d1-omni is a 600M decision model from Liquid AI, built on LFM2.5-Encoder-350M. Give it a state (text or JSON, with images or a short voice clip) and a set of typed questions, and it returns a calibrated probability for every answer in a single forward pass.

It works through Ollama’s /v1/systemone endpoint and ollama run --ask.

Highlights

• Edge-sized: 587M parameters, a 0.85 GB download. The same trunk handles every modality, with small vision (94M) and audio (112M) encoders.
• Images: one or more images per state; large frames are tiled.
• Speech: up to 30 seconds of English speech per request.
• One forward pass: every option of every question is scored together, with no output tokens.

For the most accurate decisions over text and images, use d1, Liquid AI’s 3B model. Use d1-omni when size matters or you need audio.

Usage

ollama run d1-omni --ask "Is this support request urgent?" < ticket.txt

curl http://localhost:11434/v1/systemone -d '{
  "model": "d1-omni",
  "state": "Our app crashes on launch for every user since this morning'\''s update. Please fix it now.",
  "questions": {
    "urgent": {"type": "noul", "instructions": "Is this support request urgent?"},
    "team": {
      "type": "choice",
      "instructions": "Which team should handle this request?",
      "criteria": {
        "billing": "Payments, invoices, and refunds",
        "technical": "Outages, errors, and configuration",
        "sales": "Plans and upgrades"
      }
    }
  }
}'

d1-omni answers urgent with 0.998 and picks technical with probability 0.995.

Speech

Put one base64-encoded WAV clip in images, and send audio or images, not both. Clips are cut at 30 seconds. The audio training data was English requests from a speaker to an assistant, so questions about what kind of utterance it is, its topic, and what the speaker wants work best.

curl http://localhost:11434/v1/systemone -d '{
  "model": "d1-omni",
  "state": "Voice message from a customer.",
  "images": ["<base64-encoded WAV>"],
  "questions": {
    "intent": {
      "type": "choice",
      "instructions": "What does the speaker want?",
      "criteria": {"timer": "Set a timer or alarm", "music": "Play music", "weather": "Hear the weather", "other": null}
    }
  }
}'

Images

The model was trained with up to 896 tokens of text alongside images, so keep the state and questions short when you send images.

Benchmarks

Accuracy reported by Liquid AI on public benchmarks framed as decisions. See the model card for details.

On the harder Decision Index 0.2.1, Liquid AI reports 15.95 for d1-omni and 48.57 for d1.

License

LFM Open License v1.0