# local Published articles for local. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Khan Academy Uses Local Storage and Request Queues to Handle Offline Actions DevFeed: [Khan Academy Uses Local Storage and Request Queues to Handle Offline Actions]() Original publisher: [Read original article]() Author: Khan Academy Published: 2015-08-17T22:00:00Z Content type: article Language: en Sources: [Khan Academy]() Topics: [LocalStorage](), [client](), [Code](), [Internet](), [servers]() Tags: [architecture](), [change](), [code](), [engineering](), [function](), [hints](), [linear](), [local](), [news](), [offline](), [queue](), [request](), [server](), [web-frontend]() ### AI overview This article explains how Khan Academy addressed offline hint cheating by changing the client's request architecture. Actions are stored in local storage and placed in a queue for retry when connectivity returns, with linear backoff to avoid repeated requests during outages. ### Source excerpt By Phillip Lemons The problem Recently, a number of students on Khan Academy found a way to cheat ... Read more ## Running Agent Harnesses with Local Models DevFeed: [Running Agent Harnesses with Local Models]() Original publisher: [Read original article]() Author: Avi Chawla Published: 2026-09-15T21:59:31Z Content type: tutorial Language: en Sources: [Daily Dose of Data Science]() Topics: [Large Language Model](), [coding](), [Hardware](), [Open Source](), [Claude Code](), [codex]() Tags: [agent](), [coding](), [hardware](), [local](), [models](), [open-source](), [opentelemetry](), [profiling](), [recommendations](), [run-agent](), [video]() ### AI overview A video walkthrough explains how Magnitude profiles computer hardware, benchmarks local models, recommends practical candidates, and connects a selected model to coding agent harnesses such as Claude Code, Codex, OpenCode, and Pi. The article also presents a Dynatrace reference application for tracing LLM pipelines with OpenTelemetry. ### Source excerpt ...explained with a full video walkthrough. ## Quiz: How to Get Started With Ollama DevFeed: [Quiz: How to Get Started With Ollama]() Original publisher: [Read original article]() Author: Real Python Published: 2026-09-15T12:00:00Z Content type: tutorial Language: en Sources: [Real Python]() Topics: [Ollama](), [Python](), [Code](), [Hardware]() Tags: [chat](), [generate](), [hardware](), [how-to](), [install](), [internet](), [local](), [models](), [ollama](), [python](), [running]() ### AI overview An interactive 10-question quiz tests understanding of installing Ollama, pulling local models, and calling chat and generate functions from Python. It also covers multi-turn conversations, local hardware, and data privacy. ### Source excerpt Check your understanding of installing Ollama, pulling local models, and calling the chat and generate functions from your Python code. ## NVIDIA Personal AI Router Distributes AI Tasks across Local Compute DevFeed: [NVIDIA Personal AI Router Distributes AI Tasks across Local Compute]() Original publisher: [Read original article]() Author: Sergio De Simone Published: 2026-09-11T15:00:00Z Content type: news Language: en Sources: [InfoQ]() Topics: [Local AI](), [Inference](), [GPU](), [Hardware]() Tags: [agent](), [agents](), [ai](), [ai-ml-data-engineering](), [architecture-design](), [compute](), [demo](), [development](), [gpu](), [inference](), [large-language-models](), [local](), [ml-data-engineering](), [news](), [node](), [nvidia](), [nvidia-pair-ai-task-router](), [open-source](), [orchestration](), [performance]() ### AI overview NVIDIA has introduced PAIR in beta, a local router that distributes inference requests across compatible computers for multi-agent AI workloads. It works with local inference services such as Ollama and LM Studio and selects a node based on model and engine requirements. ### Source excerpt NVIDIA Personal AI Router (PAIR), now available in beta, lets you combine the inference capacity of multiple computers on your local network and automatically distribute AI requests among them. It is primarily designed for local multi-agent AI workloads, where multiple independent model calls can otherwise overwhelm one GPU. By Sergio De Simone ## Your Agent Harness Needs Runtime Security DevFeed: [Your Agent Harness Needs Runtime Security]() Original publisher: [Read original article]() Author: Avi Chawla Published: 2026-09-09T20:59:58Z Content type: tutorial Language: en Sources: [Daily Dose of Data Science]() Topics: [agent observability](), [Agent Harness](), [Security](), [Open Source](), [telemetry]() Tags: [agent](), [agent-harness](), [ai-agents](), [anthropic](), [claude](), [cybersecurity](), [github](), [guide](), [local](), [monitoring](), [open-source](), [security](), [telemetry]() ### AI overview This guide presents Agent Beacon, an open-source telemetry layer for AI agents. It records tool calls, shell commands, file changes, and approval decisions as structured runtime events across supported agent harnesses, providing a live record of agent behavior for security monitoring and investigation. ### Source excerpt A 100% local, open-source guide to recording what AI agents actually do at runtime. ## Android Studio Quail Using On Device Gemma 4 Experience DevFeed: [Android Studio Quail Using On Device Gemma 4 Experience]() Original publisher: [Read original article]() Author: Elye - A Dev By Grace Published: 2026-09-09T11:28:45Z Content type: tutorial Language: en Sources: [Mobile App Development Publication - Medium]() Topics: [Android Studio](), [gemma4](), [Large Language Model](), [Development]() Tags: [agent](), [android](), [android-development](), [android-studio](), [development](), [gemma](), [gemma-4](), [llm](), [local](), [memory](), [mobile-app-development](), [on-device]() ### AI overview This article describes using the on-device Gemma 4 model in Android Studio Quail for Android development. It outlines selecting the local model option, choosing Gemma in Model Providers, and downloading a model, while noting the need for a fast machine with substantial memory. ### Source excerpt How's Android Studio Quail support for On-Device LLM Model Doing? Continue reading on Mobile App Development Publication " ## Ractor-ready Rails, ordered cache fetches, and more! DevFeed: [Ractor-ready Rails, ordered cache fetches, and more!]() Original publisher: [Read original article]() Author: vipulnsward Published: 2026-09-04T00:00:00Z Content type: news Language: en Sources: [Ruby on Rails: Compress the complexity of modern web apps]() Topics: [Caching](), [Claude](), [configuration]() Tags: [agents](), [cache](), [claude](), [code](), [local](), [news](), [postgresql]() ### AI overview A weekly Rails codebase update covering Ractor support, cache-fetch ordering, database and Active Record fixes, test-query shuffling, and an Active Storage dependency upgrade. It also reports Agents on Rails benchmark results for Claude Fable 5.1 and GLM 5.3 Flash. ### Source excerpt Hi, it's Vipul. Let's explore this week's changes in the Rails codebase. ## NVIDIA PAIR Virtual Inference Router Expands Available Compute on Your Local Network DevFeed: [NVIDIA PAIR Virtual Inference Router Expands Available Compute on Your Local Network]() Original publisher: [Read original article]() Author: Tanya Lenz Published: 2026-09-03T16:00:00Z Content type: release Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [Inference](), [Local AI](), [GPU](), [Hardware]() Tags: [ai-agent](), [ai-agents](), [ai-inference](), [compute](), [content-creation-rendering](), [dgx-spark](), [edge-computing](), [gaming](), [geforce](), [gpu](), [hardware](), [inference](), [local](), [nvidia](), [open-source]() ### AI overview NVIDIA PAIR is a beta virtual inference router that distributes independent local inference requests across eligible machines on a home network. It works through compatible Ollama and LM Studio interfaces without requiring changes to an agent harness. ### Source excerpt AI agents are learning to do more by working together. A lead agent can break a complex task into smaller jobs and assign those jobs to specialized subagents.... ## Give Your Coding Agents a Memory You Own DevFeed: [Give Your Coding Agents a Memory You Own]() Original publisher: [Read original article]() Author: David Corvoysier Published: 2026-09-03T00:00:00Z Content type: article Language: en Sources: [Hugging Face - Blog]() Topics: [AI-assisted coding](), [Traces](), [Inference](), [dataset]() Tags: [agents](), [announcement](), [coding](), [datasets](), [embedding](), [guide](), [inference](), [local](), [memory](), [open-source](), [retrieval](), [traces]() ### AI overview funes is a local, durable memory layer for coding agents that indexes prior session traces so agents can retrieve past decisions with provenance. It uses a deterministic pipeline with vector and BM25 search, reranking, recency weighting, and local storage. ### Source excerpt We're on a journey to advance and democratize artificial intelligence through open source and open science. ## Choosing Local Models for Coding Agents Based on Hardware and Workload DevFeed: [Choosing Local Models for Coding Agents Based on Hardware and Workload]() Original publisher: [Read original article]() Author: Avi Chawla Published: 2026-09-02T19:10:34Z Content type: tutorial Language: en Sources: [Daily Dose of Data Science]() Topics: [Local AI](), [Hardware](), [Artificial Intelligence](), [Inference](), [quantization](), [Open Source]() Tags: [ai](), [hardware](), [local](), [local-ai](), [model](), [open-source](), [quantization](), [run]() ### AI overview This practitioner's guide explains why local models that work well for chat may perform poorly in coding-agent workloads. It discusses growing conversation context, memory requirements, precision, sustained speed, and thermal limits, then introduces Magnitude, an open-source inference server that profiles a machine and selects a configuration for local agent use. ### Source excerpt A practitioner's guide to local AI. ## Encrypting SQLite Databases with Turso: Local, Cloud, and BYOK DevFeed: [Encrypting SQLite Databases with Turso: Local, Cloud, and BYOK]() Original publisher: [Read original article]() Author: Jeff Olson Published: 2026-09-02T00:00:00Z Content type: tutorial Language: en Sources: [Turso Blog]() Topics: [Turso](), [Encryption](), [SQLite](), [Cryptography](), [Databases]() Tags: [benchmark](), [cloud](), [code](), [database](), [encryption](), [local](), [open-source](), [rust](), [security](), [sqlite](), [turso]() ### AI overview A tutorial on Turso's native SQLite encryption and cloud BYOK model, covering key handling, architecture, code, and benchmarks. ### Source excerpt How Turso's two encryption models work in practice: native encryption in the Rust engine and BYOK on Turso Cloud, with working code and real benchmark numbers. ## How to Get Started With Ollama DevFeed: [How to Get Started With Ollama]() Original publisher: [Read original article]() Author: Real Python Published: 2026-09-01T14:00:00Z Content type: tutorial Language: en Sources: [Real Python]() Topics: [Language models](), [SDKs]() Tags: [ai](), [apps](), [how-to](), [large-language-models-llms](), [learn](), [local](), [models](), [offline](), [open-source](), [privacy](), [python](), [text-generation](), [tutorial]() ### AI overview A video course on using Ollama and its Python SDK to run local LLMs, generate text, and build offline-capable AI applications. ### Source excerpt Learn how to install Ollama, pull local models, and connect them to your Python code using the chat and text generation interfaces. ## Scheduling email campaigns at scale with Amazon EventBridge Scheduler DevFeed: [Scheduling email campaigns at scale with Amazon EventBridge Scheduler]() Original publisher: [Read original article]() Author: Oluwaseun Ademuwagun Published: 2026-09-01T13:09:17Z Content type: tutorial Language: en Sources: [AWS Compute Blog]() Topics: [Amazon Web Services](), [Amazon Simple Queue Service (SQS)](), [Software as a service]() Tags: [advanced-300](), [amazon-eventbridge](), [amazon-sqs](), [aws](), [cost](), [customer](), [how-to](), [integration](), [local](), [post](), [saas](), [scale](), [technical-how-to]() ### AI overview This tutorial explains how to schedule personalized email campaigns at scale with Amazon EventBridge Scheduler. It uses one schedule per recipient to deliver messages at individually optimal times, discusses batch cron jobs, Amazon SQS delay queues, and third-party campaign tools, and describes scaling schedule creation with AWS Step Functions Distributed Map and delivery through Amazon SES. ### Source excerpt Learn how to use Amazon EventBridge Scheduler to deliver email campaigns at per-recipient optimal send times. This post shows how to create one schedule per recipient with zero idle compute cost, scale schedule creation with AWS Step Functions Distributed Map, and deliver through Amazon SES. ## Build with Tailscale. Build on Tailscale. DevFeed: [Build with Tailscale. Build on Tailscale.]() Original publisher: [Read original article]() Author: Kevin Purdy Published: 2026-08-31T14:00:00Z Content type: article Language: en Sources: [Blog on Tailscale]() Topics: [networking](), [Local AI](), [Go](), [App](), [ide]() Tags: [apis](), [applications](), [dev](), [go](), [local](), [local-ai](), [networking](), [server](), [software]() ### AI overview Tailscale describes two ways to build with its networking platform: embedding secure, identity-aware connectivity into applications with tsnet, and automating tailnet creation and management through APIs. A local Ollama server illustrates how application-level identities, ACLs, MagicDNS, and managed HTTPS can avoid public ports, host daemons, and manual proxy configuration. ### Source excerpt Put secure networking inside what you build, then automate the rest. ## I replaced my DNS resolver and the smart home finally shut up DevFeed: [I replaced my DNS resolver and the smart home finally shut up]() Original publisher: [Read original article]() Author: Shed Stack Published: 2026-08-29T15:00:00Z Content type: article Language: en Sources: [Shed Stack]() Topics: [Internet of things](), [Network](), [Pi-hole](), [telemetry]() Tags: [apps](), [devices](), [dns](), [internet](), [local](), [network](), [router](), [smart-home](), [telemetry]() ### AI overview The article describes replacing Pi-hole with AdGuard Home, using device-level DNS rules and VLAN isolation to reduce telemetry from nearly 100 smart-home devices. It also notes maintenance costs, including occasional false blocks, app issues, and manual DNS configuration. ### Source excerpt AdGuard Home and some strict VLANs quieted almost 100 internet connected devices that all wanted to phone home. ## Meet editorial-guide-ramalama: An AI Assistant That Checks Your Fedora CommBlog and Magazine Articles Against Editorial Guidelines DevFeed: [Meet editorial-guide-ramalama: An AI Assistant That Checks Your Fedora CommBlog and Magazine Articles Against Editorial Guidelines]() Original publisher: [Read original article]() Author: Ananya Nalavathu Published: 2026-08-25T12:47:18Z Content type: article Language: en Sources: [Fedora Community Blog]() Topics: [Fedora](), [Retrieval Augmented Generation (RAG)](), [Artificial Intelligence](), [Local AI](), [Containers](), [Open Source](), [Tooling](), [On-device AI]() Tags: [ai](), [articles](), [blog](), [fedora-project-community](), [inference](), [local](), [mentored-projects](), [oci](), [open-source](), [rag](), [tool]() ### AI overview The article introduces editorial-guide-ramalama, a Retrieval-Augmented Generation assistant built for Fedora contributors. It checks drafts against Fedora's editorial guidelines and published articles, cites specific guidelines when it identifies problems, and suggests actionable fixes. The tool uses RamaLama to run open models locally as OCI containers, with built-in ingestion, chunking, and retrieval, avoiding API keys and external services. ### Source excerpt By Ananya Nalavathu and Francois Gonothi Toure Introduction Open source communities run on contribution, and contribution runs on documentation, storytelling, and knowledge sharing. At the Fedora Project, that means the Fedora Community Blog and Fedora Magazine, two publications that give contributors a voice and give the community a way to stay informed, inspired, and connected. [...] The post Meet editorial-guide-ramalama: An AI Assistant That Checks Your Fedora CommBlog and Magazine Articles Against Editorial Guidelines appeared first on Fedora Community Blog. ## Do IXPs make the Internet faster? It's complicated DevFeed: [Do IXPs make the Internet faster? It's complicated]() Original publisher: [Read original article]() Author: Dan Fidler Published: 2026-08-23T23:05:33Z Content type: article Language: en Sources: [APNIC Blog]() Topics: [Internet](), [networking](), [Latency](), [Network](), [Low Latency](), [Streaming](), [Caching](), [Cloud](), [Resilience](), [Routing (disambiguation)](), [datasets]() Tags: [australia](), [cloud](), [content](), [cost](), [events](), [global](), [infrastructure](), [internet](), [ixps](), [latency](), [local](), [low-latency](), [netflix](), [network](), [networks](), [performance](), [resilience](), [routing](), [streaming](), [tech-matters](), [technology](), [thailand](), [thainog]() ### AI overview IXPs do not make the Internet uniformly faster. Their impact depends on how performance is defined, where content is hosted or cached, the type of exchange, and the surrounding network conditions. The article examines latency, throughput, streaming quality, reliability, routing, and the changing meaning of keeping traffic local. ### Source excerpt IXPs shape latency, cost, resilience, and the spread of new technologies, not just Internet speed. As the Internet evolves, the role of IXPs continues to expand, as highlighted in this BPF 2026 panel discussion. ## POSETTE Talk Recap - Postgres Isn't Slow. Your Storage Is DevFeed: [POSETTE Talk Recap - Postgres Isn't Slow. Your Storage Is]() Original publisher: [Read original article]() Author: ClickHouse Published: 2026-08-20T16:11:08Z Content type: article Language: en Sources: [ClickHouse Blog]() Topics: [PostgreSQL](), [benchmarking](), [IO](), [Latency](), [Replication](), [systems](), [clickhouse](), [Kafka]() Tags: [benchmark](), [clickhouse](), [cpu](), [kafka](), [latency](), [local](), [performance](), [postgres](), [postgresql](), [replication](), [storage](), [systems]() ### AI overview This article recaps a POSETTE 2026 talk about how storage performance affects PostgreSQL workloads at scale. It describes a benchmark comparing a 3.3-billion-row workload on gp3 EBS and local NVMe, covering ingestion, read latency, autovacuum, checkpoints, and logical replication, and introduces production patterns for running PostgreSQL on local NVMe. ### Source excerpt A recap of Sai Srirampur's POSETTE 2026 talk on storage performance in Postgres, with a local NVMe vs. EBS benchmark and the production setup behind it. ## Supply chain attack on arrayref DevFeed: [Supply chain attack on arrayref]() Original publisher: [Read original article]() Author: Manish Goregaokar Published: 2026-08-20T00:00:00Z Content type: news Language: en Sources: [Rust Blog]() Topics: [Rust](), [Security]() Tags: [local](), [payload](), [research](), [rust](), [security](), [supply-chain]() ### AI overview The Rust Security Response Team confirmed a supply-chain attack involving malicious crates. A compromised build script downloaded a malicious payload, leading to the deletion or yanking of affected versions and the locking of a potentially compromised account. Developers are advised to inspect their local Cargo registry cache for the listed crates and versions. ### Source excerpt What happened On 2026-08-20 at 7:15 UTC we got a report that the proc-macro1 crate was malicious. The Rust Security Response Team verified this to be the case: the crate had a build script that was downloading a malicious payload. This crate proc-macro1 and others like it (proc-macro-en, aovine, arone, aronenao, tinymember) have been deleted. Furthermore, we discovered that the popular arrayref crate had recently been republished and made to depend on this crate, with the most recent versions yanked. We have removed the malicious version and unyanked the maliciously-yanked versions. Other crates by that author (internment, append-only-vec) were also affected so we have done the same for those, and locked the account as a precaution. We do not believe the author of arrayref to be acting maliciously, but their computer or credentials are likely compromised, and we are attempting to contact them. What you need to do We recommend you check your local dependencies to ensure these crates were not pulled in. Here are the malicious versions that we deleted from crates.io: append-only-vec@0.1.9: published at 2026-08-20T07:37:49Z, deleted at 2026-08-20T09:25:24Z. Online for 107 minutes. arrayref@0.3.10: published at 2026-08-20T07:15:00Z, deleted at 2026-08-20T08:41:40Z. Online for 86 minutes. internment@0.8.7: published at 2026-08-20T07:34:07Z, deleted at 2026-08-20T09:04:11Z. Online for 90 minutes. proc-macro1, proc-macro-en, aovine, arone, aronenao, tinymember (any versions). You can quickly check if these crates have been used locally by going through ~/.cargo/registry/cache with this command: find ~/.cargo/registry/cache -type f \( \ -name 'append-only-vec-0.1.9.crate' -o \ -name 'arrayref-0.3.10.crate' -o \ -name 'internment-0.8.7.crate' -o \ -name 'proc-macro1-*.crate' -o \ -name 'proc-macro-en-*.crate' -o \ -name 'aovine-*.crate' -o \ -name 'arone-*.crate' -o \ -name 'aronenao-*.crate' -o \ -name 'tinymember-*.crate' \ \) -print Thanks We'd like to thank the Research T ## Running the WorkOS API locally DevFeed: [Running the WorkOS API locally]() Original publisher: [Read original article]() Author: WorkOS Published: 2026-08-17T20:30:39Z Content type: tutorial Language: en Sources: [WorkOS Blog]() Topics: [API](), [Testing](), [Development](), [servers](), [SDKs](), [OpenAPI Specification](), [Authentication](), [Open Source]() Tags: [api](), [authentication](), [automated](), [backend](), [bun](), [docker](), [javascript](), [linux](), [local](), [macos](), [npm](), [open-source](), [openapi](), [python](), [tests](), [windows]() ### AI overview This tutorial introduces WorkOS Emulate, an open-source local WorkOS API server for development and automated testing. It explains how to run it locally or in CI, connect WorkOS SDKs by overriding the base URL, and use seeded data for repeatable authentication and integration tests without contacting a live WorkOS environment. ### Source excerpt WorkOS Emulate runs the WorkOS API on your own machine, so your tests can seed real data, drive full login flows, and force failures without touching prod. ## OpenAI joins PORTS-Pike project DevFeed: [OpenAI joins PORTS-Pike project]() Original publisher: [Read original article]() Published: 2026-08-17T05:00:00Z Content type: news Language: en Sources: [OpenAI News]() Topics: [datacenter](), [OpenAI](), [Nvidia](), [jobs]() Tags: [data-center](), [energy](), [global-affairs](), [infrastructure](), [jobs](), [local](), [nvidia](), [openai](), [partnership]() ### AI overview OpenAI has agreed to secure approximately 8 gigawatts-IT at the PORTS-Pike Technology Campus in Ohio in partnership with SB Energy, NVIDIA, and the U.S. Department of Energy. The project is expected to create construction and long-term operating jobs, fund community priorities, and support local infrastructure. Its data center will pay its energy and infrastructure costs and use closed-loop, air-cooled cooling systems to reduce ongoing water demand. ### Source excerpt OpenAI joins PORTS-Pike project, expanding community investment and supporting thousands of Southern Ohio jobs ## The Ghost Site Resurrector: How Junior Designers Can Turn Digital Abandonment into Cash DevFeed: [The Ghost Site Resurrector: How Junior Designers Can Turn Digital Abandonment into Cash]() Original publisher: [Read original article]() Author: Alex Harper Published: 2026-08-12T11:40:00Z Content type: article Language: en Sources: [Web Designer Depot]() Topics: [Web](), [Artificial Intelligence](), [Google]() Tags: [2026](), [ai](), [ai-web-design](), [building](), [business](), [conversion-optimization](), [design](), [digital-transformation](), [framer](), [framer-ai](), [freelance-web-design](), [freelancing-clients](), [ghost-websites](), [junior](), [junior-designer-tips](), [local](), [local-business-marketing](), [mobile-optimization](), [outdated-websites](), [responsive-design](), [search](), [seo-optimization](), [small-business-websites](), [smartphone](), [ui-modernization](), [ux-improvements](), [web-design](), [web-design-side-hustle](), [website-redesign](), [website-refresh](), [wix-adi]() ### AI overview The article presents the "Ghost Site Resurrector" strategy for junior web designers: identify local businesses with neglected websites, create a visual redesign mockup using tools such as Framer AI or Wix Harmony, and use the transformation to sell website refresh projects. It claims this approach can generate $1,000-$2,000 per project with less than four hours of total engagement. ### Source excerpt Most websites aren't broken--they're just abandoned. That forgotten, outdated site sitting on page two of Google could be a $1,500 opportunity hiding in plain sight. Welcome to the Ghost Site Resurrector strategy--where neglected businesses become your fastest path to cash. ## \[webapps\] Ray 2.56.0 - Directory Traversal & Local File Inclusion DevFeed: [\[webapps\] Ray 2.56.0 - Directory Traversal & Local File Inclusion]() Original publisher: [Read original article]() Author: Richard Howe Published: 2026-08-11T00:00:00Z Content type: article Language: en Sources: [Exploit-DB.com RSS Feed]() Topics: [webapps](), [Exploit]() Tags: [exploit](), [inclusion](), [local](), [multiple](), [webapps]() ### AI overview An Exploit Database entry describing directory traversal and local file inclusion vulnerabilities in Ray 2.56.0, affecting web applications across multiple platforms. ### Source excerpt Ray 2.56.0 - Directory Traversal & Local File Inclusion ## Meta is back with Muse Glimmer: local, agentic, multimodal, and open source DevFeed: [Meta is back with Muse Glimmer: local, agentic, multimodal, and open source]() Original publisher: [Read original article]() Author: Pedro Cuenca; merve; ben burtenshaw; Aritra Roy Gosthipaty Published: 2026-08-10T00:00:00Z Content type: article Language: en Sources: [Hugging Face - Blog]() Topics: [vlm](), [multimodal](), [Artificial Intelligence](), [hugging face](), [Benchmark](), [coding]() Tags: [agentic](), [artificial-intelligence](), [benchmark](), [hub](), [hugging-face](), [images](), [llama-cpp](), [llms](), [local](), [meta](), [model](), [multimodal](), [muse](), [open-source](), [videos](), [vllm](), [vlm](), [vlms]() ### AI overview Hugging Face presents Muse Glimmer, a local, agentic, multimodal, open-source 30B-parameter vision-language model developed with Meta. The article outlines its vision and language architecture, benchmark context, optional speculative decoding for faster generation, and support for both images and videos. ### Source excerpt We're on a journey to advance and democratize artificial intelligence through open source and open science. [Next page]()