Together AI — Best Coding & Development AI Tool (April 2026)

About Together AI

Together AI — Together AI is an AI Acceleration Cloud providing an end-to-end platform for the full generative AI lifecycle. It offers fast inference, fine-tuning, and training capabilities for generative AI models using easy-to-use APIs and highly scalable infrastructure. Users can run and fine-tune open-source models, train and deploy models at scale on their AI Acceleration Cloud and scalable GPU clusters, and optimize performance and cost. The platform supports over 200 generative AI models across various modalities like chat, images, code, and more, with OpenAI-compatible APIs.

Top use cases

Accelerating AI model training and inference for enterprises (e.g., Salesforce, Zoom, InVideo)
Building AI customer support bots that scale to high message volumes (e.g., Zomato)
Developing production-grade AI applications by unlocking data for developers and businesses
Creating next-generation text-to-video models (e.g., Pika)
Building cybersecurity models (e.g., Nexusflow)
Achieving simpler operations, improved latency, and greater cost-efficiency for AI models (e.g., Arcee AI)
Developing custom generative AI models from scratch
Performing multi-document analysis, codebase reasoning, and personalized tasks
Managing complex tool-based interactions and API function calls
Generating and debugging code with advanced LLMs
Executing visual tasks with advanced visual reasoning and video understanding
Data tasks such as classification and structured data extraction

Built for

AI DevelopersAI ResearchersMachine Learning EngineersData ScientistsEnterprises building AI applicationsStartups leveraging generative AICompanies focused on open-source AIOrganizations requiring scalable GPU infrastructure

Key features

Serverless Inference API for open-source models
Dedicated Endpoints for custom hardware deployment
Fine-Tuning (LoRA and full fine-tuning)
Together Chat app for open-source AI
Code Sandbox for AI development environments
Code Interpreter for executing LLM-generated code
GPU Clusters (Instant and Reserved) with NVIDIA GPUs (GB200, B200, H200, H100, A100)
Extensive Model Library (200+ generative AI models)
OpenAI-compatible APIs
Accelerated Software Stack (e.g., FlashAttention-3, custom CUDA kernels)
High-Speed Interconnects (InfiniBand, NVLink)
Robust Management Tools (Slurm, Kubernetes)

Pros & cons

Pros

Offers fast inference, fine-tuning, and training for generative AI models.
Provides highly scalable infrastructure with top-tier NVIDIA GPUs.
Optimizes performance and cost, claiming significantly lower costs than competitors for inference.
Features easy-to-use, OpenAI-compatible APIs for seamless integration.
Grants full model ownership and control over intellectual property, avoiding vendor lock-in.
Integrates cutting-edge AI research and optimizations (e.g., FlashAttention-3, custom kernels).
Supports a vast library of over 200 open-source and specialized generative AI models.
Ensures high reliability with a 99.9% uptime SLA for GPU clusters.
Compliant with SOC 2 and HIPAA standards for secure enterprise deployments.
Offers batch inference with an introductory 50% discount.

Cons

Pricing for NVIDIA GB200 and B200 GPUs, and custom large-scale deployments, requires direct contact, lacking immediate transparency.
Leveraging advanced features like fine-tuning hyperparameters and custom deployments may require significant technical expertise.

Pricing

Serverless Inference

$0.06

Prices are per 1 million tokens (input and output for Chat, Multimodal, Language, Code; input only for Embedding; image size/steps for Image models). Batch inference is available at an introductory 50% discount. Specific model prices range from $0.06 to $7.00 per 1M tokens dep…

Dedicated Endpoints

$0.025

Deploy models on customizable GPU endpoints with per-minute billing. Supports various NVIDIA GPUs like RTX-6000, L40, A100, H100, H200. Prices range from $0.025/minute ($1.49/hour) for RTX-6000/L40 to $0.083/minute ($4.99/hour) for H200.

Fine-tuning

$0.48

Pricing is based on model size, dataset size, and number of epochs. Supervised Fine-tuning (LoRA) ranges from $0.48 to $2.90 per 1M tokens. Full Fine-tuning ranges from $0.54 to $3.20 per 1M tokens. DPO (LoRA) ranges from $1.20 to $7.25 per 1M tokens. DPO (Full FT) ranges from…

Together GPU Clusters

$1.30

State-of-the-art clusters with NVIDIA Blackwell and Hopper GPUs (H200, H100, A100) for optimal AI training and inference. H200 starts at $2.09/hr, H100 at $1.75/hr, A100 at $1.30/hr. GB200 and B200 pricing requires contact.

Code Execution

$0.0446

Together Code Sandbox is priced per vCPU ($0.0446/hour) and per GiB RAM ($0.0149/hour). Together Code Interpreter is priced per session ($0.03 for 60 minutes).

Frequently asked questions

What types of AI models does Together AI support?

Together AI supports over 200 generative AI models, including Chat, Multimodal, Language, Image, Code, and Embedding models, with a strong focus on open-source options.

What GPU hardware is available on Together AI?

Together AI offers state-of-the-art NVIDIA GPUs, including GB200, B200, H200, H100, A100, L40, and L40S, for both inference and training workloads.

How does Together AI optimize performance and cost?

Together AI optimizes performance and cost through custom transformer-optimized kernels (e.g., FP8 inference kernels, FlashAttention-3), quality-preserving quantization (QTIP), speculative decoding, and competitive pricing models.

Can I fine-tune my own models on Together AI?

Yes, Together AI provides comprehensive fine-tuning capabilities, including LoRA and full fine-tuning, allowing users to train and improve high-quality models with complete model ownership and no vendor lock-in.

Is Together AI suitable for enterprise use?

Yes, Together AI offers secure, reliable AI infrastructure, SOC 2 and HIPAA compliance, dedicated endpoints, and expert AI advisory services, making it suitable for enterprise-scale deployments.

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