AI · alternatives · 2026
24 alternatives to FloydHub
Build Deep Learning models on cloud GPUs
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. FloydHub launched in 2018; newer entries below may have overtaken it.
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Lobe▲1,236Visual tool for building custom deep learning models
2018 · github.com · its alternatives →
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The easiest cloud IDE for deep learning
2018 · blog.floydhub.com · its alternatives →
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LobeHub▲434Your Chief Agent Operator for multi-agent work
May 2026 · lobehub.com · its alternatives →
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TensorFlow 1.0▲823Open-source machine learning library by Google
2017 · tensorflow.org · its alternatives →
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An on-premises, bare-metal solution for deploying GPU-powered applications in containers - emergingstack/es-dev-stack
2016 · github.com · its alternatives →
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Netmind Power▲272Hi 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 →
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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 →
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Cerebrium▲300If 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 →
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Running DeepSeek V3 (685B) requires 8×H100 GPUs which is about $14k/month. Most developers only need 15-25 tok/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/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 →
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vEdge is a GPU cloud compute platform making computing affordable and accessible.
2021 · gpu.land · its alternatives →
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2019 · zecoda.com · its alternatives →
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Enterprise world model that learns how you would do tasks
Mar 2026 · anterpise.com · its alternatives →
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Weights & Biases▲110Developer tools for deep learning & machine learning
2019 · wandb.ai · its alternatives →
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Accelerating open machine learning research with Cloud TPUs
2017 · sites.research.google · its alternatives →
- 21DI
Hi HN community, Shen and I created a service for anyone to easily train deep learning model on GPU power harnessed from the crowd. We have completed the first version DeepCluster.io (http://deepcluster.io) and welcome ML researchers to try it out for free! We are enthusiastic of deep learning, but often found training models with GPU instances on AWS very expensive. Meanwhile, some of our friends have idle GPUs that are used to mine cryptos. So we decided to borrow their GPUs for training deep learning model ourselves, and believe this could be a service that benefits other ML…
2019 · its alternatives →
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Hey everyone, ML Blocks is a node-based workflow builder to create multi-modal AI workflows without writing any code. You connect blocks that call various visual models like GPT4v, Segment Anything, Dino etc. along with basic image processing blocks like resize, invert color, blur, crop, and several others. The idea is to make it easier to deploy multi-step image processing workflows, without needing to spin up endless custom OpenCV cloud functions to glue together AI models. Usually, even if you're using cloud inference servers like Replicate, you still need to write your own image…
2024 · mlblocks.com · its alternatives →
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Multi-GPU reinforcement learning using Deep Q-Network in TensorFlow for OpenAI Gym - vishar0/dist-dqn
2016 · github.com · 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 →