Software Alternatives, Accelerators & Startups

GPU Mart VS Split Fee

Compare GPU Mart VS Split Fee and see what are their differences

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GPU Mart logo GPU Mart

Enterprise GPU hosting and rental for AI, AIGC image/video generation, and rendering. Dedicated GPU servers with stable uptime, full control, and no throttling or hidden limits. Get started in minutes.

Split Fee logo Split Fee

Split Fee connects UK recruitment agencies to collaborate on permanent placements. Share candidates and vacancies, match automatically, and split the fee.
  • GPU Mart GPU Mart home page
    GPU Mart home page //
    2026-04-28
  • GPU Mart GPU Server Pricing
    GPU Server Pricing //
    2026-04-28

GPU Mart has spent over 7 years empowering builders and researchers with high-performance GPU hosting. With enterprise NVIDIA GPUs, 99.9% uptime, full root access, and 24/7 expert support, we help breakthroughs happen faster.

  • Split Fee Login screen
    Login screen //
    2026-03-16
  • Split Fee Dashboard page
    Dashboard page //
    2026-03-16

Split Fee is a platform for UK recruitment agencies to collaborate on permanent placements.

Every agency has candidates they can't place and vacancies they can't fill. Another agency almost certainly has what you need โ€” but finding them, trusting them, and making the collaboration work has always been the hard part.

Split Fee solves this. Post your candidates and vacancies to the platform. Our matching algorithm finds opportunities across every agency on the network โ€” by skills, location, salary, and seniority. Candidate and client data stays anonymised until both sides agree to work together. When a placement is made, we handle the fee split and invoicing automatically.

No more posting in social media groups and hoping someone replies. No more sharing candidate details with strangers on trust alone. No more chasing invoices from agencies you barely know.

45% for you. 45% for them. 10% platform fee โ€” only when a placement is made.

Half of a placement fee is infinitely better than none of it.

GPU Mart

$ Details
$17.98 / Monthly ( 8 CPU Cores, 16GB RAM, 120GB SSD, GT730/K620 GPU Card)
Platforms
NVIDIA CUDA Linux KVM NVMe ECC RAM NVLink USA DC DDR5 ECC Windows Intel
Release Date
2019 November
Startup details
Country
United States
State
Texas
City
League
Founder(s)
Morris
Employees
50 - 99

Split Fee

Pricing URL
-
$ Details
freemium ยฃ97.0 / Monthly
Platforms
-
Release Date
2026 March
Startup details
Country
United Kingdom
Founder(s)
Abbie Taylor
Employees
1 - 9

GPU Mart features and specs

  • Up to 80% Lower Cost โ€” No Hidden Markup
    We own our hardware and skip the cloud middleman entirely โ€” so you pay for raw GPU compute, not a platform premium.
  • Built for Long-Running Workloads That Never Stop
    Every plan, including GPU VPS, is a dedicated physical GPU โ€” no virtualization. Performance is exactly what the spec sheet says, every hour.
  • Real Engineers โ€” Responding in Minutes
    Our GPU infrastructure team is online 24/7. From provisioning to CUDA configuration, help arrives fast โ€” every time.
  • AI Inference & LLM Serving
    The most cost-efficient GPU for AI inference โ€” deploy LLaMA, DeepSeek, Gemma and other open-source LLMs with predictable throughput.
  • Generative AI & Image Pipelines
    Run SDXL, Flux, ComfyUI, and video models with full VRAM access and flat monthly pricing for cost-efficient large-scale generation.
  • 3D Rendering & Visual Production
    Render with Blender, Redshift, or V-Ray on dedicated GPUs โ€” without render farm pricing or shared queues. Simple hourly or monthly pricing, no per-job markup.
  • Game Dev ยท Streaming
    Full Windows GPU environments with RDP access โ€” rare among providers. Ideal for interactive workloads. Linux also supported.

Split Fee features and specs

No features have been listed yet.

Analysis of GPU Mart

Overall verdict

  • GPU-Mart is a good choice for users needing dedicated GPU-powered virtual servers at competitive prices, particularly for tasks like AI/ML training, rendering, and deep learning, though it may not be as feature-rich or globally distributed as larger cloud providers like AWS or Google Cloud.

Why this product is good

  • Offers dedicated GPU server hosting with a range of NVIDIA GPU options (e.g., RTX, Tesla, Quadro series)
  • Competitive and transparent pricing compared to major cloud providers
  • Provides both Windows and Linux GPU server options
  • Suitable for GPU-intensive workloads like deep learning, 3D rendering, and video encoding
  • Instant deployment and remote access to servers
  • Flexible plans including monthly billing without long-term contracts

Recommended for

  • AI and machine learning developers needing affordable GPU compute
  • 3D rendering and animation studios
  • Data scientists running GPU-accelerated workloads
  • Small businesses or freelancers needing cost-effective GPU hosting
  • Users who need dedicated (non-shared) GPU resources for consistent performance

Analysis of Split Fee

Overall verdict

  • Split Fee (split-fee.com) appears to be a niche referral/fee-splitting platform aimed at connecting professionalsโ€”likely in real estate, legal, or brokerage-type industriesโ€”to share commissions on referred deals. Without independent reviews or verified track record widely available, it should be approached with due diligence, but the concept itself addresses a real market need for structured referral partnerships.

Why this product is good

  • Provides a structured framework for professionals to formally split fees or commissions on referred business
  • Can help expand referral networks beyond one's immediate contacts or region
  • May reduce disputes over referral agreements by formalizing terms upfront
  • Potentially useful for professionals who receive occasional out-of-market or out-of-expertise leads they want to monetize

Recommended for

  • Real estate agents or brokers looking to refer out-of-area clients
  • Legal or financial professionals wanting to formalize referral fee arrangements
  • Freelancers or consultants who want to monetize leads outside their expertise
  • Small firms seeking to expand reach through partner referral networks

Category Popularity

0-100% (relative to GPU Mart and Split Fee)
GPU Servers
100 100%
0% 0
SaaS
0 0%
100% 100
AI
100 100%
0% 0
Data-Driven Recruiting
0 0%
100% 100

Questions & Answers

As answered by people managing GPU Mart and Split Fee.

Which are the primary technologies used for building your product?

GPU Mart's answer

NVIDIA GPUs (RTX, A100, H100, Blackwell series) CUDA computing platform KVM virtualization (for GPU VPS environments) NVMe storage ECC memory Linux & Windows server environments SOC-certified US data center infrastructure

Split Fee's answer:

A next-generation serverless platform, built for AWS.

What makes your product unique?

GPU Mart's answer

GPU Mart is unique because it owns and operates its own GPU infrastructure, offering fully dedicated GPU servers with no shared resources, flat-rate pricing, and significantly lower costs compared to major cloud providers.

Split Fee's answer:

Split Fee is the first purpose-built platform for split fee recruitment in the UK. Instead of relying on LinkedIn groups, WhatsApp messages, and manual agreements, agencies upload their candidates and vacancies and the platform automatically matches them across agencies.

Candidate identities are revealed gradually; anonymised at first, then progressively disclosed as both sides accept, so agencies can collaborate without the risk of circumvention.

Why should a person choose your product over its competitors?

GPU Mart's answer

Users choose GPU Mart because it provides dedicated GPU performance without virtualization, up to 80% lower cost than hyperscalers, no hidden fees (no egress or setup charges), and stable long-term uptime backed by SOC-certified US data centers.

Split Fee's answer:

Most "split fee networks" are just directories or social groups where agencies post and hope someone responds. Split Fee is an actual matching engine. It scores candidate-vacancy pairs, handles the legal agreements (non-circumvention, self-billing), automates invoicing and fee splits, and manages the entire placement lifecycle from match to payment. Everything that normally requires trust, phone calls, and spreadsheets is handled by the platform.

How would you describe the primary audience of your product?

GPU Mart's answer

The primary audience includes AI developers, machine learning engineers, LLM builders, game developers, 3D artists, and companies running GPU-intensive workloads such as inference, training, rendering, and streaming.

Split Fee's answer:

UK recruitment agencies; from boutique firms with a handful of consultants to mid-sized agencies with specialist sector coverage. Any agency that has either strong candidates without the right vacancies, or client vacancies they can't fill from their own candidate pool. Split Fee turns those dormant assets into placements.

What's the story behind your product?

GPU Mart's answer

GPU Mart is built by a team with over 20 years of infrastructure experience and is backed by Database Mart. It was created to provide affordable, high-performance GPU hosting by eliminating cloud middlemen and operating directly owned GPU data centers in the US.

Split Fee's answer:

Abbie, our founder, knew that although split fee arrangements have existed in recruitment for decades, the process has always been manual: find a partner agency, negotiate terms, trust them with your candidate data, chase invoices. Most agencies avoid it because the overhead and risk outweigh the reward. Abbie built Split Fee to remove that friction entirely, with automated matching, progressive identity disclosure, built-in legal agreements, and automated billing, making split placements as straightforward as direct ones.

Who are some of the biggest customers of your product?

GPU Mart's answer

AI startups and LLM developers Machine learning research teams Game development studios (Unreal Engine / Unity users) 3D rendering professionals (Blender, V-Ray, Redshift users) Generative AI companies (Stable Diffusion, Flux, ComfyUI pipelines) Streaming and remote GPU desktop users

User comments

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What are some alternatives?

When comparing GPU Mart and Split Fee, you can also consider the following products

Vast.ai - GPU Sharing Economy: One simple interface to find the best cloud GPU rentals.

Unbench - Beyond recruitment, Unbench became a dynamic matchmaking platform, efficiently connecting companies with top specialists.

Paperspace - GPU cloud computing made easy. Effortless infrastructure for Machine Learning and Data Science

OVH Cloud - OVHcloud provides cloud solutions to meet all of your IT needs. With cutting edge cloud technology, come view our solutions by industry or use case.

Cloud GPU - Cloud GPU is a solution that provides high-performance GPUs on Google Cloud for machine learning and 3D visualization.

GPUClub.com - Rent multi-GPU servers for your data science, AI, neural networks and deep learning projects!