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Dev tools · alternatives · 2026

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24 alternatives to Spell – simple, remote GPU execution

We'd like to introduce HN to Spell, which is a tool for easily running ML/DL jobs remotely. As Deep Learning has grown we see engineers and researchers struggle to incorporate running on GPUs into their workflow. So we built Spell to be the easiest way to get code running elsewhere - like the bash '&' operator but for remote machines. Sign up for an account at https://web.spell.run/waitlist, which includes $300 in credits for GPU time. There's a waitlist, but we'll be approving accounts as they come in. Here are some of the features we really wanted and built into Spell:…

Spell is a tool for running machine learning and deep learning jobs on remote GPUs. It is designed for engineers and researchers who need GPU compute without managing their own hardware. The product lets users execute… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Prices are shown for the 2 we have checked on their own sites, 2 of them free or with a free tier. Spell – simple, remote GPU execution launched in 2018; newer entries below may have overtaken it.

  1. 1

    Hi HN, We just opened public access to Qwen3‑Coder‑480B‑A35B‑Instruct via a REST/SDK API. Why it might be interesting: - Fully open-source (Apache‑2.0): https://github.com/QwenLM/Qwen3-Coder - 480B params (35B active MoE), long context up to 1M tokens with YaRN - Matches Claude Sonnet/GPT‑4o on SWE-Bench Verified (81.6%) - Free tier: 100K tokens/month

    2023 · netmind.ai · its alternatives →

  2. 2TC

    Hello HN! I’m Jonathan from TensorDock. After 7 months in beta, we’re finally launching Core Cloud, our platform to deploy GPU virtual machines in as little as 45 seconds! https://www.tensordock.com/product-core Why? Training machine learning workloads at large clouds can be extremely expensive. This left us wondering, “how did cloud ever become more expensive than on-prem?” I’ve seen too many ML startups buy their own hardware. Cheaper dedicated servers with NVIDIA GPUs are not too hard to find, but they lack the functionality and scalability of the big clouds. We thought to…

    2022 · tensordock.com · its alternatives →

  3. 3
    Spell▲212

    Deep Learning and AI accessible to everyone

    2019 · its alternatives →

  4. 4SF

    Hey folks! We're Alex and Evan, and we're working on putting together a 512 H100 compute cluster for startups and researchers to train large generative models on. - it runs at the lowest possible margins (<$2.00&#x2F;hr per H100) - designed for bursty training runs, so you can take say 128 H100s for a week - you don’t need to commit to multiple years of compute or pay for a year upfront Big labs like OpenAI and Deepmind have big clusters that support this kind of bursty allocation for their researchers, but startups so far have had to get very small clusters on very long term contracts, wait…

    2023 · sfcompute.org · its alternatives →

  5. 5

    The video demo runs a 7b Model on a normal gaming GPU. I think it already works quite well (accounting for the limited hardware power). :)

    2024 · github.com · its alternatives →

  6. 6SS

    Running DeepSeek V3 (685B) requires 8×H100 GPUs which is about $14k&#x2F;month. Most developers only need 15-25 tok&#x2F;s. sllm lets you join a cohort of developers sharing a dedicated node. You reserve a spot with your card, and nobody is charged until the cohort fills. Prices start at $5&#x2F;mo for smaller models. The LLMs are completely private (we don't log any traffic). The API is OpenAI-compatible (we run vLLM), so you just swap the base URL. Currently offering a few models.

    Apr 2026 · sllm.cloud · its alternatives →

  7. 7

    Hey we are Computable. We spent years building trading infrastructure at Jump Trading and Coinbase. From that point of view, compute looks like energy markets before 2000: everything trades through private bilateral leases, there’s no visible price, and nothing can be resold. The same H100 rents at a 2x spread depending on who’s asking, and once you sign a 24-month lease, it can never change hands. So we built a market for GPU nodes, sold by the calendar week. Here are three things you can do on it that you can’t do anywhere else: - Buy exactly the weeks you need. Three nodes for the last…

    Aug 2026 · getcomputable.com · its alternatives →

  8. 8
    GPU.LAND▲126

    Affordable cloud GPUs for deep learning

    2021 · vedge.cloud · its alternatives →

  9. 9

    This started out as a personal effort to learn more about machine learning. It's currently a CLI app where you give it a JSON file specifying your network architecture and hyperparameters and point it to your training data, then invoke it again in 'eval' mode with some data it's not seen before and it will try to classify each sample. I don't see many other people using Vulkan for GPGPU, and there may be many good reasons for that, but I wanted to try something a bit different. I've made every attempt to make the code very clean and readable and I've written up the math in…

    2024 · github.com · its alternatives →

  10. 10

    We recently used DeepSeek V4 Flash as a teacher for finance tasks with GPT-OSS-120B. Distillation works well on this problem. At a constrained 8k token budget, our self-distilled 120B scores 83.61% on FinanceReasoning, above Kimi K3 (81.93%) and Inkling (65.13%). We released the 20B open weights. With V4 as the teacher though, we realized it would be timely to measure if the censorship characteristic of it transferred to the distilled version of the base model. tl;dr it didn't, the teacher answered politically sensitive questions 7 SDs differently than expected, but the distilled model's…

    Jul 2026 · ctgt.ai · its alternatives →

  11. 11

    AI models that run on an inference cloud optimized for speed

    May 2026 · generalcompute.com · its alternatives →

  12. 12WM

    Try it out! https:&#x2F;&#x2F;glhf.chat&#x2F; Hey HN! We’ve been working for the past few months on a website to let you easily run (almost) any open-source LLM on autoscaling GPU clusters. It’s free for now while we figure out how to price it, but we expect to be cheaper than most GPU offerings since we can run the models multi-tenant. Unlike Together AI, Fireworks, etc, we’ll run any model that the open-source vLLM project supports: we don’t have a hardcoded list. If you want a specific model or finetune, you don’t have to ask us for it: you can just paste the Hugging Face link in and…

    2024 · glhf.chat · its alternatives →

  13. 13
    ZeroGPU▲298

    The compute efficient layer for AI inference

    Jun 2026 · zerogpu.ai · its alternatives →

  14. 14

    Accelerating deep learning experimentation

    2019 · its alternatives →

  15. 15

    Easy to use and fairly priced GPUs for Machine Learning

    2019 · clevergrid.io · its alternatives →

  16. 16CG

    vEdge is a GPU cloud compute platform making computing affordable and accessible.

    2021 · gpu.land · its alternatives →

  17. 17GC

    Hi HN, YC w24 company here. We just pivoted from drone delivery to build gpudeploy.com, a website that routes on-demand traffic for GPU instances to idle compute resources. The experience is similar to lambda labs, which we’ve really enjoyed for training our robotics models, but their GPUs are never available for on-demand. We are also trying to make it more no-nonsense (no hidden fees, no H100 behind “contact sales”, etc.). The tech to make this work is actually kind of nifty, we may do an in-depth HN post on that soon. Right now, we have H100s, a few RTX 4090s and a GTX 1080 Ti online.…

    2024 · gpudeploy.com · its alternatives →

  18. 18
    RunInfra▲156

    Describe the AI model you need and get an optimized AI

    Jul 2026 · runinfra.ai · its alternatives →

  19. 19

    A simple calculator that estimates how many concurrent requests your GPU can handle for a given LLM, with shareable results.

    2025 · selfhostllm.org · its alternatives →

  20. 20
    Cerebrium▲300

    If you haven’t noticed, GPUs are scarce right now. The global boom in inference has demand growing faster than supply can keep up, and at Cerebrium ...

    2024 · cerebrium.ai · its alternatives →

  21. 21
    Neuro▲104

    Instant infrastructure for machine learning

    2021 · getneuro.ai · its alternatives →

  22. 22

    The easiest way to use cloud GPUs

    2025 · tensorpool.dev · its alternatives →

  23. 23

    An on-premises, bare-metal solution for deploying GPU-powered applications in containers - emergingstack/es-dev-stack

    2016 · github.com · its alternatives →

  24. 24

    Turn idle GPUs into cash. Get affordable AI for everyone.

    Nov 2025 · its alternatives →

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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →