Together AI
Fast open-source LLM inference platform with 200+ models, fine-tuning, and the largest selection of serverless AI APIs outside OpenAI.
Together AI is an AI cloud platform that runs the broadest selection of open-source LLMs as serverless APIs - over 200 models including Llama 3.1 405B, Qwen 2.5, DBRX, Mistral, DeepSeek, and more. Beyond inference, Together offers a fine-tuning service that allows teams to train custom models on proprietary data and deploy them via the same API. Together Turbo provides accelerated inference for specific models at significantly higher throughput. The platform is OpenAI SDK compatible, making migration straightforward. Together positions itself as the enterprise alternative to Groq (faster) and Hugging Face Inference Endpoints (more models), combining breadth, fine-tuning, and speed in one platform. Raised $228M at a $3.3B valuation.
Key Features
- 200+ open-source models including Llama 3.1 405B, Qwen 2.5 72B, DeepSeek, DBRX, and Mistral
- Fine-tuning service - train custom models on proprietary data and deploy immediately
- Together Turbo - accelerated inference for select models with higher throughput
- OpenAI SDK compatible - minimal code change to migrate from OpenAI to open-source models
- Serverless and dedicated deployments - on-demand or reserved compute options
- Vision models - LLaVA, InternVL, and other multimodal open models via API
- Free $25 credit on sign-up - enough for substantial prototyping
Use Cases
- Startups switching from OpenAI to open-source models to reduce API costs at scale
- AI engineers fine-tuning Llama or Mistral on proprietary data for domain-specific performance
- Researchers accessing the latest open-weight models (Llama 3.1 405B, DeepSeek) via API
- Enterprises requiring data privacy via open-source models with no training on customer inputs
- Developers prototyping applications across multiple model families without managing GPU infrastructure
- Teams needing multimodal open-source capabilities via LLaVA and InternVL vision APIs
Pros
- Widest model selection of any inference provider - 200+ models including models not available elsewhere via API
- Fine-tuning + inference in one platform eliminates the need for separate training and serving infrastructure
- Free $25 credit and pay-as-you-go pricing lets developers prototype before committing to a plan
Cons
- Inference speed on large models (405B) slower than Groq's LPU-based approach for latency-sensitive apps
- Fine-tuning costs and complexity increase significantly for large models and datasets
- Model availability changes frequently - specific versions can be deprecated without long notice
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