The open-source LLM inference cloud. Cheapest production API for Llama, Mistral, Qwen, and 200+ open models. $5 free credit to start.
Together AI runs a custom GPU cluster optimized for inference. They've built their own attention algorithms (the "Together Decoding" stack) that beat vLLM and TensorRT-LLM on throughput. For developers building products on open-source models (Llama, Mistral, Qwen, DeepSeek), Together is 3-10x cheaper than OpenAI for equivalent quality on many tasks. $5 free credit on signup is enough to ship an MVP.
Who it's for: AI engineers, indie hackers building on Llama/Mistral, startups that need production-grade LLM API without paying OpenAI rates, fine-tuners needing GPU training.
Llama 3.3 70B at $0.88/M tokens. DeepSeek V3 at $0.45/M. Mixtral 8x7B at $0.30/M. Compare to OpenAI's GPT-4o at $2.50/M input. The savings at scale are massive.
Together's custom inference stack is 2-3x faster than self-hosted vLLM on the same GPUs. Median latency ~150ms for 70B models. Beats most competitors on tokens/sec/$ benchmark.
Llama, Mistral, Qwen, DeepSeek, Gemma, Phi, Command-R, Yi, every major open-source model the day it releases. Drop-in API replacements — same OpenAI-compatible endpoint.
LoRA and full fine-tuning on Llama, Mistral, Qwen. Bring your own dataset (JSONL), get a custom model in 1-3 hours. Hosted on Together's GPUs — no A100/H100 rental needed.
If you're building on open-source LLMs in production, Together AI is the default choice in 2026. The pricing is unbeatable for what you get, and the OpenAI-compatible API means migrating takes 5 minutes. For proprietary frontier models (Claude, GPT-4), you'll still need OpenAI/Anthropic. For everything else, Together saves real money.
Closest Together competitor. Best-in-class function calling and structured outputs.
Run any model on cloud GPUs. Best for image/video models, not just LLMs.
LPU-powered ultra-fast inference. Beats Together on speed, loses on price.
Serverless GPU compute. Best for running custom Python AI code, not managed APIs.