Together AI
Business Profile
Core Value Proposition
[Together AI] provides an AI acceleration cloud that enables fast inference, fine-tuning, and training of frontier models on NVIDIA GPUs, with self-service Instant Clusters, serverless and dedicated endpoints, and enterprise-grade security/compliance.
Target Customer
AI researchers, AI engineers, and developers building, fine-tuning, or deploying open-source and proprietary models; AI-native companies needing scalable GPU compute for training, fine-tuning, and inference; teams requiring secure, compliant AI infrastructure.
Key Differentiator
API-first self-service GPU infrastructure with instant cluster provisioning, open-source model support and OpenAI-compatible APIs, no vendor lock-in, enterprise-grade security (SOC 2 Type 2, HIPAA), and optimization stack (Together Kernel Collection, FP8 inference kernels, QTIP quantization, speculative decoding) across multi-cloud and on-prem environments.
Implementation Timeline
Instant Clusters can be provisioned in minutes; clusters can scale from single node to multi-node configurations; burst capacity for production inference supports rapid capacity expansion as needed.
Pain Points
- 1Historically manual and brittle GPU cluster setup requiring tickets, contracts, and complex setup.
- 2Difficulty handling burst workloads for production inference and large-scale training without re-architecting systems.
- 3Need for secure, compliant AI infrastructure (SOC 2 Type 2, HIPAA) and governance with ownership of AI assets.
Key Features
- 1Serverless Inference API and Dedicated Endpoints for inference on open-source models and private deployments
- 2Fine-Tuning support (LoRA and full fine-tuning) and full model training capabilities
- 3GPU Clusters with NVIDIA GB200, H200, H100 (and Blackwell/Hopper readiness) with InfiniBand/NVLink interconnects
- 4Open-source model library and OpenAI-compatible APIs for model deployment and testing
- 5Together Kernel Collection with custom CUDA kernels, Fast FP8 inference, QTIP quantization, and speculative decoding
Target Customer Industries
Decision Makers
- 1Lead Data Scientist
- 2Founding Engineer
- 3Chief Scientist
- 4CEO
Client Results
- 1Hedra: 60% cost savings and 5x performance breakthrough in viral AI video generation
- 2Fractal AI research Lab commentary: Instant Clusters enabled spin-up of large GPU clusters on demand for 24–48 hours, accelerating training and improving research velocity
Competitive Advantages
- 1API-first, self-service provisioning with console/CLI/API access and IaC integrations (Terraform, SkyPilot)
- 2SOC 2 Type 2 and HIPAA compliance for secure workloads
- 3No vendor lock-in and ownership of AI assets; run open-source models on Together Cloud or in a hyperscaler VPC
- 4High-performance hardware and interconnects (InfiniBand, NVLink), with optimized software stack (Together Kernel Collection, FlashAttention-3)
- 5Extensive data-center footprint (25+ cities) and multi-cloud readiness
Key Benefits
Case Studies & Success Stories
Hedra Scales Viral AI Video Generation with 60% Cost Savings
Together AI enabled 60% cost savings and a 5x performance breakthrough in viral AI video generation when standard inference frameworks failed.
Fractal AI research Lab: Accelerating Research Velocity with Instant Clusters
Lead Data Scientist at Fractal AI research Lab described how Together Instant Clusters let them spin up large GPU clusters on demand for 24–48 hours to run intensive training and then scale back down, boosting productivity and research velocity.
Additional Product Information
Product Description
The AI Acceleration Cloud that enables fast inference, fine-tuning, and training of frontier models on GPU infrastructure, with self-service Instant Clusters, serverless and dedicated endpoints, Open-source model support, and enterprise-grade security and governance.
Target Market
AI researchers, AI-native companies, and developers needing scalable GPU compute to train, fine-tune, and deploy sophisticated AI models across open-source and compatible APIs.
Unique Value Proposition
End-to-end, API-first AI compute platform delivering instant GPU clusters, flexible inference endpoints, and full model ownership with secure, compliant infrastructure and open-source model support—without vendor lock-in.
Technical Requirements
{"Kubernetes or Slurm for deployment/orchestration","NVIDIA GPUs (GB200, H200, H100; Blackwell availability in roadmap)","High-performance networking (NVIDIA Quantum InfiniBand, NVLink, NVSwitch)","Shared storage for training/checkpointing, version-pinned drivers/CUDA","Open-source model integration and OpenAI-compatible APIs"}
Pricing Model
Pricing is shown per GPU-hour with term options: 1 Week - 3 Months, 1 - 6 Days, or Hourly. Hardware rates example: HGX H100 Inference − $1.76 /h (1 Week-3 Months), $2.00 /h (1-6 Days), $2.39 /h (Hourly); HGX H100 SXM − $2.20 /h, $2.50 /h, $2.99 /h; HGX H200 − $3.15 /h, $3.45 /h, $3.79 /h; HGX B200 − $4.00 /h, $4.50 /h, $5.50 /h. Shared storage $0.16 per GiB-month; data transfer is free (egress/ingress).
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