Quick answer
Replicate is a marketplace: thousands of open image, video, audio, and language models behind one API, billed per second, with zero setup. Fireworks AI is a performance engine: fast, cheap serving of popular open LLMs and your fine-tunes, billed per token. Baseten is a deployment platform: bring your own model, get autoscaling production infrastructure with observability. Prototype on Replicate, serve text on Fireworks, ship custom models on Baseten.
Not every product wants to call OpenAI. Open-weight models are cheaper, private, and customisable — but somebody has to run them on GPUs. These three companies do that in three different ways, and picking the wrong one either costs you engineering time or money.
Replicate
- Widest catalogue of any host, especially creative models — image, video, audio, upscaling
- One HTTP call per model; per-second billing that scales to zero
- Fine-tune image models and deploy your own with Cog
- Cold starts on unpopular models can be slow; costs hard to predict on long generations
Fireworks AI
- Optimised for tokens per second and cost per token on open LLMs like Llama, Qwen, and DeepSeek
- Serverless and on-demand options, plus fine-tuning with LoRA adapters served at base-model price
- Strong for production chat, RAG, and agent backends
- Narrower model catalogue than Replicate; less relevant for image or video
Baseten
- Deploy any model you can package with Truss, with autoscaling and scale-to-zero
- Optimised engines for LLMs, Whisper, and image models; metrics and tracing built in
- Dedicated and self-hosted options for compliance
- Usage-based GPU pricing needs monitoring; steeper learning curve
The decision
- Adding image or video generation to an app: Replicate
- Serving an open LLM at scale as cheaply as possible: Fireworks
- Running your own fine-tuned or custom model in production: Baseten
- Not sure yet: Replicate to prototype, then move when the bill or latency tells you to
Related reading
Bottom line
Replicate for breadth, Fireworks for speed and price on text, Baseten for control. Most teams end up using two of the three, and none of them requires you to know what a CUDA driver is.
