Together AI Pricing in May 2026

Together AI's pricing operates on usage-based tiers for different model types: Llama 3.1 70B at $0.88/1M tokens (input or output), Llama 3.1 8B at $0.20/1M tokens, Mixtral 8x22B at $1.20/1M tokens, dedicated GPU endpoints at $1.20-3.50/hour depending on chip. Real-world Together AI bills for AI products built on open-weight models land at $200-1,500/month for early-stage; high-volume products doing fine-tuning and dedicated inference hit $5K-50K/month at scale. The pricing model is dramatically cheaper than OpenAI or Anthropic for equivalent token volume — typically 50-80% lower for similar quality.

The $1,000 startup credit covers 4-15 months of moderate Together AI usage for AI products. Eligibility focuses on AI-native startups and accelerator-backed companies building on open-weight models. The credit applies to all Together services including inference, fine-tuning, and dedicated GPU endpoints. The strategic decision: Together AI vs Fireworks vs Groq is the active comparison for hosted open-weight inference. Groq wins on raw latency (3-5x faster inference for many workloads); Fireworks competes on similar pricing with strong developer experience; Together AI wins on model breadth and fine-tuning support. For products where token cost dominates (high-volume RAG, agentic workflows), open-weight via Together AI typically beats GPT-4 by 5-10x on cost. The credit window is the right time to validate whether your specific quality requirements work with Llama or Mixtral — for reasoning-heavy tasks, frontier closed models still win, but for standard chat and content generation, open-weight quality is genuinely competitive at much lower cost.