Together AI

What is Together AI?

Together AI is a cloud platform where developers and AI pioneers can train, fine-tune, and run frontier models. It provides access to over 200 generative AI models across various categories including chat, code, image, and more with OpenAI-compatible APIs.

Top Features:

• Extensive model library: access to 200+ generative AI models including Llama, Qwen, DeepSeek, and more.
• Advanced hardware: runs on cutting-edge infrastructure like NVIDIA GB200 NVL72 and Blackwell GPUs.
• OpenAI-compatible APIs: allows easy migration from closed models to open-source alternatives.
• Multimodal capabilities: supports text, image, audio, code, and vision models in one platform.

Use Cases:

• AI model training: develop and train large language models with powerful GPU infrastructure.
• Content generation: create text, images, code, and other content using various specialized models.
• Research and development: experiment with frontier AI models for academic or commercial purposes.
• Enterprise AI deployment: implement production-ready AI solutions with high availability and performance.

Who Can Use Together AI?

• AI researchers: professionals working on advancing AI capabilities and exploring model architectures.
• Software developers: engineers integrating AI capabilities into applications and products.
• Tech companies: organizations building AI-powered products that require scalable infrastructure.
• AI startups: new ventures developing specialized AI applications with limited infrastructure resources.

Pricing

• 1x H100 80GB ($3.99/hour): Dedicated inference, single-tenant GPU instance.
• 1x H200 141GB ($5.49/hour): Dedicated inference, single-tenant GPU instance.
• 1x B200 180GB ($9.95/hour): Dedicated inference, single-tenant GPU instance.
• HGX H100 ($3.49/hour): GPU Clusters, on-demand pay-as-you-go capacity.
• Serverless Inference: Pay per 1M tokens, e.g. Llama 3.3 70B $0.88 in/out.

Pros and Cons

Pros:

• Model variety: impressive selection of models covering numerous specialized use cases.
• High-performance hardware: access to state-of-the-art GPU infrastructure for demanding workloads.
• Open-source focus: emphasis on open models provides flexibility and transparency.
• Cost efficiency: competitive pricing for high-quality models compared to closed alternatives.

Cons:

• Technical complexity: requires AI expertise to fully utilize the platform's capabilities.
• Learning curve: navigating many models and options may overwhelm new users.
• Specialized focus: primarily aimed at AI professionals rather than casual users.
• Documentation depth: might need more comprehensive guides for some specialized models.

FAQs:

1) What makes Together AI different from other AI platforms?

Together AI focuses on frontier models with open-source alternatives to closed systems, running on specialized hardware for maximum performance.

2) Can I migrate from OpenAI to Together AI easily?

Yes, Together AI provides OpenAI-compatible APIs that make switching straightforward with minimal code changes.

3) What types of models are available on Together AI?

The platform offers models for chat, code, image generation, audio, vision, embeddings, reranking, and moderation.

4) Is Together AI suitable for production applications?

Yes, it provides 99.9% availability for many models, making it suitable for production-grade applications.

5) How does pricing work on Together AI?

Pricing varies by model, with some offering specific rates (like $1/M input, $3/M output for Kimi-K2) and free tiers for testing.