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Shadeform vs Together AI: Pricing, Specs, Strengths & Weaknesses

Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for Shadeform and Together AI. Rates sourced from public APIs — verify current availability and billing terms before purchasing.

Overview

Provider type
Marketplace
Specialist
Founded
2023
2022
Headquarters
San Francisco, CA
San Francisco, CA
Billing model
On-demand, Spot
Per-token (inference), On-demand / Reserved (GPU cloud)
Min commitment
None
None
Support tier
Community → Enterprise
Community → Enterprise
Regions
4 regions
2 regions

Strengths & Best For

Shadeform

Shadeform is a GPU cloud aggregator that provisions H100, A100, RTX 4090, and many other GPU types across 30+ underlying cloud providers through a single unified API, automatically routing to the cheapest available instance matching your requirements. On-demand and spot GPU rental options are surfaced from the entire provider network, giving teams multi-cloud flexibility without managing multiple accounts. A fast way to find and launch low-cost GPUs for AI training or inference workloads.

Strengths
  • 30+ provider network via single API
  • Automatic cheapest-price routing
  • Wide GPU selection across providers
  • Multi-cloud flexibility without multiple accounts
Weaknesses
  • Aggregator — pricing and availability depends on underlying providers
  • No direct infrastructure control
  • Limited enterprise features
Best For
Teams wanting multi-cloud GPU flexibilityCost-optimized GPU provisioningSpot-tolerant workloads needing lowest price
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Together AI

Together AI is a full-stack AI platform combining a high-throughput inference API (200+ open-source models), dedicated GPU clusters (H100 SXM, A100), and a managed fine-tuning service. Together MoE optimization cuts costs on large mixture-of-experts models. Function calling and JSON mode across all major models. Fine-tuning: LoRA and full fine-tune for Llama, Mistral, and Qwen. GPU cloud: H100 SXM and A100 clusters for large-scale training. Check api.together.ai/models for current per-token rates.

Strengths
  • 200+ open-source models — wide inference API catalog
  • Llama 4 Scout — competitive frontier-open pricing
  • Together MoE optimization reduces cost on large MoE models
  • Managed fine-tuning: LoRA and full fine-tune for Llama, Mistral, Qwen
  • Function calling and JSON mode across all major models
  • GPU cloud + inference API from one vendor
Weaknesses
  • GPU cloud side less polished than pure-play providers like CoreWeave
  • Inference API latency trails Fireworks and Cerebras on speed benchmarks
  • Enterprise SLAs require custom contracts — not self-serve
Best For
Teams wanting inference API + GPU training from one vendorFine-tuning Llama, Mistral, or Qwen at scaleCost-conscious teams replacing OpenAI with open-source modelsResearchers needing broad model access without self-hosting
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Key differences

Shadeform

GPU cloud aggregator — launch GPUs across 30+ providers via one API

Together AI

Full-stack AI platform — 200+ models, GPU cloud, fine-tuning, and Together MoE optimization

AttributeShadeformTogether AI
Provider typemarketplacespecialist
Billing modelOn-demand, SpotPer-token (inference), On-demand / Reserved (GPU cloud)
Min commitmentNoneNone
Regions4 (US, EU, APAC, +1)2 (US-East, US-West)
Support tierCommunity → EnterpriseCommunity → Enterprise
Best forTeams wanting multi-cloud GPU flexibility, Cost-optimized GPU provisioningTeams wanting inference API + GPU training from one vendor, Fine-tuning Llama, Mistral, or Qwen at scale
Founded / HQ2023 · San Francisco, CA2022 · San Francisco, CA