LiveKit pricing

About

LiveKit is the open-source, end-to-end WebRTC stack that has become the default real-time transport layer for voice and video AI. Launched in July 2021 as a free, Apache-2.0 server you can self-host, it grew into a three-part product: the open-source media server, LiveKit Cloud (the managed, globally-distributed network), and the Agents framework for building voice/video AI agents. LiveKit provides the real-time transport behind OpenAI’s ChatGPT voice mode, and the Agents framework — modeled on that work — is downloaded more than a million times a month. Other customers include xAI, Salesforce (Agentforce), Tesla, and even 911 emergency services; the network handles billions of calls a year.

The company raised a $45M Series B at a $345M valuation in April 2025 (led by Altimeter), then a $100M Series C at a $1B valuation in January 2026 (led by Index Ventures, with Salesforce Ventures, Hanabi, Altimeter and Redpoint). At its Series B it reported 500+ paying customers and 100,000+ developers.

For the most current information, visit LiveKit.

Pricing summary : How LiveKit’s pricing model works

LiveKit has two pricing paths. The open-source server is free to self-host under Apache 2.0 — no LiveKit fees, you pay only for your own infrastructure. LiveKit Cloud is the managed alternative with four tiers: Build (free), Ship ($50/mo), Scale ($500/mo), and Enterprise (custom).

Cloud is multi-dimension metered. Each tier bundles monthly allotments of several units, then charges usage-based overage above them:

• Agent-session minutes — time an AI agent runs on Cloud. Build includes 1,000, Ship 5,000, Scale 50,000; overage is $0.01/min.
• WebRTC media minutes — end-user connection time to the realtime network. Build 5,000, Ship 150,000, Scale 1.5M; overage is $0.0005/min (Ship) / $0.0004/min (Scale).
• Inference credits — for LiveKit Inference (LLM/STT/TTS via one API key). Build includes $2.50, Ship $5, Scale $50 (Scale gets discounted model rates).
• Telephony — 1 free US number, then $1/number and $0.01/inbound min; toll-free and SIP metered separately.
• Data transfer — 50 GB / 250 GB / 3 TB included, then $0.12/GB (Ship) / $0.10/GB (Scale).

What makes this different: LiveKit prices the AI-agent workload, not just raw video conferencing. The headline meter — agent-session minutes at a flat $0.01/min — is independent of which LLM/STT/TTS models you call (those bill separately through inference credits or your own keys). A built-in calculator estimates blended per-minute agent cost (e.g. ~$0.0735/min for a GPT-5.3 + Deepgram Nova-3 + Cartesia Sonic 3 stack), so buyers can model a voice agent end-to-end before committing.

Pricing by product

Sales motions across products: self-serve PLG for Build/Ship/Scale (instant signup, no card on Build), open-source self-host, and sales-led for Enterprise (volume + inference discounts, on-prem/private deployment).

Hidden costs : What LiveKit users actually pay

The flat $50/$500 is only the floor. A production voice-AI app stacks five separate meters: agent-session minutes, WebRTC media minutes, inference credits (or your own model bills), telephony, and data transfer. The single biggest line is usually inference — the LLM/STT/TTS model minutes that the LiveKit calculator surfaces — which can dwarf the $0.01/min agent-session fee. For example, the calculator’s sample voice stack (GPT-5.3 Chat + Deepgram Nova-3 + Cartesia Sonic 3 + observability) lands at ~$0.0735/min all-in, of which the LiveKit agent-session + observability portion is only $0.02/min.

Other things to budget for: HIPAA, RBAC, region pinning and metrics-export APIs are gated to Scale ($500) and above; cold-start prevention (always-on agents), custom voices and inference discounts also start at Ship/Scale; and toll-free numbers ($2/number, $0.02/inbound min) and third-party SIP minutes bill on top.

Want to estimate your own LiveKit bill? Use the LiveKit pricing calculator to model your costs based on usage patterns.

Pricing evolution : LiveKit pricing history and changes

Cadence

Tracked range: 2021–present. The open-source launch and the ChatGPT-voice-mode milestone are documented; the modern Build/Ship/Scale structure and per-unit rates are from a live 2026-06-09 capture of livekit.io/pricing.

Notable changes

• 2021-07 — Launches as a free, open-source, end-to-end WebRTC stack (Apache 2.0). Self-hosting carries no LiveKit fees.
• 2023-09 — LiveKit powers OpenAI’s ChatGPT voice mode and releases the open-source Agents framework; LiveKit Cloud (Build/Ship/Scale) matures, metered on participant/connection minutes and bandwidth.
• 2025-04 — $45M Series B at $345M. Cloud repositions around voice/video AI agents, making agent-session minutes and inference credits the primary metered units.
• 2026-01 — $100M Series C at a $1B valuation (Index Ventures).
• 2026-06 — Current structure: Build (free), Ship $50, Scale $500, Enterprise. Five metered dimensions with per-unit overage; LiveKit Inference exposes LLM/STT/TTS model minutes through one API key.

What’s unique : LiveKit’s distinctive pricing mechanics

1. Agent-session minutes as the headline meter. Rather than billing on raw video minutes or seats, LiveKit prices the agent runtime at a flat $0.01/min — decoupled from which models you run. It’s a value metric that maps directly to “how long my voice agent was live,” which is intuitive for AI builders.

2. Genuinely free via open source. The full WebRTC server is Apache 2.0 and self-hostable with no LiveKit fees. Cloud sells the managed global network, agent deployment/observability, and inference convenience — not the core capability — which caps pricing power but maximizes adoption.

3. Model-cost passthrough with optional discounts. LiveKit Inference lets you call LLM/STT/TTS models through one key, billed via credits; Scale and Enterprise get discounted model rates. You can also bring your own provider keys. This turns model spend into a metered, optionally-marked-up dimension layered on the subscription.

Strengths & weaknesses

Billing UX : LiveKit billing controls and transparency

• Billing controls — Self-serve signup with no credit card on Build; self-serve upgrade to Ship/Scale. Concurrency limits (concurrent agent sessions, connections, inference concurrency) are tier-capped, with higher Scale ceilings requestable via the dashboard.
• Usage visibility — Strong forward visibility: the pricing page ships an interactive per-minute cost calculator that breaks out agent-session, telephony, WebRTC, LLM, STT, TTS and observability rates by model and plan, plus session metrics/analytics and (Scale+) metrics-export APIs in-product.
• Payment options — Card-based self-serve for Build/Ship/Scale; Enterprise is invoiced under custom terms with volume (including inference) discounts, SSO, SLA and on-prem/private-deployment options.

Strategic wins : Why LiveKit’s pricing decisions worked

1. Open source as the top-of-funnel

Launching a free Apache-2.0 WebRTC stack made LiveKit the default real-time layer for an entire generation of voice/video apps — including OpenAI’s ChatGPT voice mode. The free self-host path removes adoption friction; Cloud monetizes the teams that don’t want to operate a global media network. See how AI companies structure pricing.

2. Repricing around the agent, not the call

By moving the headline meter to agent-session minutes, LiveKit aligned its pricing with the unit AI builders actually reason about, riding the voice-AI wave from a $345M (April 2025) to a $1B (January 2026) valuation. Related: outcome-based pricing trends.

3. Inference as a layered, discountable meter

Folding LLM/STT/TTS access into metered inference credits (with Scale/Enterprise discounts) lets LiveKit capture model spend as an expansion lever without forcing a single model choice. See choosing the right usage metric.

Areas to improve : Gaps in LiveKit’s pricing approach

1. Too many meters to forecast confidently

Five simultaneous metered dimensions (agent minutes, WebRTC minutes, inference, telephony, bandwidth) make it genuinely hard to predict a monthly bill without running the calculator for each scenario. A blended “all-in per-minute” headline would reduce planning friction. See bill shock and cost unpredictability.

2. Compliance gated high

HIPAA, RBAC, region pinning and metrics-export APIs only appear at the $500 Scale tier, which can push regulated startups straight to a steep step-up well before their volume justifies it.

3. Model-cost dependence

Because inference is usually the dominant line and rides third-party model pricing, LiveKit’s effective cost-to-serve for a customer can swing with provider price changes — a transparency and predictability gap LiveKit only partly controls.

Key takeaways

1. Open source built the funnel. A free Apache-2.0 WebRTC stack made LiveKit the default real-time layer for voice AI — including ChatGPT voice mode — before Cloud monetized the managed network.
2. Price the agent, not the call. Switching the headline meter to agent-session minutes ($0.01/min) aligned pricing with the AI-builder’s mental model and tracked a 3x valuation jump in nine months.
3. A flat floor plus many meters trades simplicity for fairness. Build/Ship/Scale anchor the bill, but five overage dimensions make forecasting hard.
4. Inference is the real cost driver. The $0.01/min agent fee is small next to blended model minutes (~$0.04–$0.07/min) — buyers should budget for inference first.
5. Self-host stays the escape valve. Because the core server is free under Apache 2.0, Cloud has to win on convenience and scale, not lock-in.

UBP implications

1. Choose a value metric your buyer already counts. “Agent-session minutes” maps cleanly to how voice-AI teams think about runtime — a more intuitive meter than raw video minutes or seats.
2. Layer model/inference cost as a separate, optionally-marked-up meter. Passing through (and discounting at scale) third-party model spend lets a platform expand revenue without dictating a model choice.
3. Open core changes pricing power. When the engine is free to self-host, the paid tiers must sell the managed network, observability, and compliance — not the capability. See usage-based pricing strategy.

Sources

• LiveKit pricing page (live capture, accessed 2026-06-09)
• LiveKit GitHub (open-source WebRTC server, Apache 2.0) (accessed 2026-06-09)
• LiveKit Series C: towards the voice-driven era of computing (accessed 2026-06-09)
• TechCrunch — Voice AI engine and OpenAI partner LiveKit hits $1B valuation (accessed 2026-06-09)
• FinSMEs — LiveKit Raises $45M Series B at $345M valuation (accessed 2026-06-09)
• LiveKit documentation — quotas and limits (accessed 2026-06-09)

Bottom line

LiveKit is the open-source (Apache 2.0) WebRTC stack that became the default real-time layer for voice and video AI — it powers OpenAI’s ChatGPT voice mode and its Agents framework is downloaded over a million times a month. The server is free to self-host; LiveKit Cloud is a hybrid — free Build, $50 Ship, $500 Scale and custom Enterprise — metered across agent-session minutes ($0.01/min), WebRTC media minutes ($0.0004–$0.0005/min), inference credits, telephony and data transfer. After a $45M Series B at $345M (April 2025), LiveKit raised a $100M Series C at a $1B valuation in January 2026. Browse the pricing blueprint for more fully-researched company profiles.

Want to compare LiveKit against other voice and real-time AI companies? Browse the pricing blueprint.

Pricing timeline : Major events on a vertical axis

Each milestone below corresponds to a public pricing change, product launch, or material adjustment. Major events use a filled marker; minor adjustments use a faded one.

Build free / Ship $50 / Scale $500 + multi-dimension metering

Jun 2026

Current structure: Build (free), Ship $50/mo, Scale $500/mo, Enterprise custom. Each bundles agent-session minutes, WebRTC media minutes, inference credits, telephony minutes and data transfer, then usage-based overage (agent sessions $0.01/min; WebRTC $0.0004–$0.0005/min; transfer $0.10–$0.12/GB).

Series B + voice-AI agent repositioning

Apr 2025

Raised $45M Series B at a $345M valuation (Altimeter). Cloud repositions around voice/video AI agents, foregrounding agent-session minutes and inference credits as primary metered units.

LiveKit Cloud + ChatGPT voice mode

Sep 2023

LiveKit Cloud (managed) matures with Build/Ship/Scale tiers metered on participant/connection minutes and bandwidth. LiveKit powers OpenAI's ChatGPT voice mode and releases the open-source Agents framework.

Open-source WebRTC stack launches

Jul 2021

LiveKit launches as a free, open-source, end-to-end WebRTC stack (Apache 2.0) for real-time audio/video — self-hostable with no LiveKit fees.