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Database Mart vs Together AI: Pricing, Specs, Strengths & Weaknesses

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

Overview

Provider type
Bare-metal
Specialist
Founded
2015
2022
Headquarters
United States
San Francisco, CA
Billing model
Monthly / On-demand
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

Database Mart

Database Mart provides dedicated bare-metal H100, A100, and RTX GPU servers alongside cloud instances for AI, ML, and HPC workloads, with no virtualization overhead for maximum hardware performance. Monthly and on-demand billing options are available, making it suitable for both long-running training jobs and shorter inference workloads that need dedicated GPU hardware. A practical bare-metal GPU option for teams that need consistent, dedicated performance without shared-tenancy concerns.

Strengths
  • Dedicated hardware
  • Flexible configurations
  • Competitive pricing
Weaknesses
  • Bare-metal only — requires more infrastructure management
  • Limited ML tooling vs managed cloud services
  • Smaller ecosystem and fewer integrations
Best For
Dedicated GPU workloadsLong-running trainingHPC
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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

Database Mart

Dedicated GPU servers

Together AI

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

AttributeDatabase MartTogether AI
Provider typebare-metalspecialist
Billing modelMonthly / On-demandPer-token (inference), On-demand / Reserved (GPU cloud)
Min commitmentNoneNone
Regions1 (US)2 (US-East, US-West)
Support tierStandardCommunity → Enterprise
Best forDedicated GPU workloads, Long-running trainingTeams wanting inference API + GPU training from one vendor, Fine-tuning Llama, Mistral, or Qwen at scale
Founded / HQ2015 · United States2022 · San Francisco, CA