GPT-Live-1 API Pricing: $0.05/Minute Voice Model
GPT-Live-1 costs $0.05 per minute for full-duplex voice. See the separate backend bill, workload examples, and Realtime comparison.
By AI Pricing Guru Editorial Team
AI Pricing Guru articles are maintained by the editorial workflow behind the site: daily pricing snapshots, provider source checks, and review passes for model launches, subscription limits, and billing changes.
TL;DR
- GPT-Live-1 is available now as OpenAI's full-duplex voice layer: it can listen and speak simultaneously, handle interruptions, and delegate harder reasoning or actions to a backend agent.
- The live rate below is billed by actual session duration, per second; backend model and tool usage is an additional charge.
- OpenAI reports a 30-point Full Duplex Bench gain over GPT-Realtime-2.1, while Speak saw almost 80% fewer interruptions than its previous turn-based system.
- Do not swap the model string in an existing Realtime app: GPT-Live-1 uses a separate Live endpoint and a different architecture.
GPT-Live-1 versus current realtime voice pricing
| Model | Text in / cached / out | Audio in / cached / out | Image in / cached |
|---|---|---|---|
| GPT-Realtime-2.1 | $4.00 / $0.4 / $24.00 | $32.00 / $0.4 / $64.00 | $5.00 / $0.5 |
USD per 1M modality tokens. A Realtime session can accrue text, audio, and image charges together; this is not an all-in per-minute rate.
| Model | Audio / min | Audio / hour | Change |
|---|---|---|---|
| GPT-Live 1 | $0.05 | $3.00 | Baseline |
| Grok Voice Think Fast 1.0 | $0.05 | $3.00 | 0% higher |
| Grok Voice Think Fast 2.0 | $0.08 | $4.80 | 60% higher |
Minute-priced voice rows use the provider's published audio-minute rate. Additional text, tools, or telephony charges may apply.
Live values come from the canonical pricing API.
Cost comparison from today's pricing data
USD per 1M tokens. Input and output rates are charted separately.
Estimate the backend portion of a voice-agent workload
Assumes 75% input tokens and 25% output tokens using current per-million rates.
GPT-5.6 Luna
openai
$4.50
- Input share
- $1.50
- Output share
- $3.00
GPT-6 Astra
openai
$200.00
- Input share
- $75.00
- Output share
- $125.00
Backend model rates billed in addition to GPT-Live-1
| Model | Provider | Input / 1M | Cached / 1M | Output / 1M |
|---|---|---|---|---|
| GPT-5.6 Luna | openai | $0.2 | $0.02 | $1.20 |
| GPT-6 Astra | openai | $10.00 | $1.00 | $50.00 |
Built from pricing.json at publish time.
OpenAI launched GPT-Live-1 in the API on September 10, 2026, bringing the full-duplex voice system behind ChatGPT Voice to developers. It listens and speaks at the same time, handles interruptions inside one audio model, and can delegate deeper reasoning or actions to a separate backend agent.
The pricing change is structural. GPT-Live-1 charges for the front-end voice session by elapsed time, while the chosen backend model and tools create a second bill. The live tables above pull both layers from our maintained dataset instead of freezing rates in this article.
What changed with GPT-Live-1
GPT-Live-1 replaces the familiar speech-to-text → language model → text-to-speech chain with a voice layer that reasons over incoming and outgoing audio together. OpenAI says this reduces brittle handoffs and lets the conversation continue while a backend model works.
The model accepts audio and text and returns audio and text. It natively supplies ASR transcripts and response text, supports keyword biasing and function calling, and can still expose explicit turn boundaries. It does not accept images.
The API release also adds telephony support and 12 listed preset voices spanning accents, dialects, and languages. Custom voice access requires a sales eligibility process.
GPT-Live-1 pricing impact
The voice layer’s current price appears in the first live table. OpenAI bills session duration per second rather than rounding each session to a full minute. Continuous use therefore scales directly with connected time, but that is only the front-end cost.
Backend Responses calls use the selected model’s normal token rate, and tools are charged under their usual rules. A routine reservation flow can delegate to GPT-5.6 Luna; a difficult support case can escalate to GPT-6 Astra. The second table and calculator show those maintained backend rates.
Telephony, storage, observability, human escalation, taxes, and enterprise commitments can add costs OpenAI’s model table does not include. Budget per resolved call, not per connected minute alone. Compare the wider catalog on our OpenAI pricing page and model backend traffic with the token calculator.
| Front-end voice usage | GPT-Live-1 session cost | Excludes |
|---|---|---|
| 10 minutes | $0.50 | Backend model, tools, phone carrier |
| 100 minutes | $5.00 | Backend model, tools, phone carrier |
| 1,000 minutes | $50.00 | Backend model, tools, phone carrier |
| 10,000 minutes | $500.00 | Backend model, tools, phone carrier |
A 95-second session costs about $0.0792 for GPT-Live-1 itself because OpenAI bills actual duration per second. The clean budget is voice-session time plus backend tokens, tools, telephony, infrastructure, and human escalation.
GPT-Live-1 versus GPT-Realtime-2.1
| Decision | GPT-Live-1 | GPT-Realtime-2.1 |
|---|---|---|
| Voice behavior | Full-duplex: listens and speaks simultaneously | Realtime speech-to-speech with turn handling |
| API route | v1/live/sessions | v1/realtime |
| Billing shape | Connected voice time; backend model and tools separate | Text, audio, and image tokens inside the session |
| Backend reasoning | Delegates to an OpenAI or third-party agent | Reasoning and tools run through the Realtime model |
| Image input | Not supported | Supported |
OpenAI reports a 30-percentage-point improvement on Full Duplex Bench over GPT-Realtime-2.1. With GPT-6 Astra at medium reasoning, it also reports GPT-Live-1 ranking first on Tau3 end-to-end voice-agent tasks. These are provider-run evaluations; they do not prove the same lift on a buyer’s accents, noise, telephony stack, tools, or policies.
Speak reported almost 80% fewer interruptions than its previous turn-based system. Another early customer said a cascaded build shrank by 80% and 23,000 lines. Treat both as customer evidence, not universal savings guarantees.
Who benefits—and who should wait
Phone support, reservations, healthcare intake, language learning, commerce, and accessibility products benefit when interruption handling and conversational rhythm materially affect completion. Teams with a strong backend agent can also change reasoning depth without replacing the voice experience.
Wait if the product mainly needs transcription, one-way narration, image-aware voice, or deterministic batch work. A split pipeline may be cheaper and easier to audit. Compare xAI voice pricing and our earlier OpenAI Realtime launch analysis before choosing an architecture.
What developers should do now
- Build against the Live endpoint; do not treat this as a Realtime model-string migration.
- Measure interruption success, first-response latency, background-noise failures, tool completion, escalation rate, and cost per resolved call.
- Route routine backend work to a lower-cost model and escalate only the cases that need frontier reasoning.
- Cap session duration and end abandoned or silent calls promptly.
- Test real accents, languages, phone codecs, pauses, cross-talk, and noisy environments before increasing traffic.
For a separate premium voice baseline, benchmark ElevenLabs on the same resolved-call rubric.
Affiliate disclosure: AI Pricing Guru may earn a commission from the sponsored ElevenLabs link at no extra cost to you. It does not affect this analysis.
Labs coverage
GPT-Live-1 is not eligible for the current AI Pricing Guru Labs leaderboard. It has no Chat Completions or Responses inference route, and a text-only proxy would miss full-duplex audio, interruptions, voice quality, telephony latency and backend delegation.
A valid test needs fixed audio prompts, phone codecs, controlled noise, interruptions and pauses, identical backend models and tools, end-to-end latency, task success, and a complete voice-plus-backend cost ledger. We recorded that requirement in Labs coverage notes.
Bottom line
GPT-Live-1 is a new voice architecture, not merely a Realtime refresh. Its strongest proposition is simpler full-duplex interaction with backend model choice; its main budgeting risk is treating the visible session rate as the entire agent cost.
Start with a bounded call flow, keep the backend route explicit, and promote it only when fewer interruptions and better task completion reduce total cost per accepted outcome. The maintained OpenAI API pricing guide covers the rest of the model stack.
Sources: OpenAI’s official GPT-Live-1 launch, model documentation, API pricing, and Live API guide. Facts and prices verified September 10, 2026.