VibeVoice 1.5B (GGUF, Q4_K_M)
Production-ready GGUF quantization of fixie-ai/ultravox-v0_5-llama-3_2-1b for distributed speech synthesis โ powered by the Aether edge inference runtime.
Highlights
- 1.5B parameters โ High-quality voice model. Richer speech synthesis with improved naturalness and expressiveness.
- ~0.9 GB Q4_K_M quantized โ optimized for distributed edge inference
- LLaMA architecture โ proven, stable, well-tested
- Aether runtime compatible โ layer-sharded across distributed nodes via Edgework.ai
Model Details
| Property | Value |
|---|---|
| Base model | fixie-ai/ultravox-v0_5-llama-3_2-1b |
| Parameters | 1.5B |
| Architecture | LLaMA |
| Quantization | Q4_K_M |
| Format | GGUF |
| Size | ~0.9 GB |
| License | apache-2.0 |
Usage
With llama.cpp
./llama-cli -m vibevoice-1.5b-q4_k_m.gguf -p "Your prompt here" -n 256
With Aether (Distributed Inference)
This model is deployed across the Aether distributed inference network. Weights are layer-sharded and distributed across multiple edge nodes for parallel inference.
Deployment Architecture
This model runs on the Aether distributed inference runtime โ our custom engine that shards model layers across multiple nodes for parallel execution:
- Coordinator receives requests and manages token generation
- Layer nodes each hold a subset of model layers
- Hidden states flow between nodes via gRPC
- Zero cold start via warm pool scheduling
Deployed via Edgework.ai โ bringing fast, cheap, and private inference as close to the user as possible.
About
Published by AFFECTIVELY ยท Managed by @buley
We quantize and publish production-ready models for distributed edge inference via the Aether runtime. Every release is tested for correctness and stability before publication.
- All models ยท GitHub ยท Edgework.ai
Model tree for affectively-ai/vibevoice-1.5b-gguf
Base model
fixie-ai/ultravox-v0_5-llama-3_2-1b