LoongForge
VLDA: learning compact Deltas as actionable transition interfaces for robotic manipulation. 98.5% average on LIBERO; zero-shot 84.5% on LIBERO-Plus and 62.9% on RoboTwin 2.0 hard tasks, and 17–18 points ahead of π0.5 on real robots, trained with LoongForge.
LoongForge launched on May 22, 2026 with 1 votes.
What it does
LoongForge is a modular, scalable, high-performance training framework for LLMs, VLMs, diffusion, and embodied models. Up to ~5× training speedup, native NVIDIA GPU and Kunlun XPU support.
LoongForge is a modular, high-performance training framework for LLM, VLM, DiT and embodied models. Up to ~5× speedup on NVIDIA GPU & Kunlun XPU.
Ready-to-run configs for 35+ model families — built on Megatron-LM and torch-native backends. Play the demo — 83 seconds, has background music 🎬 4.38× faster on this run — loss curves stay aligned with the baseline 📊 Benchmark ~5× Max training speedup 35+ Model families supported GPU·XPU NVIDIA & Kunlun backends Apache 2.0 Open source license 🔥 Latest News All posts → 🧩 Easy One framework, broad coverage Full coverage of mainstream open-source LLMs, VLMs, MoE, diffusion, and VLA models. Ready-to-run configs and launch scripts included. ⚡ Efficient Up to ~5× training speedup Deep performance optimizations — fused kernels, adaptive FP8, MoE A2A overlap, and multimodal pipeline scheduling.…from baidu-baige.github.io
Does a similar job
all alternatives →
LoongForge-A high-performance training framework for LLM, VLM, VLA, WanMay 2026 · github.com · ▲10A high-performance framework for training LLMs, VLMs, diffusion, and embodied models on NVIDIA GPUs and Kunlun XPUs. - GitHub - baidu-baige/LoongForge: A high-performance framework for training LLMs, VLMs, diffusion, and embodied models on NVIDIA GPUs and Kunlun XPUs.
80% faster, 50% less memory, 0% loss of accuracy Llama finetuning2023 · github.com · ▲385Hi HN! I'm just sharing a project I've been working on during the LLM Efficiency Challenge - you can now finetune Llama with QLoRA 5x faster than Huggingface's original implementation on your own local GPU. Some highlights: 1. Manual autograd engine - hand derived backprop steps. 2. QLoRA / LoRA 80% faster, 50% less memory. 3. All kernels written in OpenAI's Triton language. 4. 0% loss in accuracy - no approximation methods - all exact. 5. No change of hardware necessary. Supports NVIDIA GPUs since 2018+. CUDA 7.5+. 6. Flash Attention support via Xformers. 7. Supports 4bit and 16bit…
ChainForge, a visual tool for prompt engineering and LLM evaluation2023 · chainforge.ai · ▲177Hi HN! We’re been working hard on this low-code tool for rapid prompt discovery, robustness testing and LLM evaluation. We’ve just released documentation to help new users learn how to use it and what it can already do. Let us know what you think! :)
Llama 3.2 Interpretability with Sparse Autoencoders2024 · github.com · ▲579I spent a lot of time and money on this rather big side project of mine that attempts to replicate the mechanistic interpretability research on proprietary LLMs that was quite popular this year and produced great research papers by Anthropic [1], OpenAI [2] and Deepmind [3]. I am quite proud of this project and since I consider myself the target audience for HackerNews did I think that maybe some of you would appreciate this open research replication as well. Happy to answer any questions or face any feedback. Cheers [1]…
TensorZero2025 · github.com · ▲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:…
LLM StatsOct 2025 · llm-stats.com · ▲293I was overspending on GPT-4o. It was really hard to compare different models I could switch to, so I built this LLM comparison tool. It shows leaderboards, pricing, and performance data across 100+ LLMs (including all major providers and open-source models). Key features: - Live pricing comparisons - Benchmark Scores (MMLU, HumanEval, GPQA, etc.) - Context length vs cost analysis - Speed/throughput tests across providers - Quality vs price visualizations - Open source (all data verifiable) Try it out: https://llmstats.com I'd like to know your opinion :) Tech stack: Next.js,…
More ai this month
the category →
Paintings by AI models: programs run through a simulation of oil paint.
AI · 22d ago · stillwet.art
FastRouter.ai▲364Route requests to the right LLM for cost, latency & quality
AI · 23d ago · fastrouter.ai
Source: Product Hunt launch ↗
Launched alongside, May 2026
the whole month →
Parallel agents, diff reviewer, and multi-model comparisons
Dev tools · May 2026 · kilo.ai
Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
Life & fun · May 2026 · github.com
🌱 Private, quiet space for thinking. Simple app for .md files. - zakirullin/files.md
Dev tools · May 2026 · github.com