Fireworks AI Inference vs Beam 1.0

Fireworks AI Inference

Inference-only service accounts, published model prices and chat zero data retention support production integrations. Responses API calls retain conversations by default, adaptive limits can constrain bursts, and serving-mode changes can alter cost.

Beam 1.0

The Reflection API is OpenAI-compatible, with an OpenAPI document, strict structured outputs and tool calls, and error codes that say when to retry, and the weights are Apache-2.0. It is a free public beta with unpublished daily limits and no per-token price, reasoning can't be turned off, and three API incidents were posted between 14 and 16 October 2026.

Fireworks AI Inference

1. Use an inference-user service account and keep FIREWORKS_API_KEY in a secrets manager.
2. Use https://api.fireworks.ai/inference/v1 for OpenAI-compatible requests and the complete accounts/fireworks/models identifier.
3. Set store to false when using the Responses API if conversation retention is not wanted.
4. Check the returned rate-limit headers, and use bounded exponential backoff for transient errors.
5. Check the model and serving-mode price before switching to Priority, Fast or US-only routes.

Beam 1.0

1. Send reasoning_effort low or medium for short tasks. The default is max, and none or minimal return 400 unsupported_value
2. Return every assistant message with its reasoning_content unchanged. If a turn comes back without it, start a new conversation, since later requests fail with missing_required_parameter
3. Don't rely on stop or seed. Both are accepted and ignored, so truncate output in your own code
4. Honour x-should-retry: false on a 429. It means a daily limit is spent and Retry-After counts to 00:00 UTC
5. Set max_completion_tokens yourself on long prompts. The default budget isn't reduced to fit the prompt and includes reasoning tokens