Together AI

Snapshot Verdict

Together AI is a high-performance cloud platform designed to help developers build and run generative AI applications without being locked into a single provider like OpenAI. It offers one of the fastest inference engines on the market, supporting a vast library of open-source models including Llama 3, Mistral, and Qwen. While it lacks the "chat" interface casual users might expect, it is a powerhouse for technical professionals who need speed, customizability, and lower costs than traditional proprietary models.

Product Version

Version reviewed: API Platform Current Production Build (Oct 2024)

What This Product Actually Is

Together AI is a decentralized cloud platform specifically engineered for large language models (LLMs). Think of it as a specialized alternative to AWS or Google Cloud, but built exclusively for AI. Instead of renting a general-purpose server, you use Together AI to access pre-hosted AI models or to train and "fine-tune" your own versions of those models.

The core of the product is the Together Inference engine. This is the technology that takes a user's prompt and generates a response. Together AI has gained significant attention in the tech community by optimizing how these models run on Nvidia GPUs, often delivering tokens (words) much faster than the original creators of the models can.

The platform targets three main activities: Inference (running a model to get answers), Fine-tuning (teaching an existing model new specific data), and GPU Clusters (renting raw hardware for massive projects). For the average professional, the primary use case is the Inference API, which allows you to plug models like Llama 3 directly into your own apps or workflows.

Real-World Use & Experience

Using Together AI feels less like talking to a robot and more like working in a laboratory. When you log in, you are greeted by the "Playground." This is a clean, technical interface where you can select from dozens of open-source models. You can adjust technical parameters like "Temperature" (how creative the AI is) and "Top P" (how it selects words).

For a developer, the experience is seamless. They provide API keys that are compatible with the OpenAI library format. This means if you have an app already built for ChatGPT, you can often switch it to Together AI by changing just two lines of code. This "drop-in" compatibility is a major tactical advantage.

In testing Llama 3.1 405B (one of the largest open models) via Together AI, the speed is the first thing you notice. While proprietary models sometimes stutter or pause during long generations, Together’s custom inference stack tends to stream text at a rapid, consistent clip. However, the experience is strictly utilitarian. There are no built-in web search tools, image generators, or file-analysis features unless you build them yourself or choose a specific model that supports them.

Standout Strengths

• Industry-leading inference speeds.
• Massive library of open-source models.
• OpenAI-compatible API integration.

The speed advantage cannot be overstated. Together AI uses a proprietary "FlashAttention" implementation and other low-level optimizations that make open-source models feel significantly more responsive than when hosted on standard cloud infrastructure.

The variety is the second major win. If a new model is released by Meta, Mistral, or a research collective, it is usually live on Together AI within hours. This allows users to experiment with different "flavors" of AI to find the one that best suits their specific tone or task, rather than being stuck with whatever version of GPT-4 is currently available.

Lastly, their pricing model is transparent. You pay per million tokens, and for many models, this cost is a fraction of what you would pay for GPT-4o or Claude 3.5 Sonnet. For high-volume tasks like analyzing thousands of customer reviews or generating bulk SEO content, the savings are substantial.

Limitations, Trade-offs & Red Flags

• Steep learning curve for non-developers.
• No integrated consumer chat interface.
• Occasional rate-limiting on popular models.

Together AI is not a replacement for ChatGPT or Claude.ai for the average person. If you want a tool that can "read this PDF and summarize it," you will be disappointed. You would have to build that tool yourself using their API. The Playground is great for testing, but it is not designed for daily productivity or long-form conversation management.

Privacy and data handling are also considerations. While Together AI is enterprise-grade, using open-source models requires the user to be more aware of what model they are choosing and how it handles data. Unlike a closed ecosystem, the "intelligence" varies wildly between the 100+ models available on the platform.

Reliability can occasionally fluctuate. During major model launches (like the Llama 3 release), the platform can experience latency spikes as thousands of developers rush to test the new weights. While they have improved their infrastructure, it still lacks the "infinite" feel of the massive hyperscalers like Microsoft Azure.

Who It's Actually For

Together AI is for the "Builder." This includes software developers, data scientists, and AI hobbyists who are tired of the restrictions and costs of proprietary models. It is an excellent choice for a startup founder who wants to ensure their product isn't killed by a sudden price hike from OpenAI.

It is also ideal for researchers who need to "fine-tune" a model. If you have a specific dataset—say, legal documents from a specific jurisdiction—and you want an AI to learn that specific style, Together AI provides the easiest path to training that model and then hosting it.

Digital nomads and solo-preneurs who use "no-code" tools (like Make.com or Bubble) will also find value here. As long as the no-code tool can send an API request, Together AI acts as a cheaper, faster engine to power their automations.

Value for Money & Alternatives

Value for money: great

For anyone running AI at scale, Together AI is one of the most cost-effective options on the market. By leveraging open-source models, you avoid the "brand tax" associated with the major AI labs. Their serverless inference pricing allows you to pay only for what you use, making it accessible for small projects that might grow over time.

Alternatives

• Groq — faster inference for specific models but smaller model selection.
• DeepInfra — similar price-to-performance ratio with a different UI.
• Amazon Bedrock — more enterprise integrations but higher complexity and cost.

Final Verdict

Together AI is the premier destination for those who want to move past the "chat box" and start building with AI. It strips away the polished consumer wrappers and gives you raw, high-speed access to the most powerful open-source brains in the world. If you are comfortable with an API or a technical playground, it is arguably the best value in the AI ecosystem today. If you just want a helpful assistant to help you write emails, stick to ChatGPT.