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Inference comparison

NVIDIA DGX Cloud Lepton vs Modal

GPU marketplace against serverless gpu. Editorial fit scores help shortlist; live pricing stays on the provider sites.

NVIDIA DGX Cloud Lepton product facts checked October 2, 2026NVIDIA DGX Cloud Lepton editorial scores reviewed September 3, 2026Modal product facts checked October 2, 2026Modal editorial scores reviewed September 3, 2026

GPU marketplace

NVIDIA DGX Cloud Lepton

Partner GPU marketplace / DGX Cloud usage

vs

Serverless GPU

Modal

Functions: per-second CPU, memory and GPU resources; Shared Endpoints: per-token. Storage and network egress have separate allowances and rates.

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NVIDIA DGX Cloud Lepton vs Modal GPU inference comparison
DimensionNVIDIA DGX Cloud LeptonModal
CategoryGPU marketplaceServerless GPU
BillingPartner GPU marketplace / DGX Cloud usageFunctions: per-second CPU, memory and GPU resources; Shared Endpoints: per-token. Storage and network egress have separate allowances and rates.
GPU choiceNVIDIA and partner GPU classes exposed through DGX Cloud LeptonChoose supported GPU types through the function GPU setting, including T4, L4, A10, L40S, A100, RTX PRO 6000, H100, H200, B200 and B300; allocation and multi-GPU limits vary.
Cold startZero replicas cannot serve requests or automatically wake on traffic under the current documentation. Scale the deployment up again, or configure a nonzero minimum; provisioning/model-load delay depends on capacity.Can be noticeable on cold containers; benchmark the real image and model.
Model accessDeploy models to managed endpoints (including vLLM/SGLang workflows) using selected partner GPU capacity; NVIDIA also links to build.nvidia.com serverless APIs/NIMs as separate surfaces.Package models in images or pull at runtime
Best forTeams wanting to deploy/customize models to managed endpoints over NVIDIA Cloud Partner/GPU marketplace capacity.Developers who want GPU code as functions with autoscaling
Watch outEndpoints default to one replica and scale to zero after one hour inactive. The documentation says automatic scale-up from zero is unsupported: an operator must scale the deployment up before it can serve requests again. Partner inventory, rates and SLAs vary.You can choose a specific supported GPU type, but containers and scaling remain managed. Warm idle containers consume billable resources. Starter compute credits do not cover Shared Endpoints tokens.
GPU choice (1–10)Winner: 7/106/10
Time-to-serving (editorial) (1–10)5/10Winner: 7/10
Price clarity (1–10)5/10Winner: 7/10
Production ops (1–10)7/10Winner: 8/10
Open-model breadth (1–10)6/10Winner: 7/10

Chart

Fit scores on the decision axes

Editorial 1–10 ratings for this pair only — not live pricing or latency benchmarks.

GPU choice

Pick exact GPUs

Time-to-serving (editorial)

Warm-path fit

Price clarity

Easy to forecast

Production ops

Less DIY ops

Open-model breadth

Catalog depth

Scores are editorial planning ratings (1–10) for product shape — not published $/hour quotes or vendor SLAs. Verify current pricing on each provider site.

How to decide

Prefer NVIDIA DGX Cloud Lepton when teams wanting to deploy/customize models to managed endpoints over nvidia cloud partner/gpu marketplace capacity.. Prefer Modal when developers who want gpu code as functions with autoscaling. If those statements both feel true, rent a GPU for control and keep a managed API for peak traffic — do not force one product to do both jobs.

Common questions

NVIDIA DGX Cloud Lepton vs Modal

Answered from the verified figures on this page rather than general guidance.

How are NVIDIA DGX Cloud Lepton and Modal billed?
NVIDIA DGX Cloud Lepton uses partner gpu marketplace / dgx cloud usage; Modal uses functions: per-second cpu, memory and gpu resources; shared endpoints: per-token. storage and network egress have separate allowances and rates.. Marketplace hourly spend tracks GPU uptime; serverless and managed APIs bill for what you invoke — different failure modes if you forget to shut things down.
Which gives more control over the GPU, NVIDIA DGX Cloud Lepton or Modal?
NVIDIA DGX Cloud Lepton: NVIDIA and partner GPU classes exposed through DGX Cloud Lepton. Modal: Choose supported GPU types through the function GPU setting, including T4, L4, A10, L40S, A100, RTX PRO 6000, H100, H200, B200 and B300; allocation and multi-GPU limits vary.. NVIDIA DGX Cloud Lepton scores higher for GPU choice in our editorial fit ratings (7/10 vs 6/10). Pick a marketplace when you need a specific SKU; pick serverless or managed APIs when you want the platform to handle hardware.
Which has faster cold starts, NVIDIA DGX Cloud Lepton or Modal?
NVIDIA DGX Cloud Lepton: Zero replicas cannot serve requests or automatically wake on traffic under the current documentation. Scale the deployment up again, or configure a nonzero minimum; provisioning/model-load delay depends on capacity.. Modal: Can be noticeable on cold containers; benchmark the real image and model.. Our editorial ratings favour Modal (7/10 vs 5/10), but real latency depends on model size, region, and whether endpoints are kept warm. Those 1–10 scores are editorial rankings, not measured milliseconds — record your own TTFT/p95 on a warm endpoint in the target region before you buy on latency.
Should I use NVIDIA DGX Cloud Lepton or Modal?
Choose NVIDIA DGX Cloud Lepton when teams wanting to deploy/customize models to managed endpoints over nvidia cloud partner/gpu marketplace capacity.. Choose Modal when developers who want gpu code as functions with autoscaling. Watch out: Endpoints default to one replica and scale to zero after one hour inactive. The documentation says automatic scale-up from zero is unsupported: an operator must scale the deployment up before it can serve requests again. Partner inventory, rates and SLAs vary. You can choose a specific supported GPU type, but containers and scaling remain managed. Warm idle containers consume billable resources. Starter compute credits do not cover Shared Endpoints tokens.