Fireworks AI vs Replicate

A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.

	Fireworks AI Fine-tuning	Replicate Fine-tuning
Tagline	Production inference and fine-tuning platform for open-source LLMs, tuned for speed and enterprise economics.	One-API platform for running and fine-tuning open-source models.
Category	Fine-tuning	Fine-tuning
Pricing	Freemium· Free signup credits; pay-per-token from ~$0.14/M in; enterprise reserved capacity on request	Paid· Pay-per-second of GPU time
Model	Multi-model (DeepSeek, Qwen, GLM, Kimi, Gemma, Minimax, others)	Thousands of community + first-party models
Editorial score	—	8.5 / 10
Use cases	llm-fine-tuningserverless-inferencemulti-lora-servingcode-assistantsagentic-systems	model hostingfine-tuningAPI access
Pros	OpenAI- and Anthropic-compatible APIs against open-weight models Strong fine-tuning + multi-LoRA hosting on a shared base Serverless, on-demand, and reserved-capacity tiers cover most load shapes Used in production by Cursor, Sourcegraph, Vercel, Notion	One API, thousands of models Easy fine-tuning of Llama, SD, Flux Strong community Predictable per-second pricing
Cons	Platform itself is proprietary despite hosting open models Per-token pricing can beat DIY GPUs at low volume but not at very high steady load Model catalog churns fast; today's best price/perf may not be tomorrow's	Per-second pricing can surprise Hosted models vary in quality
Website	fireworks.ai	replicate.com

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