By Sagar Shankaran, Founder of CallSphere
ElevenAgents charges per minute. OpenAI charges per token. The real cost compare flips depending on prompt size and call length. Here is the math on identical 5-minute calls.
Key takeaways
ElevenAgents charges per minute. OpenAI charges per token. The real cost compare flips depending on prompt size and call length. Here is the math on identical 5-minute calls.
flowchart TD
Client[Client] --> Edge[Cloudflare Worker]
Edge -->|WS upgrade| DO[Durable Object]
DO --> AI[(OpenAI Realtime WS)]
AI --> DO
DO --> Client
DO -.hibernation.-> Storage[(Persisted state)]ElevenLabs and OpenAI made different choices on how to bill voice agents, and that leads to surprising winners depending on your call profile. ElevenAgents charges by the minute (a flat per-minute fee that includes TTS + STT + LLM hops in some tiers), while OpenAI's gpt-realtime charges per audio token with separate text token meters and a generous prompt-cache rate.
If you are choosing a stack in 2026, you cannot just compare headline numbers. You have to model your actual prompt sizes, tool-call density, and average call length.
LLM cost is bundled in these tiers when you use ElevenLabs' included models. Bring-your-own-LLM adds the underlying API cost.
Profile A — 5-minute SMB booking call, 8k system prompt, 60/40 talk split:
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Profile B — 12-minute healthcare intake, 22k system prompt, 50/50 talk, 18 tool calls:
Profile C — 2-minute outbound qualification, 4k prompt, 70/30 (agent talks more):
Profile D — 30-minute support escalation, 12k prompt, 50/50 talk:
The pattern: flat per-minute pricing wins on short, predictable calls without big prompts. OpenAI wins on long calls, big prompts, and anywhere you can engineer a high cache hit rate.
We run both providers on the production cluster — that is not a hedge, it is a deliberate match-to-workload strategy. The Sales product uses ElevenLabs' Sarah voice for outbound, where the per-minute predictability matters for our affiliates' margin math (see the affiliate program). The Healthcare Voice Agent uses OpenAI Realtime PCM16 24kHz because our 22k-token clinical prompt loves the cache-rate curve.
Across 6 verticals — 37 agents, 90+ tools, 115+ DB tables, HIPAA + SOC 2 aligned — we route calls to the cheaper provider per session based on three knobs: expected call length, prompt size, and brand-voice requirement. The router lives in a 90-line policy file that gets re-evaluated every Monday.
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CallSphere ships complete AI voice agents per industry — 14 tools for healthcare, 10 agents for real estate, 4 specialists for salons. See how it actually handles a call before you book a demo.
A real measurement: in March we shifted Salon GlamBook (4 agents, GB-### refs) from OpenAI Realtime to ElevenAgents Turbo because the 3-minute booking call profile favored the flat $0.10/min. Net cost dropped 24%, latency dropped 80ms, customer NPS unchanged.
If you want to feel the difference, the demo cards on our site let you A/B both vendors live, and the ROI calculator lets you plug in your own profile.
Is ElevenAgents always more expensive than OpenAI Realtime? No. On short calls (under 3 minutes) with small prompts, the flat per-minute Turbo rate ($0.10/min) often beats OpenAI's effective rate even with caching.
Can I bring my own LLM to ElevenAgents to save money? Yes — ElevenAgents supports BYO-LLM and you pay the per-minute platform fee plus your LLM bill separately.
Which has better voice quality? ElevenLabs v3 wins on emotional range and brand voices; OpenAI's gpt-realtime is closer than ever and natively faster on barge-in.
Do both support tool calls? Yes, both support function calling natively. ElevenLabs added MCP-native tool support in March 2026.
What about latency? ElevenLabs Turbo lands ~400ms voice-to-voice. OpenAI Realtime lands ~430ms after the May 2026 rearchitecture.
Written by
Sagar Shankaran· Founder, CallSphere
Sagar Shankaran is the founder of CallSphere, where he builds production AI voice and chat agents deployed across healthcare, hospitality, real estate, and home services. He writes about agentic AI, LLM engineering, and shipping voice agents that handle real calls in production.
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