For developers building GTM and AI agents, Together AI is an inference and GPU-cloud platform that serves 200+ open and open-weight models — built by the researchers behind FlashAttention and Mamba — positioned as a faster, cheaper alternative to hyperscaler inference.
Presence & Market Position
#28 of 103
GTM Developer Tools
▲ 193 60-day move
Measures earned, engagement-weighted share of voice across the GTM voices panel. Methodology →
Together AI is positioning itself as the AI Native Cloud for open-model production, turning its inference-systems research into a full stack for serving, tuning, and operating models at scale. Conversation around the company centers on day-zero model availability, throughput and latency, GPU capacity, and the economics of open weights versus proprietary APIs. Recent discussion also places Together inside enterprise-agent infrastructure, from coding workloads and long-running workflows to secure customization. The strongest proof points are technical: launch partnerships for new models, production benchmarks, dedicated clusters, and research on kernels and trillion-token agent workloads.
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Business Profile
Founded in 2022, Together AI has grown from serverless open-model inference into a 380-person infrastructure company spanning dedicated endpoints, GPU clusters, fine-tuning, and agent tooling. It remains independent, with $533.5 million in recorded funding, $1.15 billion in annualized bookings claimed in July 2026, and an $8.3 billion valuation reported that month. Systems research such as FlashAttention, Mamba, and ATLAS supports its technical identity, while the CodeSandbox and Refuel.ai acquisitions added sandboxed code execution and structured-data capabilities around the core inference platform.
Agent Readiness
Measures how easily your agents can build on it — API, MCP, CLI, SDK, docs depth. Methodology →
Together AI is built for agent workloads at the infrastructure layer. Its inference APIs serve open models for coding, tool use, speech, vision, and long-running workflows, while dedicated endpoints and GPU clusters provide reserved production capacity. Code Interpreter adds sandboxed execution, and the documented MCP server exposes Together’s documentation and agent skills inside coding environments. Recent work on ThunderAgent, Kimi K3, and trillion-token workloads reinforces the focus on high-throughput agent execution.
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