Lambda Labs Alternatives: Low-price A100 and H100 Options

TL;DR
If you like Lambda’s managed feel but want lower on-demand prices or simpler dev UX, start with Thunder Compute (A100 80 GB at $0.78 per hour, H100 at $1.47 per hour) and compare against Runpod, Crusoe, Voltage Park, Modal, Paperspace, and marketplace options like Vast.ai.

Quick picks

• Cheapest on-demand A100/H100: Thunder Compute (pricing page) – per-second billing, persistent storage, one-click VS Code integration.

• Large marketplace with consumer cards: Vast.ai (overview of GPU marketplace) – crowdsourced supply, many RTX 4090 options.

• Enterprise-y alternative with public rates: Crusoe (on-demand pricing FAQ).

• Low H100 headline price at scale: Voltage Park (pricing) – H100 from $1.99 per hour.

• Serverless and workflows: Modal (pricing) – per-second rates translate to ~$2.50/hr for A100, ~$3.95/hr for H100.

• Broad ecosystem and notebooks: Paperspace via DigitalOcean (pricing details) – H100 on-demand ~$5.95/hr; A100 also available.

Pricing snapshot (A100 and H100)

Rates are on-demand list prices where published. Some providers sell multi-GPU nodes; figures shown are per-GPU where the provider publishes per-GPU pricing.

Marketplace vs managed clouds (important if you need consumer GPUs)

Marketplaces can deliver the lowest cost, but host consistency varies.

• Vast.ai is a decentralized, peer-to-peer marketplace aggregating GPUs from both individuals and datacenters—including consumer-grade GPUs like RTX 4090—resulting in high supply variability and often lower prices.

• Runpod Community Cloud also lists consumer GPUs with transparent starting prices and community-provided capacity.

If consistent performance, multi-GPU NVLink, or enterprise networking matters, managed clouds (Thunder Compute, Lambda Labs, Crusoe, Voltage Park) are more predictable.

Why teams pick Thunder Compute

• Lowest on-demand A100/H100 rates in this comparison—A100 80 GB for $0.78/hr; H100 for $1.47/hr.

• Developer velocity—one-click VS Code, per-second billing, persistent disks, snapshots, dynamic vCPU/RAM adjustments.

• Simple pricing model—storage at $0.15/GB/month.
  See the Thunder Compute pricing page for up-to-date details.

How to choose

• For multi-GPU training with fast interconnect: opt for managed providers that explicitly publish SXM node specs and interconnect performance.

• For fast prototyping or fine-tuning: prioritize per-second billing, quick restart speeds, and persistent storage.

• To minimize cash burn: compare hourly A100 vs H100 costs—A100 often offers more cost-effective compute per token for prototyping models.

• If you need consumer GPUs: good for specific workloads like image generation or lightweight training, but verify VRAM, driver compatibility, and host stability.