Search: “hardware”

ORBITALIF: An Efficient Spiking Federated Learning Framework for Onboard Cloud Removal

model-releasesarxiv-cs-ai

arXiv:2608.24073v1 Announce Type: cross Abstract: Low-earth-orbit (LEO) satellites enable high-resolution, large-scale Earth observation for applications such as disaster monitoring and environmental

26 Aug 2026

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Qwen3.8-27B IQ3_XXS wrote a correct multilayer TMM on a 16 GB Quadro — after 100 minutes, 3 compactions, and 108k output tokens

DGX agent

https://preview.redd.it/i8rjx0ar5mlh1.png?width=2160&format=png&auto=webp&s=c2588bc7b2519ea71b176ca73faf566dfc585496 I wanted to see whether a heavily quantized 27B model running entirely on an older

model-releasesr-localllama

26 Aug 2026

Your model fits. Your settings don't. Three Ollama defaults multiply your memory before the model ever loads.

ollama ps settles this in one line, and almost nobody runs it before changing their quant. The PROCESSOR column reports exactly one of three things: 100% GPU - every layer on the GPU 100% CPU - the GP

26 Aug 2026

Safety

Balancing Safety and Optimality in Robot Path Planning: Algorithm and Metric

arXiv:2505.23197v4 Announce Type: replace-cross Abstract: Path planning for autonomous robots faces a fundamental trade-off between path length and obstacle clearance. While existing algorithms typica

safetyarxiv-cs-ai

GCS-Bridging: Restoring Connectivity of Disconnected Convex Sets for Graph-of-Convex-Sets Motion Planning

arXiv:2608.22326v1 Announce Type: new Abstract: Graph-of-Convex-Sets (GCS)-based trajectory optimization represents collision-free regions in configuration space as a finite collection of convex sets

applicationsarxiv-cs-ro

How to run LLMs as regular guy with low resources?

Hello everyone. I hope is all well with you all. I been around this sub for a few months and been quietly reading and I have seen how many of you are spending $10k on the Mac M5 and I am assuming you

local-air-localllama

Improving an ollama model with rag and raft

Building a local AI agent hierarchy on a budget — RAG, quantization, and testing whether fact-grounding pushes small models toward real creativity I don't have a CS background, a GPU, or much of a bud

local-air-ollama

Lifelong Robot Recomposition via Persistent Categorical Modeling for Unified Task-Driven Co-Design, Verification, and Planning

arXiv:2608.21676v1 Announce Type: new Abstract: Robotic systems are traditionally designed and deployed in static configurations, with assumptions made at design-time becoming immutable constraints du

applicationsarxiv-cs-ro

MADR: MPC-guided Adversarial DeepReach

arXiv:2510.18845v2 Announce Type: replace Abstract: Hamilton-Jacobi (HJ) Reachability offers a framework for generating safe value functions and policies in the face of adversarial disturbance, but is

researcharxiv-cs-ro

Neighbor-Aware View Synthesis for Restoring Missing Views in Light-Field Camera Arrays

arXiv:2608.23175v1 Announce Type: new Abstract: In light-field (LF) imaging systems, dense spatial sampling from a camera array enables powerful post-capture capabilities such as refocusing and depth

applicationsarxiv-cs-cv

NeuroPrefetcher: Storage-Aware Sparse LLM Inference via Delta Prefetching

model-releasesarxiv-cs-lg

arXiv:2608.22643v1 Announce Type: cross Abstract: Deploying large language models on edge devices is increasingly limited by a widening gap between model size and available memory. Existing approaches

Industry

OpenAI says its Jalapeño chip can power faster AI responses than the competition

OpenAI says its new AI chip, Jalapeño, completes tasks more efficiently and returns responses faster than other AI systems, according to a blog post published on Tuesday. During a briefing with report

industrythe-verge-ai

OpenAI says its Jalapeño chip delivered 1.5x-1.9x more AI work per watt and 1.7x-3.6x lower latency vs. Nvidia chips across GPT-OSS, DeepSeek R1, Kimi K2.5 1T (Emma Roth/The Verge)

Emma Roth / The Verge: OpenAI says its Jalapeño chip delivered 1.5x-1.9x more AI work per watt and 1.7x-3.6x lower latency vs. Nvidia chips across GPT-OSS, DeepSeek R1, Kimi K2.5 1T — Jalapeño outperf

model-releasestechmeme

Particle Image Velocimetry Refinement via Consensus ADMM for Active Fluid Control

arXiv:2512.11695v3 Announce Type: replace-cross Abstract: Particle Image Velocimetry (PIV) is among the central modalities for measuring flow fields across laboratory, industrial and environmental set

agentsarxiv-cs-cv

Physical Agentic AI: An Architecture for Orchestrating a Robot Crew with LLMs

arXiv:2608.22657v1 Announce Type: cross Abstract: Agentic AI frameworks interpret open-ended task goals and decompose them into multi-step plans. Richer information about embodiment-specific capabilit

agentsarxiv-cs-ai

Power-Performance Characterization of TinyML Systems

arXiv:2608.21646v1 Announce Type: cross Abstract: TinyML systems are enabling machine learning (ML) inference at the edge. However, there is little quantitative analysis of such systems. This paper pr

researcharxiv-cs-ai

Quantum-Inspired Hybrid Neural Networks for Neural Decoding: A Controlled Ablation Study of Learnable Quantum Sidecar Integration

arXiv:2608.22475v1 Announce Type: new Abstract: We study parameterized quantum circuits (PQCs) integrated as residual sidecar modules within a ResNet-50 backbone for 31-class neural population decodin

researcharxiv-cs-lg

Reproducible Vision-Guided 6-DoF Robotic Manipulator with a Mixed Stepper-Driver Architecture and Browser-Native Control

model-releasesarxiv-cs-cv

arXiv:2608.22799v1 Announce Type: cross Abstract: We present the NeuralNexus Arm, an open, low-cost 6-DOF robotic manipulator built by an undergraduate engineering team, together with the design decis

Reservoir of Importance: Learning Semi-Structured Sparsity with Differentiable Subset Sampling

model-releasesarxiv-cs-lg

arXiv:2608.23048v1 Announce Type: new Abstract: Semi-structured N:M sparsity has emerged as a practical direction for accelerating large language models (LLMs). However, existing learnable-mask approa

Spiking Neural Networks for Energy-Efficient Object Detection in Forward-Looking Sonar Imagery

arXiv:2608.22072v1 Announce Type: new Abstract: Autonomous underwater vehicles (AUVs) are increasingly important tools in industries ranging from research, to energy, to defense. AUVs are power-constr

agentsarxiv-cs-cv

Spinning Quadrotor: Hover Thrust Augmentation with Passive Lifting Surfaces

arXiv:2608.23163v1 Announce Type: new Abstract: Conventional multirotor aerial vehicles actively suppress yaw rotation during hover, expending power to maintain a fixed heading despite the fact that y

researcharxiv-cs-ro

Spyre-Accelerated Retrieval-Augmented Generation on IBM LinuxONE: A Cloud-Native Architecture for Secure, High-Throughput Enterprise AI Inference

model-releasesarxiv-cs-ai

arXiv:2608.21393v1 Announce Type: new Abstract: Running large language models inside enterprise environments has always bumped up against a practical wall: the data lives in one place, the AI horsepow

Today we’re launching Portable Computer on @NVIDIA DGX Spark. Portable Computer is a fully local version of Perplexity Computer, where the e…

Today we’re launching Portable Computer on @NVIDIA DGX Spark. Portable Computer is a fully local version of Perplexity Computer, where the entire runtime: orchestrator LLM, subagent LLM, agent harness

local-aiperplexity--x

VersaDB: A High-Performance AI Storage Database for Unifying Mutimodal Datasets

arXiv:2608.22795v1 Announce Type: new Abstract: The AI field has been rapidly developing, leading to the emergence of a large number of AI training datasets of various types. These datasets contain di

researcharxiv-cs-cv

Whole-Body Bilateral Teleoperation with Multi-Stage Object Parameter Estimation for Wheeled Humanoid Locomanipulation

model-releasesarxiv-cs-ro

arXiv:2508.09846v2 Announce Type: replace Abstract: This paper presents an object-aware whole-body bilateral teleoperation framework for wheeled humanoid loco-manipulation. This framework combines who

Safety

A Safety-Driven Architectural Framework for Fail-Operational Drone Swarms in Critical Missions

arXiv:2608.20906v1 Announce Type: cross Abstract: The certification of Unmanned Aerial Vehicle (UAV) swarms for safety-critical operations requires verifiable design assurance. Airworthiness standards

safetyarxiv-cs-ro

Safety

Advantage-level Aggregation Reinforcement Learning for X-point Target Magnetic Configuration Control in an EXL-50U Experiment-Calibrated Simulation Environment

arXiv:2608.20834v1 Announce Type: cross Abstract: Managing divertor heat loads is a central challenge for compact, high-power tokamaks. To increase local flux expansion and decouple the dissipation vo

safetyarxiv-cs-ai

Best model for 16gb ram Mac

Hi everybody! Every now and then these days, we’re seeing really huge open-weight models popping up. But since not everybody has a DGX Station at home, I’m interested in really small models. It’s incr

Do not blindly delete your older models, some are still precious

I have deleted tons and tons of older models to make space since I can't afford storage anymore. Easily 10TB... Anyways, I have been considering deleting DeepSeekV3.2 but decide to run it one more tim

agentsr-localllama

Edge-Based Agentic Retrieval-Augmented Generation for Autonomous FHWA Bridge Inspection Compliance

arXiv:2608.20372v1 Announce Type: cross Abstract: The Federal Highway Administration (FHWA) mandates that over 600,000 bridges in the United States be evaluated against the Recording and Coding Guide

agentsarxiv-cs-ai

Event-triggered Implicit Perturbation for Zeroth-Order Fine-Tuning of Spiking Transformers

arXiv:2608.21223v1 Announce Type: cross Abstract: Zeroth-order (ZO) optimization estimates gradients using only forward-pass evaluations, making it suitable for fine-tuning non-differentiable, event-d

researcharxiv-cs-lg

Fast Coordinated Bimanual Motion Planning With Hard Constraints

arXiv:2608.20946v1 Announce Type: new Abstract: Bimanual manipulation enables complex tasks but introduces added complexity from the high number of degrees of freedom involved. When handling rigid obj

applicationsarxiv-cs-ro

GPU Poor - Don't overlook Laguna XS 2.1

As per title. I'm not affiliated with the team behind this model in any way, shape or form. As a GPU poor myself (8 GB VRAM laptop + 12 GB VRAM desktop), I found Laguna to be very promising on my lapt

is there a music UPSCALER llm?

similar to video upscaler LLMs, what's the bleeding edge right now on something similar for audio music? the idea is you feed it in with a low bitrate MONO old soundtrack, and the LLM then recreates i

local-air-localllama

Llama-Mobile: Efficient 2.7-Bit Quantization of VLMs

model-releasesarxiv-cs-cv

arXiv:2608.21134v1 Announce Type: new Abstract: Deploying vision-language models (VLMs) on mobile devices is challenging due to their significant memory and compute requirements. We present a framewor

Planning to spend ~$100 benchmarking differnet Qwen3.8-27B quants and kv cache and looking for input before I start

TL;DR: I'm planning to spend around 100 on cloud GPUs to benchmark Qwen3.8-27B with a focus on questions that actually matter when running it locally: different quant levels/providers, 8-bit vs 16-bit

Real local agentic coding on a 12GB VRAM budget.

Thanks to Unsloth Dynamic 3.0 quants coming in slightly leaner and better preserved, I settled on Qwen 3.8 27B (`UD_Q4_K_XL`) at 100K context as my daily driver for Hermes Agent and OpenCode. On an RT

Rethinking Expressivity and Efficiency in Test-Time Training

arXiv:2608.21308v1 Announce Type: new Abstract: Test-Time Training (TTT) enables long-context processing via continuous weight updates during inference, but current methods struggle to balance the exp

researcharxiv-cs-lg

What's the best local model you've found for 8 GB of VRAM?

I'm curious what other people are using for local LLM coding / agentic coding with only 8 GB of VRAM. My current setup is: Intel Core i7-11800H RTX 3070 Laptop, 8 GB VRAM 32 GB DDR4 RAM openSUSE Tumbl

Benchmark results: what is the best and fastest engine to run Qwen3.8-27B on macOS

WARNING: I think I made a mistake with omlx, and its results below seem to be without any kind of acceleration. I am rerunning them with Lightning MTP and ANE support for prefill. Will update the post

23 Aug 2026

New qwen3.8:27b on a 39k line C to single-file HTML / three.js port

I was just curious how the new qwen3.8:27b does on a hard C to HTML porting job against Opus 5 in a default Claude Code. The job: my fun side project is a procedural shooter in a single C file. Port i

23 Aug 2026

Your model fits in VRAM. Your context doesn't. The KV cache math nobody shows you.

Spent way too long confused about why an 8B at Q4_K_M, about 4.9GB on disk, would OOM on a 12GB card. The weights fit twice over. The answer is the KV cache, and the math is simple enough that you can

23 Aug 2026

3 experiments running dsv4-flash-0731 q4+ quants on 128GB RAM + ~60 GB VRAM (with a quite bad pcie infra) with an acceptable tgs and relatively acceptable pp speed

The post describes some experiments I had while trying to desperately run deepseek-v4-flash-0731 4 bit+ quants on my machine which is supposed to support only q2 quants of the model, a or 2.xx bpw qua

Benchmarking qwen3.8:27b by having it port a 34k line C game to one HTML file. The agent mattered more than I expected.

My hobby project skill-issue is an arena FPS in a single C file, about 34k lines, everything procedural. My test for local setups is to have an agent port it to a single file HTML version with three.j

Current best model for narrative, chat, prompt creation (so basically everything except agentic coding)? - 5090

Im looking to set up a new local llm (probably on unsloth studio as that seemed to be doing pretty well last time I tested it). This one won't need to do agentic coding or app building or anything (no

I forked Ninfer 3090 and converted it to run on the CMP170HX - doubled my Qwen3.6-35B from llama.cpp

Good afternoon, everyone! I wanted to show the work I've been doing around porting Ninfer over to the CMP170HX (Github) So, first, I do want to call out the amazing work that Neroued, Sergiuszm and sp

Ollama + llama.cpp + VS Code + OWUI + ...cloud?

I've been trying to figure out what the best configuration for my local stack would be and have been primarily determining this through trial and error. I wanted to get some outside opinions and stack

Single RTX 5090: Qwen3.8-27B NVFP4 at a real 262K context in vLLM — 77 tok/s short-context, 64.7 tok/s at 128K

This is the Qwen3.8-27B setup I actually use every day on one RTX 5090. I wanted to write it down with enough detail that another 5090 owner can reproduce it instead of guessing which memory knobs I u