LLM
Fireworks AI logo

Fireworks AI LLM inference for Bolna AI voice agents

Fireworks AI serves open models to a Bolna voice agent on serverless per-token access or on-demand GPU deployments, connected as an OpenAI-compatible custom LLM.

llmfireworksopen-modelsserverlesscustom-llm
At a glance

How Fireworks AI fits in the stack

Best for

Reasoning, policy handling, tool use, and response generation.

Use this layer when

You want to tune quality, cost, latency, or function-calling behavior.

Connects to

Transcribed caller input upstream and voice or actions downstream.

Voice Stack

The LLM is the reasoning layer

The LLM is the reasoning layer

This provider decides how the agent interprets intent, selects next actions, calls tools, and formulates responses. It is the decision engine inside the voice stack.

TelephonyPhone Network
→
STTListener
→
LLMReasoning
→
TTSVoice
→
ToolsActions

Last updated

What is Fireworks AI used for in a Bolna voice agent?

Fireworks AI serves open models to a Bolna voice agent through an OpenAI-compatible API, either on shared serverless capacity paid per token or on dedicated on-demand GPUs. Start on serverless to try a model quickly, then move to an on-demand deployment for no rate limits or a model that isn't on serverless. The one Fireworks-specific detail is the model ID, which is a full resource path.

How do I set up Fireworks AI with Bolna?

  1. In the Fireworks dashboard, open API keys and click Create API key.
  2. Find a chat model in the Fireworks model library and copy its full ID, such as accounts/fireworks/models/llama-v3p1-8b-instruct. Versions use p for the decimal point, so Llama 3.1 is llama-v3p1.
  3. In Bolna, go to Settings → Integrations → LLM → Custom LLM → Add model, or choose + Add custom LLM in an agent's LLM Provider dropdown. Select Fireworks AI.
  4. Enter the full model ID, set Endpoint URL to https://api.fireworks.ai/inference/v1, paste your key and set Family to llama, for example.
  5. Choose custom on the agent's Intelligence tab, pick the model and save.

The Fireworks AI setup guide in the Bolna docs shows how to create an on-demand deployment with firectl.

What is the difference between Fireworks serverless and on-demand in Bolna?

ServerlessOn-demand deployment
CapacityShared, per-tokenDedicated GPUs for one model
Rate limitsYesNone
How you create itNothing to createfirectl create deployment
Model name in Bolnaaccounts/fireworks/models/<model>accounts/fireworks/models/<model>#accounts/<account-id>/deployments/<deployment-id>
Endpoint URLhttps://api.fireworks.ai/inference/v1Same

An on-demand deployment created with --min-replica-count 0 can scale to zero, and the next call waits for a GPU to start. Use --min-replica-count 1 for live voice traffic.

What can you build with Fireworks AI and Bolna?

Quick model trials. Try several open models on serverless with no deployment, then keep the one that sounds best on calls. Together AI is another serverless catalog to compare.

Campaigns that outgrow serverless. When a batch starts hitting rate limits, move the agent to an on-demand deployment, which has none.

Agents on models not offered on serverless. On-demand deployments give a wider choice of models. For your own fine-tuned weights, also see Baseten.

Open-model agents with their own billing. Tokens are billed by Fireworks, not Bolna. The custom LLM page covers how custom models work.

FAQ

Fireworks AI on Bolna: frequently asked questions

Yes. Add it as a custom LLM with the Fireworks AI preset, the endpoint https://api.fireworks.ai/inference/v1, your Fireworks key and the full model ID.

You probably entered a short name such as llama-v3p1-8b-instruct. Fireworks needs the full path, for example accounts/fireworks/models/llama-v3p1-8b-instruct.

Register the model ID followed by # and the deployment name, for example accounts/fireworks/models/gpt-oss-120b#accounts/<account-id>/deployments/<deployment-id>, with the same endpoint and key.

Serverless has rate limits. Move the agent to an on-demand deployment, which has none, and keep at least one replica running for live calls.

Browse this layer

Keep exploring the voice stack

Browse

Large Language Models

The LLM is the brain of your voice agent. It understands what callers say and decides how to respond. Bolna lets you switch between models like GPT-5.4 mini, Claude and DeepSeek by changing the provider and model in your agent LLM settings, so you can tune for speed, cost or reasoning depth.

Browse

Telephony

Telephony providers connect your voice agents to the phone network so they can make and receive real calls. Bolna supports managed integrations with major carriers as well as bring-your-own-carrier via SIP trunking, giving you full control over call routing, number provisioning, and cost.

Browse

Speech-to-Text

Speech-to-text converts what callers say into text that your LLM can process. Transcription accuracy and latency directly affect how natural a conversation feels. Bolna supports streaming STT providers optimized for telephony audio, including specialized models for Indian languages.

Browse

Text-to-Speech

Text-to-speech turns your agent responses into spoken audio. Voice quality shapes how callers perceive your brand. Flat, robotic speech kills trust while natural, expressive voices build it. Bolna integrates with the fastest TTS providers so responses sound human and arrive without awkward pauses.

Browse

Tools & Workflows

Tools let your voice agents take action during a call, not just talk. Book a calendar slot, look up an order through your own API, push a lead into your CRM, or trigger a multi-step automation in Zapier. These integrations turn voice agents from answering machines into workflow engines.

See where Fireworks AI fits in your production workflow

Use the demo to walk through provider selection, stack tradeoffs, and the exact workflow you want Bolna to automate.