Baseten vs Together AI

Side-by-side comparison of Baseten and Together AI: pricing, features, API access, and community ratings.

AI comparison summary

TL;DR: Both platforms prioritize speed, but Baseten emphasizes production reliability with 99.99% uptime SLAs, hands-on engineering support, and multi-cloud/self-hosted flexibility, while Together AI offers a more comprehensive full-stack experience including compute infrastructure, fine-tuning, and research innovations at lower costs. Together AI provides a free tier for experimentation, whereas Baseten is paid-only but positions itself for enterprise deployments requiring white-glove support. Choose Baseten for mission-critical applications needing guaranteed uptime and dedicated support, or Together AI for broader experimentation and cost optimization across the entire ML lifecycle.

Baseten
Baseten

The fastest AI model inference platform for production-grade deployments

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Together AI
Together AI

The AI Native Cloud — full-stack platform for inference, compute, and model shaping

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Category
AI infrastructure
AI infrastructure
Pricing
Paid
Freemium
Starting price
Free tier
Audience
Technical
Technical
API available
Open source
Self-hostable
Model provider
Open-source models (e.g., DeepSeek, Gemma, Llama, Qwen, GLM, MiniMax, Kimi)
Founded
2019
2022
Headquarters
San Francisco, USA
San Francisco, USA
Key strengths
  • ·Blazing-fast inference with custom kernels and advanced caching via the Baseten Inference Stack
  • ·Multi-cloud and self-hosted deployment options with 99.99% uptime SLA
  • ·Purpose-built optimizations for LLMs, image generation, transcription, TTS, and embeddings
  • ·Ultra-low-latency compound AI with Baseten Chains for granular GPU and autoscaling control
  • ·Industry-leading inference speed (31%+ more TPS than next-fastest OSS engine)
  • ·Full-stack platform: inference, compute, fine-tuning, storage, and sandboxes
  • ·Cutting-edge in-house research (FlashAttention, ThunderKittens, ATLAS)
  • ·Broad open-source model library with serverless and dedicated deployment options