Together AI
Full‑stack AI cloud platform enabling high‑performance training, fine‑tuning, inference, and GPU compute for open‑source generative models.
What is Together AI?
Together AI is an American AI infrastructure company founded in June 2022 and headquartered in San Francisco. Its platform delivers a research‑optimized cloud stack for training, fine‑tuning, inference, and GPU cluster compute tailored to open‑source generative models, with performance gains from custom kernel innovations like FlashAttention and proprietary inference engines. The platform supports over 200 open‑source models across modalities (text, image, audio, code) and is used by developers and enterprises seeking faster inference, lower costs, and full‑stack AI infrastructure.
What you can do with it
Rapid experimentation with open‑source models
Developers can quickly swap between models via a unified API to prototype text, code, or multimodal tasks without managing infrastructure.
Domain‑specific model customization
Teams fine‑tune open models (e.g. Llama, Mistral) using LoRA or full‑tuning, with supervised or preference‑driven formats for tailored behavior.
Low‑latency production inference
Deploy inference workloads on dedicated GPU endpoints to ensure consistent performance for high‑throughput applications.
Agentic application development
Use the integrated code sandbox to safely run and test LLM‑driven agents with custom logic and workflows.
Efficient model iteration
Leverage fast preprocessing and batching to iterate quickly through tuning and deployment cycles with lower latency overhead.
Key features
- Unified API access to 200+ open‑source models
- High‑performance serverless inference with batching and model‑specific throughput tuning
- LoRA and full‑parameter fine‑tuning (including supervised and preference‑based methods)
- Token‑based pricing for inference and fine‑tuning, with no minimums
- Dedicated GPU instances and on‑demand GPU clusters (H100, H200, B200 hardware)
- Integrated code sandbox environment for agent workflows
- Accelerated preprocessing and speculative decoding for faster throughput
Screenshots
Inputs / Outputs
Strengths & Limitations
Strengths
Performance optimized
Custom kernels (FlashAttention‑3, Together Kernel Collection) and Blackwell GPU infrastructure deliver 2–3× faster inference and up to ~90% faster training throughput.
Strong open‑source support
Platform hosts and integrates hundreds of open‑source models and projects like RedPajama, supporting rapid access to new releases.
Comprehensive full‑stack offering
Includes serverless inference, fine‑tuning, custom training, GPU clusters, storage, sandbox environments, and evaluation tools in a single platform.
Enterprise‑grade compute
Operates large GPU clusters (H100, H200, B200, GB200 NVL72) with substantial power capacity and reserved infrastructure deals.
Open AI ecosystem integration
API supports OpenAI‑compatible endpoints, easing migration from other providers.
Strong leadership and funding
Founded by renowned researchers and entrepreneurs, with over $500M funding to date, valued at over $3B.
Limitations
Pricing complexity
Multiple pricing tiers (serverless, dedicated, cluster, reserved) may require analysis to estimate costs accurately.
Enterprise focus
Platform is optimized for high‑scale use; may be overkill for casual or low‑volume users.
Opaque educational pricing
No publicly advertised free tier or clear student pricing, despite 'freemium' label; limited transparency on free access.
Complex infrastructure
Users unfamiliar with GPU cluster configuration or research tooling may face steep learning curve.
Pricing & Plans
Model: Freemium
Free Credit
Includes $5 in free credits for initial experimentation with inference or fine‑tuning
Serverless Inference
Pay‑as‑you‑go token pricing across model catalog, varies by model complexity
Fine‑Tuning
LoRA or full tuning; supervised or preference‑based methods; cost depends on model size and method
Dedicated GPU Instances
Single‑tenant H100/H200/B200 hardware with guaranteed performance
Serverless inference billed per million tokens (e.g. Llama 4 Maverick ~$0.27 per input million tokens); dedicated inference endpoints from $3.99/hr (H100) up to $9.95/hr (B200); on-demand GPU clusters $3.49–$7.49/hr, reserved clusters discounted by multi‑month commitments.
Who it's for
Ideal for
AI engineers, researchers, or startups requiring high-performance compute and infrastructure for open‑source model training, fine‑tuning, or inference.
Not ideal for
Casual users or small teams with minimal compute needs or limited budget, seeking simple low‑cost solutions.
What users say
- High performance
- Open‑source friendly
- Research‑grade tooling
- Enterprise reliability
FAQ
What modalities does Together AI support?+
The platform supports text, image, audio, and code generative tasks across hundreds of open‑source models.
How is pricing structured?+
Pricing includes token‑based serverless inference; hourly billing for dedicated endpoints; on‑demand and reserved GPU clusters with volume discounts.
Are the APIs OpenAI‑compatible?+
Yes, inference APIs are compatible with OpenAI’s format for easy migration.
What makes Together AI perform better than hyperscalers?+
Use of custom kernels like FlashAttention‑3 and high‑efficiency GPU infra (Blackwell, GB200) yields faster inference and training at lower cost.
Ratings & Reviews
No reviews yet — be the first to rate this tool.