Life & fun · alternatives · 2026
24 alternatives to AdaBound, an optimizer that trains as fast as Adam and as good as SGD
An optimizer that trains as fast as Adam and as good as SGD. - Luolc/AdaBound
AdaBound is an optimizer for machine learning model training available on GitHub. It bridges the gap between adaptive optimizers like Adam, which train quickly but produce less accurate final models, and stochastic… 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 1 we have checked on their own sites, 1 of them free or with a free tier. AdaBound, an optimizer that trains as fast as Adam and as good as SGD launched in 2019; newer entries below may have overtaken it.
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Trying to do gradient descent using automatic differentiation over branchy programs? Or to combine them with neural networks for end-to-end training? Then this might be interesting to you. We develped DiscoGrad, a tool for automatic differentiation through C++ programs involving input-dependent control flow (e.g., "if (f(x) < c) { ... }", differentiating wrt. x) and randomness. Our initial motivation was to enable the use of gradient descent with simulations, which often rely heavily on such discrete branching. The latter makes plain autodiff mostly useless, since it can only account for the…
2024 · github.com · its alternatives →
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TensorZero▲307Hi HN! We're Gabriel & Viraj, and we're excited to open source TensorZero. To be a little cheeky, TensorZero is an open-source platform that helps LLM applications graduate from API wrappers into defensible AI products. 1. Integrate our model gateway 2. Send metrics or feedback 3. Unlock compounding improvements in quality, cost, and latency It enables a data & learning flywheel for LLMs by unifying: • Inference: one API for all LLMs, with <1ms P99 overhead • Observability: inference & feedback → your database • Optimization: better prompts, models, inference strategies • Experimentation:…
2025 · github.com · its alternatives →
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FastRouter.aifree tier, from $199/mo▲364Route requests to the right LLM for cost, latency & quality
23d ago · fastrouter.ai · its alternatives →
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Fine-tuning, RL, and inference in one CLI
Dec 2025 · github.com · its alternatives →
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AdalFlow: The library to build & auto-optimize LLM applications. - SylphAI-Inc/AdalFlow
2024 · github.com · its alternatives →
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RunInfra▲156Describe the AI model you need and get an optimized AI
Jul 2026 · runinfra.ai · its alternatives →
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Open-source machine learning library by Google
2018 · tensorflow.org · its alternatives →
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After training calculator agent via RL, I really wanted to go bigger! So I built RL infrastructure for training long-horizon terminal/coding agents that scales from 2x A100s to 32x H100s (~$1M worth of compute!) Without any training, my 32B agent hit #19 on Terminal-Bench leaderboard, beating Stanford's Terminus-Qwen3-235B-A22! With training... well, too expensive, but I bet the results would be good! *What I did*: - Created a Claude Code-inspired agent (system msg + tools) - Built Docker-isolated GRPO training where each rollout gets its own container - Developed a multi-agent…
2025 · github.com · its alternatives →
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A single / multi layer / recurrent neural network written in Golang. - made2591/go-perceptron-go
2017 · github.com · its alternatives →
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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 →
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Haskell re-implementation of STOKE, the stochastic superoptimizer - blaze/notebooks/tutorial.ipynb at master · bollu/blaze
2019 · github.com · its alternatives →
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Label images and video for Computer Vision applications - Cartucho/OpenLabeling
2018 · github.com · its alternatives →
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Minimal, readable LLM post-training experiments on one 8GB GPU. Measures forgetting, seed variance, and RL emergence. - pochenai/nano-llm-posttraining
Aug 2026 · github.com · its alternatives →
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stable diffusion training. Contribute to Jack000/glid-3-xl-stable development by creating an account on GitHub.
2022 · github.com · its alternatives →
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Arc enables continual learning for agents to adapt, learn, and transfer knowledge in live environments. Open-source SDK for building agents that learn from experience and improve over time.
2025 · arc.computer · its alternatives →
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2022 · healthydiffusion.com · its alternatives →
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A minimalist deep learning library written from scratch in Python - sradc/SmallPebble
2021 · github.com · its alternatives →
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It's our new text-to-image model: a 9.3B single-stream diffusion transformer trained entirely from scratch. We focused heavily on controllability through structured JSON prompts, with strong text rendering, spatial awareness through bounding box guidance, and color palette control. It has the best text rendering of any open-weight model we've tested so far, and the NF4 quantized checkpoint runs on a single 24GB GPU. For more technical details and examples see our blog post: https://ideogram.ai/blog/ideogram-4.0/ We will be happy to answer any questions :)
Jun 2026 · github.com · its alternatives →
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High performance storage engine for efficient LLM inference and GPU Training.
Sep 2026 · theopenlake.com · its alternatives →
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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 →
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I've been working on training this small vision language model for the last month - excited to release the first prototype today! It is based on SigLIP (image encoder), Phi-1.5 (text model) and trained using the LLaVa-1.5 training dataset. It runs reasonably fast on CPU with ~8GB of RAM in full 32-bit precision. There's plenty of room to speed it up and reduce memory consumption by quantizing the model. I posted a video of it running on my M2 Macbook Air (on CPU not MPS, so performance should be comparable on other hardware) on Twitter to demonstrate inference speed:…
2023 · github.com · its alternatives →
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This is a low-level opensource library I developed for my own use and decided to share, as it makes it possible to process large checkpoints of neural networks without renting high-RAM instances, on a regular PC. It replaces torch.load() with a custom function that produces a dictionary that materializes tensors on the fly. Compared to other solutions it doesn't require sharding or re-encoding checkpoints and uses them completely as-is. It is a foundation to make it possible to run inference and compress language models and other large models one layer at a time - in principle, even one…
2023 · github.com · its alternatives →
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Alder▲22Optimizing Data Warehouse Query Performance via AI Agents
2025 · alderintelligence.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 →