Baseten vs Replicate: Token Pricing, Speed & Intelligence
Full comparison of Baseten and Replicate — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Rates sourced from public APIs — verify before use.
Baseten
Production ML infrastructure — deploy any model with custom serving, autoscaling, and GPU selection
Baseten is a production ML infrastructure platform for deploying custom and open-weight models with full control over serving configuration, GPU selection, autoscaling, and cold-start behavior. Unlike managed inference APIs, Baseten lets you bring your own model weights, custom preprocessing, and serving logic. It supports Truss (Baseten's open-source model packaging format), vLLM, TensorRT-LLM, and custom Python serving code. Ideal for teams that need more control than a managed API but less overhead than raw Kubernetes.
Replicate
Run any open-source AI model via API — FLUX 1.1 Pro, Llama 4, video, audio, and custom models
Replicate is a platform for running open-source AI models via a simple API. It hosts thousands of community models including FLUX 1.1 Pro, Llama 4, Stable Diffusion, Whisper, and video generation models. Pay per prediction with no infrastructure to manage. The 2026 catalog has expanded significantly with FLUX 1.1 Pro Ultra, Kling v2.1, and Llama 4 Scout/Maverick. Custom model deployment via Cog remains a core differentiator.
Key metric comparison
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$0.05
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$0.25
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300 tok/s
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250ms
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74/100
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131K
Live token pricing
Strengths and weaknesses
Baseten
Replicate
Key differentiators
The production ML platform that gives you managed-API convenience with custom-serving flexibility — deploy any model with your own preprocessing logic, GPU selection, and autoscaling without managing Kubernetes.
A broad catalog of community AI models — if a model exists on Hugging Face, it's likely on Replicate. Strong coverage for image, video, and audio model access, plus custom model deployment via Cog.
Frequently asked questions
Baseten FAQs
What is Baseten?
Baseten is a production ML infrastructure platform for deploying AI models with custom serving logic, GPU selection, and autoscaling. It supports any open-weight model or custom fine-tune via the Truss packaging format.
How does Baseten differ from Together AI or Replicate?
Baseten gives you full control over the serving stack — custom preprocessing, postprocessing, GPU selection, and autoscaling behavior. Together AI and Replicate are managed APIs with fixed serving; Baseten is for teams that need custom model serving logic.
What GPUs does Baseten support?
Baseten supports H100 SXM, H100 PCIe, A100 80GB, A10G, and T4 GPUs with per-second billing. You select the GPU type per deployment based on your model's memory and throughput requirements.
Replicate FAQs
What new models did Replicate add in 2026?
Replicate added FLUX 1.1 Pro Ultra, Kling v2.1 (video generation), Llama 4 Scout and Maverick, and many other models in 2026. The catalog is continuously updated as new community models are released.
How does Replicate pricing work?
Replicate charges per prediction based on compute time used. Pricing varies by model and GPU type. Text models are billed per token; image models per image; video models per second of output. Some models are free with rate limits.
Can I deploy my own model on Replicate?
Yes. Replicate lets you package and deploy custom models using Cog, their open-source model packaging tool. Once deployed, your model gets a public API endpoint with automatic scaling.
Provider resources
Key strengths compared
Baseten
- Full control over model serving: custom preprocessing, postprocessing, and business logic
- Bring your own weights — deploy any HuggingFace model or custom fine-tune
- GPU selection: H100, A100, A10G, T4 with per-second billing
- More setup required than managed APIs — not a drop-in OpenAI replacement
- Cold starts on scale-to-zero deployments (configurable warm pool available)
Replicate
- Broad catalog of community AI models — text, image, video, audio
- FLUX 1.1 Pro Ultra and Kling v2.1 in the 2026 catalog
- Llama 4 Scout and Maverick available
- Higher per-token cost than dedicated text inference APIs
- Cold start latency on less popular models
Key weaknesses compared
Baseten
- More setup required than managed APIs — not a drop-in OpenAI replacement
- Cold starts on scale-to-zero deployments (configurable warm pool available)
- Pricing is higher than shared inference APIs for low-volume workloads
Replicate
- Higher per-token cost than dedicated text inference APIs
- Cold start latency on less popular models
- Less suitable for high-throughput text inference
Provider category context
Baseten is a inference api, founded in 2019. Replicate is a inference api, founded in 2021. Both are inference api providers — the comparison is primarily about pricing, model selection, and feature differentiation within the same tier.
How to choose between them
Both Baseten and Replicate host open-weight models. The key differentiators are latency, throughput, and which specific model versions each provider offers. Check the speed metrics above — inference API providers often differ significantly on tokens-per-second for the same model. Pricing is typically competitive between them; availability of specific model versions (e.g., Llama 3.1 405B, DeepSeek V3) may be the deciding factor.