Compare listed Replicate GPU hourly rates, models and regions below. Check the provider for availability, full instance cost and billing terms before choosing.
Replicate
Specialist CloudRun AI models via API — community library, billed per second
Replicate is a model API platform that lets developers run thousands of open-source AI models — image generation, video, audio, LLM, and more — via a simple REST API with per-second billing and no infrastructure management. Developers can also package and deploy their own custom models using Cog, Replicate's open-source containerization tool. A top choice for teams that want to integrate AI capabilities into applications without managing GPU infrastructure, with a large community model library covering Stable Diffusion, Flux, Llama, and hundreds of other models.
Cheapest On-Demand Replicate Pricing
$0.14/hr
Cheapest Spot Replicate Pricing
—
Replicate GPU Listings
6
Replicate Billing
Per-second serverless
Replicate Performance Benchmarks
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Replicate Info
Headquarters
San Francisco, CA
Founded
2021
Regions
US
Min Commitment
None
Support
Community → Enterprise
Replicate Strengths
- ▸Thousands of community models available via API
- ▸Per-second billing — zero idle cost
- ▸Cog: open-source model packaging and deployment
- ▸No infrastructure management required
Replicate Weaknesses
- ▸Less suited for custom training or fine-tuning at scale
- ▸Pricing can be higher for sustained high-throughput inference
- ▸Limited control over underlying infrastructure
Replicate is Best For
Replicate GPU Catalog
Estimate — not from live API. These figures may not reflect current pricing.
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Replicate — Frequently Asked Questions (FAQs)
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Replicate GPU pricing overview
Replicate is a specialist GPU cloud provider headquartered in San Francisco, CA. Replicate is a model API platform that lets developers run thousands of open-source AI models — image generation, video, audio, LLM, and more — via a simple REST API with per-second billing and no infrastructure management. Developers can also package and deploy their own custom models using Cog, Replicate's open-source containerization tool. A top choice for teams that want to integrate AI capabilities into applications without managing GPU infrastructure, with a large community model library covering Stable Diffusion, Flux, Llama, and hundreds of other models. Billing is Per-second serverless with a minimum commitment of None. Available regions include US. GPU instances can be provisioned on-demand, making Replicate suitable for both short-duration experiments and sustained production workloads.
Replicate vs other GPU providers
Replicate competes with providers including Lambda Labs, CoreWeave, RunPod, Paperspace, Vast.ai, and the major hyperscalers (AWS, Google Cloud, Azure) for GPU compute workloads spanning LLM training, fine-tuning, and inference serving. Key differentiators include: Thousands of community models available via API; Per-second billing — zero idle cost; Cog: open-source model packaging and deployment. Use the side-by-side comparison tool above to see Replicate pricing against any other provider across shared GPU models. For a broader market view, the live GPU prices table shows all 6 Replicate listings alongside 91+ providers in a single sortable view.
Best use cases for Replicate
Replicate is best suited for: Developers integrating AI models into applications, Teams wanting access to community model library, Rapid prototyping with pre-built models. Support tiers range from Community → Enterprise, making it viable for both individual researchers and enterprise teams with SLA requirements. There are currently 6 active GPU listings on Replicate, covering T4, L4, A40, A100 40GB and more. H100 SXM5 instances with NVLink interconnect are commonly used for large-scale training workloads. A100 40GB and RTX 4090 instances are frequently used for fine-tuning and inference of smaller models.
Replicate billing model and cost structure
Replicate uses Per-second serverless pricing. Spot pricing is not currently available on this provider — all instances are on-demand. Reserved instance pricing may be available for predictable long-running workloads — check the provider's pricing page for current committed-use rates. Always compare the effective hourly rate including egress, storage, and networking costs when evaluating total cost of ownership across providers.
Choosing the right GPU on Replicate
GPU selection depends on model size, precision, and whether your workload is compute-bound or memory-bandwidth-bound. For LLM training above 30B parameters, H100 80GB SXM5 instances with NVLink are the standard choice — high HBM3 bandwidth and FP16 throughput make them well-suited for large transformer workloads. For inference of 7B–13B models in FP16 or BF16, A100 40GB is a common choice on many providers. RTX 4090 instances are widely used for fine-tuning, prototyping, and quantized inference (INT4/INT8) of models up to 70B. Read the H100 vs A100 guide or the GPU benchmarks for ML guide for a full breakdown.
How Replicate pricing data is collected
Prices shown are sourced from Replicate's public pricing API or pricing page and refreshed every 15 minutes. On-demand rates reflect the current list price for a single GPU instance in the cheapest available region. Spot prices, where available, reflect interruptible instance rates at the time of the last snapshot. All prices are in USD per hour. Daily snapshots are kept in our history archive and visualised in the GPU price history charts — useful for identifying seasonal pricing patterns and evaluating whether current rates are above or below the 30-day average.
Evaluating managed LLM inference APIs as an alternative to self-hosted GPU compute? Compare live LLM token prices across OpenAI, Anthropic, Google, Groq, and many other providers. The cheapest GPU cloud guide covers the break-even analysis between self-hosted and managed inference at different request volumes.
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Launch your first GPU on Replicate
On-demand from $0.14/hr — 6 GPU configurations available. Per-second serverless billing.