Together AI is a cloud-native platform focused on open-source large language models (LLMs). Designed to support organizations and developers who want more control over their AI infrastructure, Together AI allows teams to train, fine-tune, and serve LLMs at scale—without relying exclusively on closed platforms like OpenAI or Anthropic.
Together AI combines the performance of proprietary systems with the freedom of open-source models, enabling businesses to own their models, control their data, and customize LLMs for specific use cases, all while benefiting from a scalable, optimized backend. With strong community ties and enterprise-level capabilities, Together AI is fast becoming the go-to solution for businesses seeking AI independence.
Features of Together AI
Hosted Inference APIs for Open-Source Models
Serve top-tier open models like Meta’s Llama 2, Mistral, and Mixtral, with APIs that offer high availability, low latency, and performance comparable to closed alternatives.
Model Fine-Tuning Infrastructure
Together AI allows users to fine-tune models using their proprietary or domain-specific datasets via APIs or custom pipelines. Ideal for creating vertical-specific LLMs.
Open-Source Optimized Stack
Built to work seamlessly with models from Hugging Face, EleutherAI, Meta, Mistral, and other open communities. Provides a secure alternative to proprietary cloud APIs.
Inference-Optimized Clusters
Together AI uses custom-built infrastructure optimized for LLM inference, ensuring cost-effective scalability across multiple GPUs and nodes.
Collaborative Notebooks and Templates
Pre-built examples, notebooks, and tools help teams get started with training, inference, and evaluation faster—ideal for ML engineers and data scientists.
Enterprise-Grade Deployment
SLAs, dedicated clusters, data privacy guarantees, and auditability make Together AI suitable for healthcare, finance, and government sectors.
Model Evaluation and Benchmarking Tools
Use Together AI’s tools to compare different open-source models on various tasks, including summarization, reasoning, coding, and chat.
Fine-Tuning as a Service (FTaaS)
Offers professional services and infrastructure to help organizations fine-tune and maintain custom models at scale, even without in-house ML ops.
How Together AI Works
Select a Model or Bring Your Own
Choose from open-source models like Llama 2, Mixtral, Mistral, or upload your own model to deploy and serve.Train or Fine-Tune
Upload your data and configure fine-tuning parameters. Together AI provides GPU infrastructure and optimized workflows for efficient model customization.Deploy via API
Serve your model with Together AI’s inference-optimized APIs. Easily integrate into products, websites, or back-end services.Evaluate and Optimize
Use built-in benchmarking tools or plug in your evaluation framework to monitor model performance across tasks and use cases.Scale with Demand
Whether you’re deploying a single use case or building an enterprise-level AI system, Together AI scales with your workload using multi-node GPU clusters.
Use Cases for Together AI
AI Product Development
Startups and product teams can quickly deploy and scale custom LLMs for chatbots, assistants, and workflow automation.
Enterprise Knowledge Management
Fine-tune models on internal documentation, CRM data, or legal texts to power smarter enterprise search and summarization tools.
Healthcare and Life Sciences
Create HIPAA-compliant, domain-specific models for diagnosis support, clinical research, and patient interaction.
Financial Services
Deploy secure LLMs for compliance automation, sentiment analysis, and financial document summarization without exposing sensitive data.
Education and Research
Universities and labs can test and benchmark multiple open-source models without incurring massive cloud costs or relying on black-box APIs.
Government and Defense
Deploy trusted, transparent models for mission-critical systems while meeting strict data governance requirements.
Pricing of Together AI
As of June 2025, Together AI offers flexible, usage-based pricing for its APIs and infrastructure. While specific pricing details vary by model and compute demand, here is a general breakdown:
Pay-as-You-Go API Access
Charged per 1,000 tokens, with pricing based on the model’s size and complexity (e.g., Llama 2 vs. Mixtral).Fine-Tuning Services
Custom quotes provided based on dataset size, model architecture, and GPU hours required. Includes optional MLOps support.Enterprise Plans
Tailored for large-scale use cases. Includes:Dedicated GPU clusters
Priority support
Custom security protocols
SLAs and uptime guarantees
Pricing details are not fully listed publicly, so interested teams should contact Together AI for a personalized demo and quote at https://www.together.ai.
Strengths of Together AI
Empowers users with full control over LLMs and their data
Supports leading open-source models with enterprise-grade performance
Scalable, low-latency inference APIs with flexible deployment
Fine-tuning infrastructure eliminates complex ML operations
Transparent and audit-ready—ideal for regulated industries
Active participation in the open-source community
Great for startups, enterprises, and public sector organizations alike
Drawbacks of Together AI
Requires some technical know-how to fully leverage advanced features
May not match all capabilities of proprietary models like GPT-4 in terms of general reasoning
Custom fine-tuning and enterprise deployments require direct engagement
Not a no-code platform—built for developers and ML engineers
Lacks pre-built turnkey solutions for end users; best suited as infrastructure
Comparison with Other Tools
Together AI vs. OpenAI
OpenAI provides powerful proprietary models, but lacks customization and data control. Together AI enables users to fine-tune and host open-source models for more flexibility.
Together AI vs. Hugging Face Inference Endpoints
Hugging Face offers similar API access to open models. Together AI focuses more on high-performance, enterprise-scale deployment and fine-tuning infrastructure.
Together AI vs. AWS Bedrock
Bedrock supports proprietary and foundation models, but Together AI gives deeper control and more direct customization via open-source stack.
Together AI vs. Google Vertex AI
Vertex AI integrates with Google’s cloud ecosystem but can be more complex and costly. Together AI is optimized specifically for open-source LLMs.
Customer Reviews and Testimonials
Together AI has quickly earned a reputation among developers and AI-focused companies:
“Together gave us the tools to fine-tune an open-source model for our legal platform. It performs better than GPT-3.5 and keeps all data private.” – CTO, LegalTech Startup
“We needed transparency, cost-efficiency, and speed. Together delivered on all fronts.” – AI Infrastructure Lead, Enterprise SaaS Company
“Instead of relying on closed APIs, we now control and deploy our own models, and our margins improved by 40%.” – Head of Engineering, HealthTech Firm
The platform is also active in the open-source community and widely recognized for its contributions to model hosting and democratized AI infrastructure.
Conclusion
Together AI is building the foundation for a more open, customizable, and scalable AI ecosystem. Whether you’re a startup experimenting with open-source models or an enterprise deploying mission-critical AI systems, Together AI gives you the tools to train, tune, serve, and scale LLMs on your terms.
As AI adoption accelerates across industries, Together AI offers a compelling path toward model sovereignty, transparency, and control—without sacrificing performance.
