull mxbai-embed-large      # higher quality, slower
Configure in Settings → Intelligence → Embedding provider → Ollama.

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LM Studio

LM Studio is a GUI alternative to Ollama. The setup is the same—install, download a model, start the local server, and point Hyprcore at http://localhost:1234. Pros over Ollama: nicer UI for browsing models, supports more model formats out of the box.

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OpenRouter

If you want one API to access dozens of models (Anthropic, OpenAI, Google, Mistral, Meta, …) without juggling keys, use OpenRouter. Settings → Models → Post-processing → Provider: OpenRouter and paste your key. This is also what powers Hyprcore Cloud under the hood, so picking OpenRouter directly gives you the same model selection at OpenRouter’s pricing.