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SaaSLens Editorial Team
Editorial Team
SaaSLens Editorial Team, Editorial Team
We rate Together AI 4.3/5. Fastest open-source model inference, making it especially useful for developers and startups. The main tradeoff: smaller model library than hugging face.
About Together AI
Together AI focuses on making open-source model inference fast and cheap. Their infrastructure is optimized for throughput, consistently benchmarking as the fastest provider for Llama, Mixtral, and other popular open-source models.
Pricing is per-token: Llama 3.1 8B at $0.20/M tokens, Llama 3.1 70B at $0.90/M tokens, Mixtral 8x22B at $1.20/M tokens. Image generation models like SDXL run at $0.006/step. New accounts get $5 in free credits.
The API is OpenAI-compatible, making migration trivial. Swap the base URL and API key, and your existing OpenAI SDK code works with Together's models. Function calling and JSON mode are supported for structured outputs.
Fine-tuning is a key differentiator: upload your dataset, select a base model, and Together handles the training. Fine-tuned models are served at the same inference speeds as base models, making custom models practical for production.
For solo developers who want open-source model performance at reasonable cost, Together AI offers the best price-to-performance ratio. It's significantly cheaper than OpenAI for comparable quality using Llama 3.1 70B.
Limitations: the model library is curated (dozens, not thousands), there's no permanent free tier, image and audio model support is narrower than Replicate, and the brand is less established than OpenAI or Anthropic.
Pros & Cons
Pros
- +Fastest open-source model inference
- +Very competitive pricing
- +Excellent developer documentation
- +Strong fine-tuning capabilities
Cons
- -Smaller model library than Hugging Face
- -Less brand recognition
- -No free tier (only trial credits)
- -Limited non-LLM model support
Real-World Sentiment
What Users Love
- ✓The community consensus: fastest open-source model inference sets this tool apart.
- ✓Bootstrapped founders especially value that very competitive pricing.
- ✓In our research, excellent developer documentation is mentioned most often as a highlight.
- ✓Power users note that strong fine-tuning capabilities saves them significant time.
Common Complaints
- ⚠Worth knowing: smaller model library than hugging face.
- ⚠This comes up often in discussions — less brand recognition.
- ⚠The most common criticism is that no free tier (only trial credits).
- ⚠Solo founders should be aware: limited non-llm model support.
Best For
Consider Alternatives If...
- ➜If smaller model library than hugging face matters to you, consider Groq.
- ➜If less brand recognition matters to you, consider Hugging Face.
Best For
- ▶Cost-effective LLM inference
- ▶Fine-tuning custom language models
- ▶Building AI chatbots and assistants
- ▶Batch processing text data
- ▶Replacing expensive proprietary APIs
Key Features
Alternatives to Together AI
Fastest LLM inference via custom AI hardware (LPU)
Open-source hub for ML models, datasets, and AI apps
Compare Together AI
How We Evaluate Tools
Our editorial team tests and reviews each tool based on features, pricing, ease of use, integration ecosystem, and real user feedback. Ratings reflect our independent assessment and are not influenced by affiliate partnerships. Learn more about our process.
Frequently Asked Questions
Is Together AI free?
Together AI is a paid tool. A free trial may be available. Pay-per-token. Llama 3.1 8B: $0.20/M tokens. Llama 3.1 70B: $0.90/M tokens. Mixtral 8x22B: $1.20/M tokens. $5 free credits for new accounts.
What are the best alternatives to Together AI?
The best alternatives to Together AI include Groq, Hugging Face. Each offers similar functionality with different strengths in features, pricing, and ease of use. Visit our alternatives page for detailed comparisons.
What is Together AI used for?
Fast, affordable inference for open-source AI models Common use cases include: Cost-effective LLM inference, Fine-tuning custom language models, Building AI chatbots and assistants, Batch processing text data, Replacing expensive proprietary APIs.