Replicate vs Together AI: LLM APIs Comparison (2026)
Replicate focuses on a pay-per-usage system with extensive open-source model access and custom deployment, while Together AI offers more structured GPU cluster access, serverless inference, and fine-tuning capabilities, with a clear starting price.
AI Citation Scorecard
How often each is cited by major AI engines when buyers ask llm apis questions. Last 90 days across ChatGPT, Perplexity, Gemini, Claude, and Copilot.
Probes run hourly; each (engine × query) combo retests every ~3 days.
Pricing
Key Features
- ✓Pay per usage model
- ✓Thousands of open-source models
- ✓Custom model deployment using Cog
- ✓Fast booting fine-tunes available
- ✓Dedicated hardware for private models
- ✓Auto-scaling for high traffic
- ✓Integrates with existing workflows
- ✓Supports various input/output types
- ✓On-demand GPU Clusters
- ✓Serverless Inference
- ✓Fine-Tuning
- ✓Dedicated Inference
When to choose Replicate
Replicate is suitable for users who prioritize access to a vast array of open-source models, require flexible pay-per-usage billing, and need custom model deployment with features like dedicated hardware and auto-scaling.
When to choose Together AI
Together AI is suitable for users who need on-demand GPU clusters, serverless inference, and fine-tuning options, with a predictable starting price point. It aims for high scalability and user-friendliness.
Frequently Asked Questions
AI visibility profiles
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