Alternatives
Products that do what DCompute does
Serving GPU Compute, Not Highway Robbery
- 1
- 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
- 3GC
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
- 4OG
Greetings HN! This is Doruk from Oblivus, and I'm excited to announce the launch of our platform, Oblivus Cloud. After more than a year of beta testing, we're excited to offer you a platform where you can deploy affordable and scalable GPU virtual machines in as little as 30 seconds! https://oblivus.com/cloud - What sets Oblivus Cloud apart? At the start of our journey, we had two primary goals in mind: to democratize High-Performance Computing and make it as straightforward as possible. We understand that maintaining GPU servers through major cloud service providers can be…
2023 · oblivus.com
- 5CG
2021 · gpu.land
- 6SF
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/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
- 7
The first open-source price index for GPU compute
10d ago · getcomputable.com
- 8
Affordable H100, H200, GB300, and B200 GPU compute for training, inference, and everything in between.
4d ago · compute.cheap
- 9IV
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
- 10
- 11
- 12
- 13TG
Hey folks! I’m Jonathan from TensorDock, and we’re building a cloud GPU marketplace. We want to make GPUs truly affordable and accessible. I once started a web hosting service on self-hosted servers in middle school. But building servers isn’t the same as selling cloud. There’s a lot of open source software to manage your homelab for side projects, but there isn’t anything to commercialize that. Large cloud providers charge obscene prices — so much so that they can often pay back their hardware in under 6 months with 24x7 utilization. We are building the software that allows anyone to become…
2024 · dashboard.tensordock.com
- 14
- 15UA
The standard GPU utilization metric reported by nvidia-smi, nvtop, Weights & Biases, Amazon CloudWatch, Google Cloud Monitoring, and Azure Monitor is highly misleading. It reports the fraction of time that any kernel is running on the GPU, which means a GPU can report 100% utilization even if only a small portion of its compute capacity is actually being used. In practice, we've seen workloads with ~1–10% real compute throughput while dashboards show 100%. This becomes a problem when teams rely on that metric for capacity planning or optimization decisions, it can make underutilized systems…
Apr 2026 · systalyze.com
- 16
- 17IM
2022 · paylesstoaws.com
- 18OD
Hi HN, We’ve launched a GPU cloud platform offering on-demand access to high-end GPUs — with pricing starting at $0.79/hr, no queue, and no preemption. What we offer: - On-demand H100, H200, and B200 instances - H200 pricing from $0.79/hr - Multi-region support: US, Singapore, and Europe - No queuing, no bidding, and no interruptions - Used by AI startups, researchers, and open-source developers Try it: https://hpc-ai.com/?utm_source=hackernews&utm_medium=post&ut... We built this after facing our own frustrations with high prices and long wait times on other…
2025 · hpc-ai.com
- 19
- 20SS
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
- 21CB
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…
Jul 2026 · getcomputable.com
- 22AS
2019 · github.com
- 23GB
2016 · paperspace.com
- 24ST
I've been working on CloudRouter, a skill + CLI that gives coding agents like Claude Code and Codex the ability to start cloud VMs and GPUs. When an agent writes code, it usually needs to start a dev server, run tests, open a browser to verify its work. Today that all happens on your local machine. This works fine for a single task, but the agent is sharing your computer: your ports, RAM, screen. If you run multiple agents in parallel, it gets a bit chaotic. Docker helps with isolation, but it still uses your machine's resources, and doesn't give the agent a browser, a desktop, or a GPU to…
Feb 2026 · cloudrouter.dev
Ranked by how close each launch is in meaning, then by votes. Refine with a description →