whereismyai
Homi
Homi is an open decision model that processes audio clips and questions to return option probabilities.
Homi is an open decision model that takes in audio natively along with typed questions, returning a probability for every option without generating text. Based on Qwen3-Omni-30B-A3B-Instruct with frozen weights, a decision head, and LoRA parameters, it handles paralinguistic and phonological questions that transcripts miss. It provides yes/no, choice, and score question types for tasks like audio monitoring and evaluation. The codebase includes inference scripts, evaluation runners, and training data pipelines. It is released under the Apache-2.0 license for both code and weights.
Homi at a glance
- Best for: Researcher
- Runs on: self-hosted, open source
- Pricing: Free
- Released: October 2026
- Category: AI research tool
- Website: github.com/egma-ai/homi
Key features
- Answers typed questions about audio clips
- Returns a probability for every option
- Supports yes/no, choice, and score question types
- Uses frozen Qwen3-Omni-30B-A3B-Instruct base weights
- Includes inference code and a command-line interface
- Provides evaluation benchmarks and runners
- Includes training data builders and recipes
Use it for
- Monitoring and evaluating large-scale audio at low cost
- Answering paralinguistic and phonological audio questions
- Assessing speech pitch, speed, volume, and emotion
Alternatives to Homi
- Oumi — Automates model training and evaluation to cut costs and improve accuracy.
- NanoJev — It runs parallel decisions and outputs probability distributions without output-token decoding.
- Decido — Runs locally on CPU while beating published benchmark scores.
- Vegaml — Runs locally on your hardware with calibrated probabilities and conformal answer sets.
- LMMs-Eval — Provides open research and tooling for multimodal model evaluation and benchmarks.
- OpenCompass — It offers an objective, comprehensive, and credible open-source AI evaluation system.
- Ncm — Generates text significantly faster than diffusion baselines while maintaining high quality.
- Vev — Runs locally on NVIDIA hardware with a fast, Jev-compatible API.
- SemIf OpenJev — Extracts direct token probabilities without generating text or running JSON repair loops.
- Hemory — Connects real-world conversations to your AI agents via MCP.
- Anime Text Dataset — Provides structured anime data with field-level provenance and question-answering pairs.
- Blumify — Tracks daily interviews and speeches of prominent AI leaders.
All Homi alternatives