The Cheapest GPU Cloud Providers for AI Inference in 2026

GPU inference costs have dropped dramatically since 2023. H100 spot rates are now available from $1.89/hr on marketplaces like RunPod and Vast.ai — down from $8+/hr in early 2023. RTX 4090 instances start at $0.35/hr. For most production inference workloads, the cheapest option depends on your model size, latency requirements, and tolerance for spot interruptions.

This guide ranks the most cost-effective GPU cloud providers for AI inference in 2026, accounting for on-demand rates, spot availability, per-second billing, and hidden costs like egress fees. See the live GPU price comparison table for current rates across all providers.

RunPod and Vast.ai consistently offer the lowest spot GPU rates. RunPod community cloud RTX 4090 starts at $0.34/hr; H100 80GB spot from $1.89/hr. Vast.ai's marketplace model means prices fluctuate with supply — RTX 3090 from $0.15/hr, H100 from $1.60/hr. Both use per-second billing with no minimum commitment.

Salad Cloud offers the lowest absolute rates for inference via its distributed GPU network — RTX 4090 from $0.12/hr — but with higher latency variance and less predictable availability. Best for batch inference workloads that tolerate variable performance. Read our guide on spot vs on-demand GPU pricing to understand the trade-offs.

Lambda Labs, Fluidstack, and TensorDock offer a middle ground — lower rates than hyperscalers with better reliability than pure marketplaces. Lambda Labs H100 on-demand: $2.49/hr (one of the lowest fixed rates). Fluidstack offers H100 from $2.29/hr with per-minute billing. TensorDock provides RTX 4090 from $0.44/hr with per-second billing.

CoreWeave is the premium specialist option — H100 from $2.89/hr on-demand, but with enterprise SLAs, dedicated networking, and the best multi-GPU cluster support outside hyperscalers. Worth the premium for production workloads requiring guaranteed availability. Compare CoreWeave vs Lambda Labs pricing side-by-side.

AWS, Google Cloud, and Azure are rarely the cheapest option for pure inference compute, but they make sense when: (1) you need tight integration with other cloud services (S3, BigQuery, Azure OpenAI); (2) compliance requirements mandate a specific cloud; (3) you're using reserved instances with 1–3 year commitments, which can reduce H100 costs by 40–60%.

Google Cloud's sustained use discounts automatically apply after 25% monthly usage, effectively reducing on-demand rates by up to 30% for always-on inference services. Track 90-day GPU price history to see how hyperscaler rates compare over time.

Egress fees are the most commonly overlooked cost. AWS charges $0.09/GB for data transfer out; Google Cloud $0.08/GB; Azure $0.087/GB. For inference APIs serving large responses (images, audio, long text), egress can add 20–40% to your total compute bill. Providers like Lambda Labs and CoreWeave have lower or no egress fees for most use cases.

Storage costs also add up — GPU instances with attached NVMe storage charge $0.10–$0.20/GB/month. For inference, minimize persistent storage by loading models from object storage at startup rather than keeping them on attached volumes. If you're evaluating managed LLM APIs as an alternative, see live LLM inference prices to compare cost-per-token across 33+ providers.