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

Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for GPUniq 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
Various
San Francisco, CA
Billing model
Per-second (marketplace)
Per-token (inference), On-demand / Reserved (GPU cloud)
Min commitment
None
None
Support tier
Standard
Community → Enterprise
Regions
1 regions
2 regions

Strengths & Best For

GPUniq

GPUniq is a live GPU marketplace offering a wide range of hardware including NVIDIA B200 192GB, H200 141GB, H100 80GB, A100 80GB, and RTX 4090 with per-second billing. Prices are dynamic and set by marketplace supply and demand — observed minimums range from $0.48/hr (A100) to $9.42/hr (B200). The marketplace model means pricing can be significantly below fixed-rate providers during low-demand periods. A strong option for teams that want access to next-generation hardware (B200, H200) at marketplace rates.

Strengths
  • B200 192GB and H200 141GB availability
  • Per-second billing — pay only for what you use
  • Dynamic marketplace pricing — can be well below fixed rates
  • Wide GPU catalog from RTX 4090 to B200
Weaknesses
  • Marketplace model — prices and availability fluctuate
  • No guaranteed availability for specific GPU models
  • Newer provider — limited public track record
Best For
Teams wanting B200 or H200 at marketplace ratesCost-sensitive workloads with flexible schedulingShort-burst GPU jobs benefiting from per-second billing
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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

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Key differences

GPUniq

GPU marketplace — B200, H200, H100, A100, RTX 4090 with per-second billing

Together AI

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

AttributeGPUniqTogether AI
Provider typemarketplacespecialist
Billing modelPer-second (marketplace)Per-token (inference), On-demand / Reserved (GPU cloud)
Min commitmentNoneNone
Regions1 (Various)2 (US-East, US-West)
Support tierStandardCommunity → Enterprise
Best forTeams wanting B200 or H200 at marketplace rates, Cost-sensitive workloads with flexible schedulingTeams wanting inference API + GPU training from one vendor, Fine-tuning Llama, Mistral, or Qwen at scale
Founded / HQ2023 · Various2022 · San Francisco, CA