📖 The AI Tool Bible

Lambda vs Together AI

A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.

 
Lambda
Fine-tuning
Together AI
Fine-tuning
TaglineOn-demand NVIDIA GPU cloud built specifically for training, fine-tuning, and serving large AI models.Fine-tune & serve open-weight models (Llama, Mistral, DeepSeek).
CategoryFine-tuningFine-tuning
PricingPaid· Pay-by-the-minute: A100 from $1.29/hr, H100 SXM from $3.99/hr, B200 from $6.69/hr; clusters priced by quotePaid· Pay-per-token; fine-tuning per-token
Model—Llama / Mistral / Qwen / DeepSeek and others
Editorial score—8.6 / 10
Use cases
llm-trainingfine-tuninggpu-rentalmodel-inferencedistributed-training
open modelsfine-tuninginference
Pros
  • Substantially cheaper H100/A100/B200 hours than AWS, GCP or Azure
  • Per-minute billing with no egress fees
  • Pre-installed Lambda Stack means instances are training-ready in minutes
  • Offers both single on-demand GPUs and full multi-thousand-GPU clusters
  • SOC 2 Type II with single-tenant hardware isolation on clusters
  • Wide open-model catalogue
  • Competitive inference pricing
  • Fine-tune + serve in one place
  • Dedicated endpoints for production
Cons
  • Popular GPUs (H100, B200) are frequently sold out
  • No managed fine-tuning-as-a-service API - you run your own training stack
  • Fewer managed services and regions than AWS/GCP/Azure
  • Latency varies by model
  • Less polish than OpenAI
Websitelambdalabs.comwww.together.ai
Pick Lambda if
  • ✅ Substantially cheaper H100/A100/B200 hours than AWS, GCP or Azure
  • ✅ Per-minute billing with no egress fees
  • ✅ Pre-installed Lambda Stack means instances are training-ready in minutes
  • ✅ Offers both single on-demand GPUs and full multi-thousand-GPU clusters
Pick Together AI if
  • ✅ Wide open-model catalogue
  • ✅ Competitive inference pricing
  • ✅ Fine-tune + serve in one place
  • ✅ Dedicated endpoints for production
Compare a different pair →