HOSTKEY GPU Grant for Scientific Projects

Free GPU & Compute | Amount: Free dedicated GPU server (NVIDIA A100 80GB, H100, or RTX-class) for declared project duration. Configuration depends on proposal. | AI-generated | 4/5 HardNeeds approval, startup status, or specific criteria active
2026-05-09
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Source: https://hostkey.com/about-us/grants-for-scientific-projects-and-startups

Description

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+ 1 HOSTKEY (EU/Netherlands-based bare-metal & GPU hosting provider) runs a recurring GPU Grant Program that awards free GPU server time to academic researchers, data scientists, and prospective startups working in AI, machine learning, big data, robotics, voice recognition, medical diagnostics, financial modeling, and other compute-heavy fields. Grant recipients get dedicated access to professional NVIDIA hardware (Tesla A100 80GB, H100, RTX-class GPUs) for the duration of their declared project. The program is competitive — proposals are reviewed and only a limited number of grants are awarded per round. Open to teams from the EU, US, and other countries.

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+ 2  

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+ 3

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+ 4  

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+ 5 Registration (Step-by-Step)

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+ 6  

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+ 8 2. Prepare your research proposal (1-2 pages, max 1,500 words) covering:

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+ 9 • Research area and problem you are solving

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+ 10 • Main idea, societal/industrial benefits

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+ 11 • Prior work and expected outcomes

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+ 12 • Project timeline

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+ 13 Justification of compute requirements (which GPU configuration you need and why)

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+ 14 3. Prepare your CV and gather links to relevant publications

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+ 15 4. Go to the application form at landing.hostkey.com/grant_for_scientific_projects and submit through the form linked there

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+ 16 5. (Optional but recommended) Attach letters of recommendation if requested by HOSTKEY during evaluation

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+ 17 6. Wait for review — there is no published timeline; HOSTKEY notifies winners by email

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+ 18 7. If awarded: HOSTKEY provisions the dedicated GPU server matching your declared scope

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+ 19  

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+ 20 Important:

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+ 21 • Only one application per round per applicant

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+ 22 • The application form URL landing.hostkey.com/grant_for_scientific_projects_form returned a 404 during research — start from the parent landing page above and follow the in-page "Apply" link to reach the live form

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+ 23 • Direct contact for questions: partners@hostkey.com / +31 20 820 3777

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+ 24  

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+ 25

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+ 26  

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+ 27 Eligibility (Who Qualifies)

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+ 28  

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+ 29 The program leans academic-first but does open the door to startups:

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+ 30  

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+ 31 Primary target: Full-time faculty or research fellows at a recognized academic institution, acting as Principal Investigator of the project

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+ 32 Also eligible: Prospective AI/ML startups and competition winners from data-science platforms (Kaggle, DrivenData, IDAO, ZINDI)

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+ 33 Field requirement: Your project must be in AI, ML, big data analysis, robotics, medical/financial AI, voice recognition, video/graphics rendering, or HPC

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+ 34 Geography: EU, US, and "other countries" — no hard geographic block, but billing/legal entity is in the Netherlands

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+ 35 Not a fit if: You are an indie hacker / hobbyist with no institutional or competition-track credentials, or you want general-purpose cloud credits (this is not a credit grant — it is a dedicated bare-metal GPU server for a specific project)

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+ 36  

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+ 37

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+ 38  

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+ 39 What You Get (GPU Hardware)

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+ 40  

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+ 41 HOSTKEY does not publish a fixed grant SKU — what you get depends on what you justify in your proposal and what is available. Their general GPU lineup that grants are drawn from:

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+ 42  

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+ 43 GPUMemoryTypical Use

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+ 44 NVIDIA H10080 GB HBM2eLLM training, large-scale AI

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+ 45 NVIDIA A100 80GB80 GBAI training/inference, large model fine-tuning

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+ 46 NVIDIA A100 40GB40 GBMid-scale AI workloads

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+ 47 NVIDIA RTX 4090 / RTX A-series24 GB+Inference, smaller training jobs, rendering

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+ 48 Multi-GPU nodesup to 8 GPUs / NVLinkDistributed training

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+ 49  

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+ 50 Servers are dedicated bare metal, not shared VMs — you get root access for the grant period.

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+ 51  

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+ 52 See current hardware at hostkey.com/gpu-dedicated-servers/nvidia-gpu-ai.

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+ 53  

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+ 54

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+ 55  

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+ 56 Proposal Requirements

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+ 57  

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+ 58 A winning proposal needs:

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+ 59  

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+ 60 Length: 1-2 pages, max 1,500 words

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+ 61 Research area and the specific challenges you are addressing

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+ 62 Main idea and benefits to society or industry

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+ 63 Prior work (yours and the field's) with citations

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+ 64 Expected outcomes and a timeline

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+ 65 Justification of compute — be specific: which GPU, how many, for how long, and why. Vague "we need GPUs" requests get rejected

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+ 66 CV of the applicant (the PI)

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+ 67 • Links to publications (if any)

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+ 68  

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+ 69

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+ 70  

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+ 71 Recipient Obligations

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+ 72  

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+ 73 Grants are framed as charitable donations, but HOSTKEY expects winners to:

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+ 74  

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+ 75 1. Submit a follow-up report describing the research outcomes after the grant period

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+ 76 2. Acknowledge HOSTKEY in resulting publications and post links back to HOSTKEY

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+ 77 3. Not resell or redistribute the granted compute

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+ 78  

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+ 79

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+ 80  

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+ 81 Additional Tips

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+ 82  

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+ 83 Difficulty is real — this is a competitive academic grant, not a self-serve credit. Expect a meaningful rejection rate. Strong PI credentials, prior publications, or competition wins materially improve your odds

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+ 84 No published deadline — applications appear to be rolling, but "the number of grants is limited per round" so apply when you have a concrete project, not speculatively

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+ 85 No timeline guarantee — HOSTKEY does not publish review SLA; expect weeks, not days

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+ 86 Alternate HOSTKEY grant track: GPU grants for data science competition winners — separate program if you have placed in Kaggle / DrivenData / ZINDI / IDAO

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+ 87 If you are an indie builder without academic credentials, this is probably not your best bet — look at NVIDIA Inception (startups), Lambda research credits, or the various always-free GPU offerings (Kaggle Notebooks, Colab, Modal free tier) instead

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+ 88 Bare metal vs cloud: because you get a dedicated server, there is no per-second billing surprise after the grant ends — but you are also responsible for setting up your own CUDA/Docker stack on the box

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+ 89  

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+ 90

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+ 91  

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+ 92 Sources:

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