Tool Introduction

Together AI is a research-driven platform that empowers organizations to build and deploy generative AI at scale. Founded by leading AI researchers and entrepreneurs, the company addresses the gap in accessible, customizable alternatives to proprietary systems. Together AI enables startups, enterprises, and research teams to train, fine-tune, and operate models using open-source technologies and scalable infrastructure. Its cloud-based suite supports every stage of the generative AI lifecycle: model training, fine-tuning, inference, and deployment. With an open approach to model development and strong community engagement through contributions of research and datasets, Together AI promotes transparency, flexibility, and ethical stewardship of AI.

Demo Available?

Together AI offers a free trial with $1 in credits across all models without requiring a credit card at signup time.

Tool's Accuracy

-

Aggregate Rating

4.3/5 stars (estimated from informal sources and limited reviews)

Detailed Overview

What Together AI Does

Together AI provides a cloud-based platform covering the full lifecycle of generative AI development. Users can train large models from scratch or fine-tune existing ones using high-performance GPUs like H100s. It supports parameter-efficient tuning methods such as LoRA. The service offers fast inference with optimized engines using techniques like quantization and speculative decoding. Models can be accessed via OpenAI-compatible APIs and deployed either in customer VPCs or on Together’s secure cloud. Users retain full model ownership.

Who Together AI is for

Developers use it to build applications like chatbots or content tools. Data scientists customize models for specific domains using orchestration features from Refuel.ai. Enterprises integrate scalable generative models into products while maintaining privacy controls. Research teams experiment with open-source LLMs to advance innovation.

Top Differentiators

Together AI emphasizes open-source transparency over closed platforms. Users retain model ownership with no vendor lock-in. Its optimized inference engine delivers fast performance at lower cost. The platform covers the full pipeline—from data ingestion through deployment—and includes enterprise-grade security like SOC 2/HIPAA compliance.

Introductory Video

Founding Year

2022

Target Industry

B2B, Enterprise, SMB, Technology, Financial Services, Healthcare, E-commerce, Media

Available Integrations

Vercel: Sync API token for seamless web app deployment using Together's inference API.
Vercel AI SDK: Combine SDK with OpenAI integration to prototype apps quickly using shared config settings.
Autogen Library (Python): Use agent-based workflows powered by Together's language backend for code generation tasks.
PyTorch/TensorFlow Frameworks: Directly integrate model deployment via native API compatibility.
MongoDB Atlas: Power retrieval augmented generation pipelines for personalized outputs via database access.
Cartesia Sonic Voice API: Add low-latency multi-language voice synthesis features into enterprise solutions.

Custom integrations are enabled through RESTful endpoints supporting automated workflows across third-party platforms.

Pay-as-you-go: Requires a minimum $5 credit to access the platform. No free trials or permanent free tier.
Serverless Inference: Charged per usage. FLUX.1 input at $0.0027 per million tokens, Google Imagen 4.0 Fast at $0.02 per image, Kling 1.6 Standard at $0.19 per video, Whisper Large v3 batch API at $0.0015 per audio minute, BGE-Base-EN v1.5 embeddings at $0.01 per million tokens.
Dedicated Deployments: Hourly pricing for hardware with performance guarantees: H200 141GB at $4.99, H100 80GB at $3.36, A100 SXM 40GB at $2.40. Includes autoscaling and support for custom models.
Fine-Tuning: Charged by tokens processed. LoRA up to 16B parameters at $0.48, full fine-tuning at $1.20, scaling to 70–100B: LoRA at $2.90 and full fine-tuning at $7.25 per million tokens; DeepSeek-V3 LoRA supervised costs $10 with a minimum of $20.
GPU Cloud: NVIDIA HGX H100 SXM hourly at $2.99 or long-term (1 week–3 months) use from $2.20 per hour; code execution charged at $0.0446 per vCPU hour or $0.03 per session.
Scale and Enterprise Plans: Include higher rate limits up to 9,000 requests/minute and 5 million tokens/minute plus discounts and added features like HIPAA

Pricing last verified: 01/23/2026
Official Source: https://www.together.ai/pricing
Disclaimer: Pricing is subject to change. Please confirm current pricing on the vendor site.

Features & Specs

Supported Models: LLMs and vision models from open-source libraries (e.g., Llama, Mistral).
Training Infrastructure: GB200/B200/H100 GPU clusters with shared or dedicated options.
Fine-Tuning Options: Full or parameter-efficient (LoRA) via API integration.
Inference Engine:
- Custom FP8 kernels (75%+ faster than base PyTorch)
- Quality-preserving quantization (QTIP)
- Speculative decoding for higher throughput
- Turbo/Reference/Lite modes balance speed vs cost vs accuracy
API Access: REST APIs compatible with OpenAI format.
Deployment Flexibility: Cloud-hosted or VPC-based deployments supported.
Privacy Controls: Local storage options or use of secure Together cloud.
Model Ownership: Retained by users after training/fine-tuning.
Data Orchestration Tools: Integrated via Refuel.ai acquisition.
User Management: SSO/SCIM support plus role-based access control (RBAC).

Security & Compliance

Together AI implements encryption at rest/in transit and offers role-based access control plus SSO/SCIM support for identity management. Data may be stored locally or within their secure cloud environment depending on user preference. The platform complies with SOC 2 standards as well as HIPAA regulations governing healthcare data handling.

Industry Use-Cases

Software & Technology

Together AI lets developers fine-tune LLMs on proprietary data then deploy them via API into apps, speeding feature delivery without heavy infrastructure setup.

Financial Services

Institutions automate compliance document analysis by fine-tuning LLMs internally, boosting risk assessment accuracy while reducing manual workload.

Healthcare

Healthcare providers extract structured insights from clinical notes using deidentified data, improving care quality while meeting HIPAA rules.

E-commerce & Retail

Retailers use Together’s inference tools to generate product descriptions at scale, cutting content costs while increasing personalization impact.

Media & Content Creation

Media firms automate blog writing by customizing LLMs with editorial styles, delivering more consistent output faster across channels.

Tool's Alternatives

Lambda Labs

Offers flexible GPU infrastructure with private deployments but lacks streamlined APIs found in Together’s ecosystem.

RunPod

Enables global GPU clouds including serverless containers but may involve more configuration complexity during prototyping stages.

Replicate

Ideal for deploying prebuilt community-contributed models quickly but limited in advanced customization features like full fine-tuning support.

Fal.ai

Specializes in serverless scaling for bursty workloads but doesn’t match the depth of customization offered by Together’s toolchain.

Vertex AI

Google’s managed ML suite integrates deeply with BigQuery but focuses less on open-source model usage than Together does.

Frequently Asked Questions

How does model ownership work on Together AI?

You keep full rights over any model you train or fine-tune on the platform, including those built from open-source bases, with no vendor lock-in applied afterward.

Can I deploy my trained models outside of Together’s infrastructure?

Yes, you can host your models inside your own virtual private cloud (VPC) instead of relying solely on their managed services if privacy matters most to you.

Does Together offer OpenAI-compatible APIs?

Yes, their endpoints are fully compatible which makes switching easier if you've already built apps around OpenAI specifications or SDK patterns.

What GPUs are supported for training/inference?

High-performance GPUs include GB200s/B200s/H100s among others, with pricing varying between $1–$5/hour depending on configuration type selected per session needs.

Is there a free trial available?

Yes, a free Build Tier includes initial credits ($1 worth), high request limits (6k RPM), generous token allowances, and requires no credit card upfront during sign-up phase.

Which industries benefit most from this platform?

Industries like tech/devops teams needing rapid prototypes benefit alongside finance firms focused on compliance automation, and healthcare groups managing sensitive records securely under HIPAA rulesets too.

What kind of customizations are possible during fine-tuning?

You can choose between full-scale retraining methods or lighter-weight approaches such as LoRA, to fit different dataset sizes or latency preferences when adapting base models toward unique tasks/goals onsite.

*Does the system support RAG workflows?*

Yes, with MongoDB Atlas integration you can build real-time retrieval pipelines that enhance response personalization inside apps handling live customer queries/data feeds directly connected through indexed sources online/offline alike.

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Together AI

Open, Scalable Generative AI for Developers and Enterprises