Tool profile
Inference platform for serving open models with fast APIs, fine tuning, and production ready tooling.
Model inference
Fireworks AI is model infrastructure for teams that want inference, deployment, and fine-tuning options without buying a packaged end-user AI product. It is aimed at builders working directly at the serving layer, where token pricing, model choice, GPU deployment, and performance characteristics matter more than collaboration UX.
That makes it a model-platform decision rather than a workflow-software decision. Teams usually evaluate Fireworks when they care about inference economics and deployment flexibility across open models.
Quick fit
Editorial take
Fireworks AI should be judged like model infrastructure. The core decision is whether the team needs serving flexibility and better price-performance control, because that matters much more here than any generic AI-product polish.
What it does well
Primary use cases
Fit notes
Compare with
Pressure-test this pick against nearby alternatives.
Agenta
Free planLLMOps
Open-source LLMOps platform for prompt management, evaluation, observability, and collaborative AI application development with a clear hosted pricing ladder.
Choose Agenta when the team wants collaborative prompt management, evals, and observability in one hosted workflow.
Pricing snapshot
Fireworks AI uses pay-as-you-go pricing for non-enterprise usage and gives new users free credits. Charges depend on the service, including per-token serverless inference, per-GPU-time deployments, and per-token fine-tuning data. As one current official example, GPT OSS 120B is listed around $0.15 input, $0.07 cached input, and $0.60 output per 1M tokens.
AgentOps
Free planAgent observability
Observability for AI agents with tracing, debugging, session visibility, and production monitoring.
Closer to agent observability than to model hosting or prompt tooling
