- Specialization
- Distributed Computing
- Business
Compute Hostingand 1 more business valuesLess
- Inference Serving
- Market
Software Developmentand 1 more market valuesLess
- Scientific Research
- Ecosystem
- Neoclouds
- Customers
Developersand 2 more customers valuesLess
- Enterprises
- Researchers
More details
- Organization type
- Commercial Company
- Ecosystem
- Neoclouds
- Business
- Compute Hosting, Inference Serving
- Specialization
- Distributed Computing
- Market
- Software Development, Scientific Research
- Customers
- Developers, Enterprises, Researchers
- Delivery models
- Managed Compute, API
- Revenue models
- Usage Based
- Listing status
- Not classified
- Latest equity round
- Series C
- Reported funding amount
- Not classified
About
Together AI builds a full-stack AI cloud platform for developing, training, fine-tuning, and running production models. It sells to AI developers, researchers, startups, and enterprises, differentiating through systems research and infrastructure optimized for AI workloads.
Market
Together AI competes in the AI infrastructure and AI cloud market, providing managed inference, model customization, and GPU compute for open-source generative AI models. It positions itself as an AI Native Cloud with a vertically integrated stack spanning accelerators, interconnects, orchestration, training, and inference. Its differentiation is the combination of research-driven efficient inference, serverless and dedicated deployment options, fine-tuning, and GPU clusters without requiring customers to manage infrastructure or make long-term commitments.
Together AI targets AI-native startups and enterprises building or operating production-scale AI applications, particularly organizations needing inference, model customization, and dedicated GPU capacity. Its primary buyers are CTOs, engineering leaders, and AI/ML teams.
At a Glance
Problem
AI teams need to move open-source models from experimentation into reliable production services, but doing so requires specialized GPUs, high-speed networking, orchestration, training, and inference infrastructure. The pain is both technical and economic: latency, throughput, GPU utilization, and serving costs directly affect the viability of AI products. Together AI’s optimization work frames the central need as reducing inference latency without massive cost, with performance gains of up to 2x for leading open-source models.
The killer use case is production inference for AI-native companies: serving popular open-source models through dependable APIs without building and operating the entire GPU and model-serving stack themselves. Fine-tuning models and scaling dedicated compute are adjacent needs for teams that want more control, lower unit economics, or specialized behavior.
Product / Service
Together AI positions itself as an AI Native Cloud: a full-stack platform spanning serverless and dedicated inference, accelerated compute, and model shaping. Its products let customers build, fine-tune, and deploy open-source models, while also providing GPU clusters on the same production-oriented platform. The delivery model combines API access for on-demand model inference with dedicated infrastructure for workloads requiring predictable capacity or deeper customization.
The benefit is consolidation and speed. Rather than separately sourcing GPUs, managing networking and orchestration, optimizing inference engines, and operating model endpoints, customers can use one platform to develop and run models. Together AI’s infrastructure and optimization focus is intended to improve latency and throughput while reducing the operational burden and cost of serving open-source AI at scale.
Market
Together AI competes in AI infrastructure and the emerging AI-native-cloud or GPU-cloud category, with a particular focus on open-source model inference, fine-tuning, training, and dedicated compute. Comparable offerings include Replicate, Fireworks AI, Anyscale, and Modal: Replicate emphasizes simple deployment, Fireworks and Together emphasize performance and model catalog breadth, Anyscale is built around Ray, and Modal offers a more general serverless compute model.
The available evidence indicates that Together AI is a commercial, scaled company rather than pre-revenue. As of July 2026, it said it was trusted by thousands of customers, including Cognition, Decagon, and Eleven; third-party reporting also described its API business as generating a material share of revenue. Its disclosed financing included a $305 million Series B announced in February 2025 at a reported $3.3 billion valuation, signaling substantial investor conviction in the market for AI infrastructure and open-source model deployment.
Founders & Leadership
Funding History
Lux Capital
Kleiner Perkins
Salesforce Ventures
General Catalyst, Prosperity7 Ventures
Aramco Ventures
Recent News
Mubadala Investment Company and Together AI announced a strategic partnership to explore AI infrastructure and ecosystem opportunities in the UAE. Together AI said it would establish a local presence in Abu Dhabi, bringing its AI compute infrastructure and open-source model platform closer to regional demand.
Together AI introduced automatic idle shutdown for dedicated deployments. The feature is intended to shut down idle deployments automatically and was listed under new releases.
Together AI launched rollouts for dedicated model inference, enabling traffic to move between deployments under the same endpoint without changing its URL. The release supports canary, blue-green, and rolling strategies, with optional live-metric gates, and was incorporated into Together CLI and Python SDK version 2.34.0.
Together AI added MiniMaxAI/MiniMax-H3 to its serverless model offering. The changelog lists pricing of $0.1391 per second at 2K.
Together AI made DeepSeek-V4.1-Flash available through its serverless model catalog. The model supports a 1-million-token context length, FP8 quantization, function calling, and structured outputs.
Equinix announced a new collaboration with Together AI and NVIDIA to deliver Equinix Inference Exchange, a distributed AI inference program for global enterprises. The offering combines NVIDIA’s Enterprise Reference Architectures, Together AI’s inference platform, and Equinix’s global infrastructure and connectivity.
Together AI and HUMAIN announced a strategic partnership to connect HUMAIN’s expanding Saudi Arabian AI compute capacity with Together AI’s global customer ecosystem and inference platform. The partnership includes construction of a new 250-megawatt data center in Saudi Arabia and is expected to generate more than $5 billion in gross annualized revenue in its first year.
Together AI and IBM signed a multi-year $240 million agreement to build a large-scale AI inference cluster on IBM Cloud using NVIDIA HGX B300 systems and Spectrum-X networking. Together AI will use the cluster to provide open-source model inference services to enterprise customers, with availability expected in Q1 2027.
Together AI launched Provisioned Throughput, a reserved inference-capacity product for frontier open models with token-based pricing and a 99% uptime SLA. It initially supports MiniMax M3 and GLM-5.2 across North America, EMEA, and other regions.
Together AI announced an $800 million Series C backed by investors including Aramco Ventures, NVIDIA, Vista Equity, General Catalyst, and Salesforce Ventures. The company also secured commitments for more than 500 MW of compute capacity to support future growth.
Together AI introduced a new brand identity centered on its positioning as the AI Native Cloud and as a backend for AI-native builders. The announcement described the platform as providing building blocks for open-model and AI application development.
VentureBeat covered Together AI's ATLAS research and system, an adaptive speculator designed to overcome the limitations of static speculative-decoding systems. ATLAS learns from workloads in real time to improve inference speed.
Active Roles
76Business Model
Together AI generates revenue through per-token API usage for model inference and GPU server rentals for training, fine-tuning, and serving workloads. Its API business scales with inference volume, while GPU rentals represent the larger revenue share.
Products
Customers
Tech Stack
Similar Companies
Competitors
Key Investors
Prosperity7 Ventures, General Catalyst, Nvidia, Salesforce Ventures, Coatue, Lux Capital, Emergence Capital, Kleiner Perkins, NEA, 137 Ventures