PhoneLLM Alpha 1
PhoneLLM Alpha 1 is Pipecat's open-weights text model for phone and voice agents: a full-parameter fine-tune of NVIDIA Nemotron 3 Nano 30B-A3B with 30B total and 3.5B active parameters, a 256K-token context, accurate multi-turn tool calling with thinking disabled, and BSD 2-Clause weights.
Model
PhoneLLM Alpha 1 is a full-parameter supervised fine-tune of NVIDIA's Nemotron 3 Nano 30B-A3B, trained by the Pipecat team at Daily with the NVIDIA NeMo framework. It keeps the base model's hybrid Mamba-Transformer mixture-of-experts architecture: 52 layers mixing Mamba-2, MoE and grouped-query attention blocks, 128 routed experts plus one shared expert with 6 active per token, 30B total parameters with 3.5B active, and a 262,144-token context. The fine-tune targets English-language phone agents that handle inbound customer-service calls and common outbound calling tasks, and is trained to call the right tools at the right time across long multi-turn conversations without thinking enabled, so the model answers without a reasoning delay; Pipecat recommends temperature 0 and thinking off, matching the training setup.
PhoneLLM Alpha 1 is released under the BSD 2-Clause license; as a derivative of Nemotron 3 Nano, redistribution must also carry the NVIDIA Nemotron Open Model License and attribution notices. Full details are in Pipecat's announcement and the model card.
Dedicated Endpoint
DocsA Dedicated Endpoint is your own deployment of PhoneLLM Alpha 1, on an inference stack that Modal tunes and autoscales. Bring fine-tuned weights if you have them. Compute is billed by the second, and only while it runs.
modal endpoint create --model pipecat-ai/phonellm-alpha-1