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Nebius Startup Deals & Discounts

Our listing shows up to $100k in Nebius GPU credits; Nebius names no amount and wants VC-partner backing with $5M+ raised. $100k is 22,222 H100 hours.

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Deal Overview

Best Offer

$100K

Total Value

$100K

Available Deals

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Available Deals

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Open Access100K

Up to $100k in free credits

Up to $100k in free credits

Promo code, redemption steps & eligibility

Nebius Startup Deals - Overview

Nebius runs an application-based startup program that bundles introductory credits, engineering time and investor introductions. Our listing says up to $100k in credits for new customers or free-plan accounts. Nebius's own startup page is narrower than that, and anyone planning around the $100k should read its terms first:

  • Funding: at least $5M raised, from one of the vendor's approved venture partners.
  • Age and product: incorporated fewer than 5 years ago, building or scaling an AI-enabled product or model.
  • Excluded: consultancies and outsourced dev shops, resellers, cloud providers, crypto-only companies and public companies.
  • Speed: no response time is promised, and applicants can land on a waitlist.

The page gives no duration and no tier amounts, so the $100k ceiling comes from our listing alone.

Against other programs in our catalog. Together AI lists up to $50,000 in credits, DigitalOcean for AI lists up to $100,000, and Google Cloud runs from $2,000 up to $350,000 depending on funding history. Nebius ties with DigitalOcean for AI on the $100k ceiling. The entry bar is what separates them: Nebius's page asks for a venture-backed company with $5M raised, while Google Cloud's low tier starts at $2,000 for startups that have raised nothing.

About Nebius

Nebius runs a GPU cloud for training and serving AI models. Its price list spans NVIDIA HGX B300, B200, H200 and H100 machines, RTX PRO 6000 and L40S cards, plain CPU instances, shared and object storage, and a managed Kubernetes service that carries no charge. Slurm on Kubernetes (Soperator) is free software billed only by consumption, and teams that would rather skip cluster work can call open-s...

Key Features

Current NVIDIA lineup, B300 down to L40S

B300, B200, H200 and H100 HGX machines, RTX PRO 6000 and L40S cards are all on the price list, so one account can cover training and cheaper inference.

Managed Kubernetes and Slurm

Managed Service for Kubernetes has no charge, and Soperator runs Slurm on Kubernetes as free software that is billed only through the resources it uses.

Preemptible instances

Spot-style capacity cuts H100 and H200 hours to a fraction of the on-demand rate, with prices that move and no guarantee a job keeps its machines.

Commitment discounts

Reserving large clusters for several months lowers the on-demand rate by up to 35%.

Token Factory

A hosted inference service for open-source models, for teams that want an API instead of a cluster.

Free network traffic

Egress and ingress traffic and public IP addresses carry no charge on the price list.

Pros & Cons

Pros

  • A price list with real GPU-hour rates, so the value of a credit can be worked out in advance.
  • No large commitment is needed to start paying: the first payment minimum is $25.
  • Non-virtualized GPUs and no network egress fee suit sustained training and serving.
  • Engineering support and investor introductions are part of the program, not only credits.

Cons

  • Credits are tied to approved venture partners and $5M+ raised, which excludes most seed and pre-seed teams.
  • No response time is guaranteed, and applicants can sit on a waitlist.
  • The page publishes no credit amount or length, so the $100k headline cannot be confirmed from the vendor.
  • Consultancies, resellers, cloud providers, crypto-only firms and public companies are excluded.

Use Cases

Fits: a venture-backed AI lab fine-tuning or pre-training its own models. Large H100 or H200 runs are the case the credit was priced for, and Soperator gives a Slurm-style scheduler without a licence bill.

Fits: an inference-heavy product with steady traffic. Reserved capacity brings the rate down by up to 35%, and egress traffic costs nothing, which matters when you serve many tokens to many users.

Skip: a pre-seed team calling a hosted model API. The program's entry bar is $5M raised, and an app that only sends prompts to someone else's model has no use for GPU hours. Hosted-credit programs such as OpenAI's or Together AI's fit that team better.

Skip: an agency or consultancy building AI for clients. Outsourced development firms are on the excluded list.

Skip: a founder who wants a predictable start date. With no promised response time and a waitlist, a launch that depends on the credits arriving by a fixed week is a risk.

Pricing

Nebius's price page lists these on-demand rates per GPU-hour: B300 $9.50, B200 $8.50, H200 $5.40, H100 $4.50, RTX PRO 6000 $1.80, and L40S from $1.55. Preemptible H100 and H200 capacity starts at $0.79. Committing to large clusters for months takes up to 35% off on-demand.

What up to $100,000 of credit covers at those rates:

HardwareRate per GPU-hourGPU-hours bought
H100, on-demand$4.5022,222
H200, on-demand$5.4018,518
B200, on-demand$8.5011,764
L40S, Intel host$1.5564,516
H100, preemptible$0.79126,582

An eight-GPU H100 server costs $36 per hour, so the full credit runs one for 2,777 hours, about 115 days of nonstop use. A day of that server costs $864 at list. Preemptible prices can change as often as every 15 minutes, so the last row is a floor, not a plan.

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