Pipecat vs LiveKit Agents: which voice framework fits?

Pick Pipecat if you want to choose the transport yourself, such as Daily, plain WebSockets, a Twilio media stream or even a LiveKit room, and you like building a bot as an explicit pipeline of processors. Pick LiveKit Agents if you are already on LiveKit or want the media server, job dispatch, telephony and agent framework from one vendor, or if you need Node.js. Both are open source and both are Python-first. Sources checked 2026-11-03.

Quick comparison

The column order follows the query wording, not a ranking.

How they differ

Pipeline or room participant

Pipecat's README describes it as an open-source Python framework where each pipeline is an agent, built from modular components and composed with handoff, parallel fan-out or sidecar workers over a shared bus. The transport is one processor among others, which is why the same bot can run over Daily, WebSockets or a phone stream.

LiveKit Agents starts from the room. The README defines an Agent (instructions and tools), an AgentSession that manages the conversation, an entrypoint per session and an AgentServer that schedules jobs and launches agents. The agent is a server-side participant in a LiveKit room, and clients use LiveKit's WebRTC SDKs.

Turn-taking

This is where voice bots feel good or bad. LiveKit's README lists semantic turn detection with "a transformer model to detect when a user is done with their turn." Pipecat ships smart turn as the default stop strategy and, in 1.15.0, added ClassifierUserTurnStrategies and UserTurnStrategiesParams, which decide whether several strategies must all agree. That release also changed the default to all-must-agree, so read the Pipecat 1.15.0 notes before upgrading.

Telephony

Pipecat connects to phone providers through serializers for their media streams: Twilio, Telnyx, Plivo, Exotel, Genesys and Vonage. LiveKit Agents uses LiveKit's own SIP telephony stack for inbound and outbound calls, and its examples include an outbound caller. If your numbers already live at Twilio and you do not want a media server, Pipecat is the shorter path. If you want SIP trunks into the same rooms as your web users, LiveKit fits.

Providers and models

Both have long provider lists. Pipecat's README groups them into STT, LLM, TTS, speech-to-speech, video avatars (HeyGen, Tavus, Simli), memory (mem0), vision and audio processing, with 96 optional extras on PyPI. LiveKit Agents installs plugins as extras too (81 on PyPI), such as livekit-agents[openai,deepgram,cartesia]. It also offers LiveKit Inference, one API for hosted models through LiveKit Cloud. The README example uses it for Deepgram STT, a Gemma LLM and Cartesia TTS.

Testing and tooling

LiveKit Agents includes a test framework: AgentSession.run() in pytest, then result.expect assertions on function calls and messages, with .judge(llm, intent=...) for fuzzy checks. Pipecat has pipecat eval scenarios, which 1.15.0 extended with text_matches regex checks. It also has the Whisker debugger, the Tail terminal dashboard and pipecat init scaffolding. Both projects publish skills for AI coding assistants: Pipecat Skills for Claude Code, and the LiveKit Agent Skill plus a LiveKit Docs MCP server.

Which one to choose

• Already on Daily, or you want plain WebSockets or a Twilio stream without a media server: Pipecat.
• Already on LiveKit, or you want web, mobile and SIP callers in the same rooms: LiveKit Agents.
• A Node.js or TypeScript backend: LiveKit Agents, through AgentsJS.
• Structured, scripted conversations such as intake forms: Pipecat, with Pipecat Flows built in. LiveKit handles this with agent handoffs.
• Behaviour tests in CI: LiveKit's pytest helpers are the more complete built-in option today.
• Expressive TTS (laughs, pauses, delivery tags): Pipecat 1.15.0 added this as an alpha feature. Expect API changes.

How we compared

We read both READMEs, the PyPI metadata for pipecat-ai 1.15.0 and livekit-agents 1.8.10, the Pipecat 1.15.0 and LiveKit Agents 1.8.10 release notes, and the npm entry for @livekit/agents, and we pulled repository metadata from the GitHub API. All were checked on 2026-11-03. We did not install, run or benchmark either framework, so there are no latency figures here.

Limitations

No latency or cost benchmarks: real-world response time depends mostly on your STT, LLM and TTS providers and on network placement. Pipecat Cloud, LiveKit Cloud and LiveKit Inference pricing is not in the sources. Star counts change daily.

Related: the Pipecat 1.15.0 launch, LiveKit Agents 1.8.10, best free AI voice models and Moss TTS vs Kokoro. Browse the Pipecat and LiveKit Agents hubs and the voice agents category.