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Replicate vs Together AI: Complete AI Inference Comparison

Compare Replicate and Together AI on model offering, pricing, latency, and developer experience. Discover which AI inference platform best fits your project.

Replicate

A platform for running open-source ML models via a simple API. Replicate hosts thousands of models (LLMs, image generation, speech) and charges per-second compute. No infrastructure management — you call models as an API and pay per use.

Together AI

An inference platform focused on hosting open-source LLMs and embeddings with low latency and favorable pricing. Together offers Llama, Mistral, Qwen, and proprietary models via a unified API. Strong in throughput and developer experience.

Comparison table

FeatureReplicateTogether AI
Model offeringVery broad — LLMs, image, audio, video modelsFocus on LLMs and embeddings — less image/audio
PricingPer-second GPU — varies per modelPer token — often more favorable for text
Cold startCan be slower — models load on demandFaster cold start for popular models
API styleREST — different inputs/outputs per modelOpenAI-compatible API — easy swap

Verdict

Replicate is ideal for broad model offering and multimodal use cases. Together AI excels for pure LLM inference with favorable pricing and low latency. Choose Replicate for image/video/speech; choose Together for production LLMs.

Our recommendation

At AVARC Solutions we use Replicate for image and video models (e.g. Stable Diffusion), and Together for text LLMs when cost efficiency and latency are priorities. Both integrate easily into Next.js and Node.js backends.

Further reading

What is AI?What is an LLM?Groq vs Together AI comparison

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Frequently asked questions

It depends on usage. Replicate charges per-second GPU; Together per token. For many text requests Together is often cheaper. For image generation Replicate is competitive.
Together focuses primarily on LLMs and embeddings. For image generation, Replicate or dedicated providers like Stability are better suited.
Yes, Replicate supports deploying your own models via Cog. You can containerize your model and run it on Replicate.

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