AI · alternatives · 2026
24 alternatives to Epochly
Train AI models 1000x faster than your local laptop.
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
- 1SF
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 · its alternatives →
- 2
General Compute▲315AI models that run on an inference cloud optimized for speed
May 2026 · generalcompute.com · its alternatives →
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- 4TC
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 →
- 5
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 →
- 6
RunInfra▲156Describe the AI model you need and get an optimized AI
Jul 2026 · runinfra.ai · its alternatives →
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Make a website with AI in seconds for $1
2023 · parking.onamae.com · its alternatives →
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- 10
RL-training an AI agent to RL-train AI agents. Contribute to Danau5tin/ai-trains-ai development by creating an account on GitHub.
Jul 2026 · github.com · its alternatives →
- 11
DataMacaw▲67Train and run your AI models easily at low cost in the cloud
2022 · aws.amazon.com · its alternatives →
- 12
Multi-GPU reinforcement learning using Deep Q-Network in TensorFlow for OpenAI Gym - vishar0/dist-dqn
2016 · github.com · its alternatives →
- 13
Self-host AI/ML with the world's cheapest GPU cloud
2025 · thundercompute.com · its alternatives →
- 14
Hi HN, We're excited to introduce Fixstars AIBooster, our new performance engineering tool designed to significantly accelerate AI model training while optimizing GPU utilization. AIBooster provides: Real-time monitoring of GPU, CPU, memory, and power consumption. Clear visibility into performance bottlenecks, helping developers optimize AI workloads. Proven acceleration of AI training processes—users commonly achieve up to 2-3x speed improvements. Significant cost savings by maximizing infrastructure efficiency. It's free to try, requires minimal setup, and integrates seamlessly into your…
2025 · fixstars.com · its alternatives →
- 15
Jupyter notebooks you can run on free cloud GPUs
2019 · its alternatives →
- 16
Training DL models need not be expensive or complicated.
2021 · jarvislabs.ai · its alternatives →
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- 18
The Emotion Engine has 32 MB of RAM total, so the trick is streaming weights from CD-ROM one matrix at a time during the forward pass — only activations, KV cache and embeddings live in RAM. This means models bigger than the RAM can still run, they just read more from disc. Had to build a custom quantized format (PSNT), hack endianness, write a tokenizer pipeline, and most of the PS2 SDK from scratch (releasing that separately). The model itself is also custom — a 10M param Llama-style architecture I trained specifically for this. And it works. On real hardware.
Mar 2026 · github.com · its alternatives →
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- 21FH
Hi, This is Dan and Genevieve from Burstable AI. We've iterated and made a 45 degree pivot, taking what we learned from developing burst (https://news.ycombinator.com/item?id=28191459) to introduce a cloud service that provides access to a GPU-enabled machine using Jupyterlab to provide notebooks, shell access, and a code/text editor. GPU access is measured and the first 50 hours are free. This is *not* a platform to do crypto mining or run weeks of model training for free. We are focused on the R & D phase of modern AI/ML, where developers/scientists are…
2022 · cloudburst.host · its alternatives →
- 22
Trying to get a better understanding for the economics of compute, started with a tracker. Most importantly, it needs more data. Anything else I should add?
2025 · computeprices.com · its alternatives →
- 23
We built RapidFire AI, an open-source Python tool to speed up LLM fine-tuning and post-training with a powerful level of control not found in most tools: Stop, resume, clone-modify and warm-start configs on the fly—so you can branch experiments while they’re running instead of starting from scratch or running one after another. - Works within your OSS stack: PyTorch, HuggingFace TRL/PEFT), MLflow. - Hyperparallel search: launch as many configs as you want together, even on a single GPU - Dynamic real-time control: stop laggards, resume them later to revisit, branch promising configs in…
2025 · github.com · its alternatives →
- 24DI
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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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 →