Together AI provides serverless LLM inference for open models and custom fine-tuned variants, enabling builders to ship AI features without managing infrastructure.
Together AI is an inference platform designed for builders shipping AI-powered features at scale. The service hosts open-source language models (Llama, Mistral, Qwen, and others) alongside proprietary options, offering API-first access without requiring operators to provision or manage GPU infrastructure. The platform targets teams that need predictable inference costs and model flexibility. Rather than committing to a single closed model, builders can experiment across open models, switch between providers, or fine-tune variants on Together's infrastructure. This is particularly valuable for teams building domain-specific applications where model selection directly impacts product quality and cost. Key operational decisions: Together AI charges per token (input and output), with pricing varying by model size and quantization. Verify current pricing on vendor site. The service includes batch inference for non-real-time workloads, which can reduce per-token costs significantly. Builders can also upload custom fine-tuned models and serve them through the same API, avoiding vendor lock-in on model weights. Integration is straightforward for teams already using LLM APIs—the SDKs and REST endpoints follow familiar patterns. The platform supports streaming responses, which is essential for user-facing chat and generation features. Operators should verify current model availability and SLA terms on the vendor site, as model catalogs and performance guarantees evolve. Common use cases include: chat interfaces powered by open models, content generation with fine-tuned variants, retrieval-augmented generation (RAG) pipelines, and cost-optimized inference for high-volume applications. Teams often choose Together AI when they need to balance cost, model control, and infrastructure simplicity—particularly if they're evaluating multiple models or building multi-tenant systems where model selection is a product decision.
Together AI provides serverless LLM inference for open models and custom fine-tuned variants, enabling builders to ship AI features without managing infrastructure.
Ship chat interfaces powered by open-source language models without managing GPU infrastructure; Fine-tune and serve custom models for domain-specific tasks (legal, medical, technical domains); Build cost-optimized inference pipelines for high-volume text generation and summarization; Experiment across multiple models (Llama, Mistral, Qwen) to optimize for quality and latency.
Together AI uses a usage based pricing model, starting around See vendor site — sample data, with a free plan available. Pricing changes often — confirm current tiers on the vendor site.
Yes, Together AI lists an API, so you can integrate it into custom workflows.
Inference latency and availability depend on shared infrastructure (verify SLA terms on vendor site); Per-token pricing can become expensive at very high volumes compared to self-hosted solutions; Model catalog and availability subject to change; verify current offerings before architecture decisions; Limited control over underlying hardware and optimization compared to dedicated GPU rental.
Popular Together AI alternatives include vllm, modal, replicate, anyscale. See the full alternatives page for side-by-side comparisons.