Affordable hosted inference for Llama, Mixtral, and more — the cost-efficient conversation engine for high-volume Fluents deployments.
Run Open-Weight LLMs via Deep Infra in Your Fluents Stack
Deep Infra hosts leading open-weight LLMs — Llama, Mixtral, Qwen, Mistral — at some of the most competitive inference pricing available. For Fluents deployments where the economics of cost-per-call matter and open-source model quality is sufficient for the use case, Deep Infra is a practical path to scale.
Like all conversation engine alternatives in Fluents, switching to Deep Infra affects only the LLM reasoning layer — Deepgram handles transcription and ElevenLabs handles voice synthesis unchanged.
Lowest-cost inference for open-weight models like Llama and Mixtral — reducing cost-per-call for high-volume Fluents operations
Wide model selection: access the latest Llama, Mixtral, Qwen, and Mistral releases as soon as they're available
Simple API access — no GPU infrastructure to manage, no capacity planning, no uptime concerns
The Cost Lever in Voice AI
For a Fluents deployment making millions of calls per year, the conversation engine cost is a meaningful operating expense. The difference between frontier model pricing and Deep Infra's open-weight inference pricing can be 10-20x per token. For structured, repeatable workflows — appointment reminders, renewal outreach, intake qualification — where the task doesn't require frontier model reasoning, that cost difference compounds dramatically at scale.
Insurance: Renewal Campaigns at Low Cost Per Call
An insurance carrier running 500,000 annual renewal reminder calls doesn't need GPT-4 to confirm a policyholder's renewal date and ask if they have questions. Llama 3.1 70B via Deep Infra handles this reliably — at a fraction of frontier model costs. The savings fund the calls that actually need human or high-capability AI follow-up.
Healthcare: Appointment Reminders at Scale
A healthcare network running daily appointment reminders across multiple clinics handles millions of patient calls per year. Using Deep Infra's affordable inference for these structured, low-complexity calls reduces the AI cost per reminder to near-negligible levels — making the economics of AI calling at full network scale work.