Together AI
Run open-source models at scale. Cost-effective for high-volume agent workloads.
Together AI is a cloud platform built specifically for AI inference, offering developers and organizations fast, cost-effective access to a wide range of open-source large language models. Positioned as an alternative to proprietary model providers like OpenAI and Anthropic, Together AI focuses on open-source models — including Llama, DeepSeek, Qwen, MiniMax, and others — giving teams flexibility without vendor lock-in.
The platform operates across several deployment modes. Serverless Inference provides on-demand API access to models without managing infrastructure. Batch Inference targets workloads that process large volumes of tokens at once, with pricing up to 50% lower than standard serverless rates. Dedicated Model Inference provisions custom hardware for teams that need predictable performance and isolation. Dedicated Container Inference extends this to fully custom model deployments.
Beyond inference, Together AI offers a compute layer with GPU Clusters and an AI Factory for frontier-scale infrastructure needs. Developers can fine-tune models on their own data, run evaluations to benchmark quality, and use a Sandbox environment for prototyping. Managed Storage handles model weights and datasets securely.
The platform is built around performance research. Together AI's team publishes and maintains work on FlashAttention (including FlashAttention-4, which targets NVIDIA Blackwell GPUs), ATLAS (a runtime-learning speculator system delivering up to 4x faster LLM inference), and ThunderKittens. This research orientation means performance improvements flow directly into the hosted platform.
In the LLM provider landscape, Together AI competes with services like Fireworks AI, Groq, Replicate, and Anyscale. Its differentiation lies in the breadth of supported open-source models, the combination of inference and compute offerings under one roof, and its proprietary inference optimization research. For teams running high-volume agentic workloads — where token costs accumulate quickly — Together AI's pricing and batch capabilities make it a practical choice compared to premium-tier closed model providers.
The platform includes a model library, a web-based playground, a chat interface (Together Chat), and a 'Which LLM to use' tool for model selection guidance. Documentation, cookbooks, and demo apps round out the developer experience. A startup accelerator program is available for early-stage companies building on the platform.
Key Features
- Serverless Inference API with access to a large library of open-source models including Llama, DeepSeek, Qwen, and MiniMax
- Batch Inference API for processing large token volumes at up to 50% lower cost compared to standard inference
- Dedicated Model and Container Inference for teams requiring custom hardware or private model deployments
- GPU Clusters and AI Factory for organizations needing scalable, self-service NVIDIA GPU compute
- Fine-tuning platform supporting larger models and longer contexts with custom training data
- Model evaluation tools to measure and benchmark model quality
- Proprietary inference research including FlashAttention-4 and ATLAS speculative decoding (up to 4x faster inference)
- Developer tools including a playground, Together Chat, model library, cookbooks, and sandbox environments
Pros & Cons
Pros
- Wide selection of open-source models in a single API, reducing the need to manage multiple providers
- Batch Inference API significantly reduces costs for high-volume workloads
- In-house inference research (FlashAttention, ATLAS) delivers performance improvements that benefit hosted users
- Combines inference, compute, fine-tuning, and storage under one platform
- OpenAI-compatible API surface lowers switching and integration costs
Cons
- Does not provide access to proprietary closed models (GPT-4, Claude, Gemini), so teams needing those must maintain separate integrations
- Dedicated infrastructure options may introduce complexity for smaller teams
- Fine-tuning and evaluation tooling is newer and may lack depth compared to specialized ML platforms
- GPU cluster availability and pricing depend on hardware supply, which can vary
Pricing
Together AI offers a Batch Inference API at up to 50% lower cost than standard serverless inference for most models. Serverless, dedicated, and compute pricing details are available on the official pricing page. Visit the official website for current pricing details.
Who Is This For?
Together AI is best suited for development teams and companies building high-volume AI applications — particularly agentic pipelines, voice agents, or batch processing workflows — where inference cost and throughput are critical constraints. It is an especially strong fit for organizations committed to open-source models who want a single provider for inference, fine-tuning, and compute rather than stitching together multiple services.
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