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← Back to Together AI Overview

Together AI Pricing & Plans 2026

Complete pricing guide for Together AI. Compare all plans, analyze costs, and find the perfect tier for your needs.

Try Together AI Free →Compare Plans ↓

Not sure if free is enough? See our Free vs Paid comparison →
Still deciding? Read our full verdict on whether Together AI is worth it →

🆓Free Tier Available
💎4 Paid Plans
⚡No Setup Fees

Choose Your Plan

Serverless inference

Per-million-token pricing per model (open models from sub-$0.20/M input typical)

mo

    Start Free Trial →

    Dedicated endpoints

    Per-hour GPU pricing for pinned model deployments

    mo

      Start Free Trial →
      Most Popular

      GPU Clusters / Instant Clusters

      Reserved H100/H200/B200/GB200 capacity, hourly and contracted

      mo

        Start Free Trial →

        Enterprise

        Custom

        mo

          Contact Sales →

          Pricing sourced from Together AI · Last verified March 2026

          Feature Comparison

          Detailed feature comparison coming soon. Visit Together AI's website for complete plan details.

          View Full Features →

          Is Together AI Worth It?

          ✅ Why Choose Together AI

          • • Breadth of open-weight model catalog (200+) with one OpenAI-compatible API
          • • One account spans serverless, dedicated endpoints, fine-tuning, and reserved GPU capacity
          • • Transparent per-token pricing — easy to model unit economics against closed providers
          • • InfiniBand-backed GPU Clusters are credible for real training, not just inference

          ⚠️ Consider This

          • • Frontier-class reasoning still lags closed models on the hardest benchmarks
          • • Fastest single-model latency is sometimes beaten by Groq or Cerebras
          • • Many model variants means model selection itself becomes a project
          • • Dedicated endpoint cost calculations require attention to GPU type and utilization

          What Users Say About Together AI

          👍 What Users Love

          • ✓Breadth of open-weight model catalog (200+) with one OpenAI-compatible API
          • ✓One account spans serverless, dedicated endpoints, fine-tuning, and reserved GPU capacity
          • ✓Transparent per-token pricing — easy to model unit economics against closed providers
          • ✓InfiniBand-backed GPU Clusters are credible for real training, not just inference

          👎 Common Concerns

          • ⚠Frontier-class reasoning still lags closed models on the hardest benchmarks
          • ⚠Fastest single-model latency is sometimes beaten by Groq or Cerebras
          • ⚠Many model variants means model selection itself becomes a project
          • ⚠Dedicated endpoint cost calculations require attention to GPU type and utilization

          Pricing FAQ

          How does Together AI compare to using OpenAI's API directly?

          Together AI provides access to open-source models (Llama, Mistral, DeepSeek) through an OpenAI-compatible API. Key advantages include 5-20x lower costs per token, faster inference speeds through custom optimizations, and access to specialized models. The tradeoff is that even the best open-source models may lag behind GPT-4 on complex reasoning tasks, though the gap is rapidly narrowing with models like Llama 3.3 and DeepSeek-V3.

          Does Together AI support function calling for AI agents?

          Yes, Together AI implements OpenAI-compatible function calling across supported models including Llama, Mistral, and other major families. The implementation uses the same tools/function_call API format, so existing agent code using OpenAI SDK works with minimal changes. Function calling quality varies by model size - larger models (70B+) generally produce more reliable tool calls than smaller ones.

          Can I fine-tune models on Together AI for my specific use case?

          Yes, Together AI provides comprehensive fine-tuning capabilities for customizing open-source models on your data. You can fine-tune Llama, Mistral, and other supported base models using instruction tuning, domain adaptation, or full fine-tuning. The platform supports advanced techniques like LoRA and QLoRA for efficient training. Fine-tuned models are automatically deployed for inference through the same API with usage-based pricing.

          What are dedicated endpoints and when should I use them?

          Dedicated endpoints provide reserved GPU capacity with guaranteed performance and sub-100ms latency SLAs. They're ideal for production applications requiring consistent performance, high-volume workloads, or custom model hosting. Unlike serverless inference which shares resources, dedicated endpoints give you isolated infrastructure. Pricing is based on hourly GPU reservations rather than per-token usage.

          How reliable is Together AI for production workloads?

          Together AI offers 99.9% uptime SLA on dedicated endpoints and maintains high availability on serverless infrastructure. The platform is SOC 2 Type II certified with enterprise security features. For mission-critical applications, dedicated endpoints provide the most reliable option with guaranteed capacity and consistent performance. Enterprise plans include priority support and custom SLAs.

          Ready to Get Started?

          AI builders and operators use Together AI to streamline their workflow.

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          More about Together AI

          ReviewAlternativesFree vs PaidPros & ConsWorth It?Tutorial

          Compare Together AI Pricing with Alternatives

          Fireworks AI Pricing

          Production inference platform for open-weight LLMs, multimodal models, and custom fine-tunes — known for very fast serving (FireAttention/FireOptimizer), reliable function calling, and JSON mode at low per-token prices.

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          Groq Pricing

          AI inference cloud built on Groq's own LPU (Language Processing Unit) chips that serves open-weight LLMs, Whisper, and vision models at the lowest latency in the market, with an OpenAI-compatible API.

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          Replicate Pricing

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          Anyscale Pricing

          Anyscale is the managed Ray platform from the original creators of Ray, providing production-scale infrastructure for distributed AI workloads — model training, batch inference, RAG pipelines, agent orchestration, and reinforcement learning — running on any cloud with autoscaling GPU and CPU clusters.

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