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

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

Overview

Provider type
Marketplace
Specialist
Founded
2022
2022
Headquarters
United States
San Francisco, CA
Billing model
On-demand (per-minute), Spot, Reserved
Per-token (inference), On-demand / Reserved (GPU cloud)
Min commitment
20-minute minimum runtime
None
Support tier
Community → Standard
Community → Enterprise
Regions
3 regions
2 regions

Strengths & Best For

Spheron

Spheron is a GPU marketplace sourcing from certified data center partners globally. GPU catalog: B300 Blackwell, B200 Blackwell, H200, H100, MI300X, GH200, A100, RTX PRO 6000, RTX 5090, L40S, RTX 4090 — on-demand and spot. GB200 and GB300 available to reserve. NVIDIA R100 Rubin (288 GB HBM4) pre-order. Per-minute billing, 20-minute minimum. Accepts USDT/USDC.

Strengths
  • B300, H100, RTX 4090 — competitive live pricing
  • Spot pricing available on H200, H100, A100
  • MI300X — AMD high-VRAM option
  • NVIDIA R100 Rubin pre-order available
  • Per-minute billing, 20-minute minimum, no contracts
  • Accepts USDT and USDC crypto payments
Weaknesses
  • Marketplace model — hardware consistency varies by partner
  • 20-minute minimum runtime (not per-second)
  • No enterprise SLAs
Best For
Cost-sensitive AI workloads needing multi-provider flexibilityTeams wanting vetted marketplace GPU accessSpot-tolerant batch training and inferenceCrypto-native teams
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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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Live GPU Pricing

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Region Coverage

Popular Comparisons

Key differences

Spheron

B300, H100, B200, H200 — per-minute billing, 20-min minimum

Together AI

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

AttributeSpheronTogether AI
Provider typemarketplacespecialist
Billing modelOn-demand (per-minute), Spot, ReservedPer-token (inference), On-demand / Reserved (GPU cloud)
Min commitment20-minute minimum runtimeNone
Regions3 (US, EU, APAC)2 (US-East, US-West)
Support tierCommunity → StandardCommunity → Enterprise
Best forCost-sensitive AI workloads needing multi-provider flexibility, Teams wanting vetted marketplace GPU accessTeams wanting inference API + GPU training from one vendor, Fine-tuning Llama, Mistral, or Qwen at scale
Founded / HQ2022 · United States2022 · San Francisco, CA