FireOptimizer
FireOptimizer optimizes model inference and supports fine-tuning with users' data.
Find alternatives to FireOptimizer
What it does
- Model inference
- Model training
Features 4
- 3D OptimizerTailors inference to a workload's speed, quality and cost by tuning serving configurations from over 100,000 options.
- Reinforcement learningImproves model quality from feedback by defining success criteria, without complex pipelines.
- Supervised fine tuningFine-tunes models on the customer's own data with an optimized training stack.
- Multi-LoRADeploys hundreds of fine-tuned models without added infrastructure or cost.
Sources
- Pricing
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"Supervised and preference fine tuning is priced per 1M training tokens."
- Description
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Official documentation · 15 Oct 2026
"optimizing for speed, quality, and cost"
- What it does
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Official documentation · 15 Oct 2026
"Fine tune with your own data"
- Sold within
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Official documentation · 15 Oct 2026
"With FireOptimizer, our proprietary optimization layer"
- Name
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Official documentation · 15 Oct 2026
"FireOptimizer tailors inference to your exact needs"
- URL
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Official documentation · 15 Oct 2026
"FireOptimizer tailors inference to your exact needs"
- Deployment
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Official documentation · 15 Oct 2026
"Fireworks Virtual Cloud gives you instant access"
Also from Fireworks AI
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Fireworks AI Model API
Hosted API for serving and fine-tuning open-weight models, billed per token.
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Fireworks Nexus Model API
Routing layer for coding harnesses such as Claude Code, Codex and OpenCode that scores each request and sends it to an open model or your closed provider to cut cost.
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Fireworks Inference API service
Serving for frontier open models and for a customer's own post-trained versions of them, on an inference engine tuned at each layer.
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Fireworks Training API service
Training and retraining of custom models on Fireworks, offered across several training surfaces and served on the same platform.
-
Fireworks Speech Recognition API service
Real-time and batch speech-to-text on Fireworks, aimed at voice workflows that need low-latency transcription at scale.
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