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Open Source
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Google Summer of Code 2026 With the Kotlin Foundation: Recap
The Kotlin Foundation wrapped up its fourth Google Summer of Code program in 2026, supporting two projects by Ayako Hayasaka and Mark Seif Khalil. Ayako implemented tail-call support in the Kotlin/Wasm backend, using return_call and return_call_ref instructions to avoid stack growth in recursive programs, and then found and fixed a missing optimization for return_call in the V8 engine that caused a performance regression. Mark built a database and automated pipeline to collect and structure scattered information about where Kotlin is taught worldwide, covering courses, curricula, repositories, and learning platforms. In Ayako’s benchmarks, several recursive patterns achieved 1.7 to 4.3 times faster execution at a recursion depth of 10,000, and at a depth of one million, the same programs crashed without tail calls but completed successfully with them. The education landscape project now provides a reusable foundation for monitoring Kotlin’s presence in education and identifying trends and gaps.
Deploy with Void
VoidZero has open-sourced Void, a toolkit for building and deploying full-stack Vite applications to Cloudflare. The release includes three products: Void Platform, Void SDK, and Void CLI, which integrate into a single Vite workflow. The SDK provides file-based routing, database integration via imports, and end-to-end type safety from the database to the user interface. The CLI handles building, migrating, provisioning resources, and deploying with a single command, automatically inferring bindings like databases or AI services. The Platform offers a shared deployment environment with access controls and resource limits, enabling teams to prototype and ship internal apps in minutes.
Apertus 1.5 Release Notes
Apertus 1.5 extends the 8B and 70B open-weight models with image and audio understanding, a thinking mode, and a 262,144-token context window, released under Apache 2.0. The models are a continued pretraining of Apertus 1.0, adding 4 trillion tokens to the 8B model and 2 trillion to the 70B model, for totals of 19T and 17T respectively. Multimodality uses an early-fusion tokenizer with Emu3.5 for images and WavTokenizer for audio, keeping the architecture unchanged and training at text-only speed. Post-training includes SFT, long-context SFT, reinforcement learning with verifiable rewards, DPO, and charter alignment via SDPO, with all data and recipes publicly documented. Evaluation results show competitive performance on reasoning, coding, and multilingual tasks, with the 8B model matching GPT-OSS-20B on translation and outperforming Claude Haiku 4.5, reported transparently via the EvalEval Coalition’s EEE schema.
Meta Muse Spark Open is live on Together AI
Meta Muse Spark Open, an open-weight model for agentic coding, is now available on Together AI as a Day 0 launch partner with a 1-million-token context window on serverless and dedicated infrastructure. The model is trained on real developer work including multi-file refactors, debugging sessions, and long-running tasks, leading to higher first-attempt accuracy and reliable tool calling. It features long-horizon autonomy with planning, observation, and self-correction, computer use for desktop and mobile, multimodal input accepting text, image, audio, and video, and intent commentary that states actions before execution for auditability. Early access customers Factory and Ollama tested the model pre-launch and are offering it to their users from day zero. Serverless pricing is $1.25 per million input tokens, $4.25 per million output tokens, and $0.15 per million cached input tokens.
NVIDIA Run:ai Is Now Open Source as Part of NVIDIA DSX AI Factory Platform
NVIDIA has released the complete Run:ai platform as open source software, expanding the NVIDIA DSX AI Factory Platform and giving customers, developers, and ecosystem partners production-grade AI workload and GPU orchestration capabilities. Run:ai has dynamically allocated GPU resources and managed workloads on Kubernetes across data processing, training, and inference. The release includes the full platform plus four independently adoptable components: KAI Scheduler, GPU Fractioning Operator, KAI Resource Management, and Workload Map. Teams can deploy the stack from the NVIDIA Run:ai repository in the DSX AI Factory GitHub organization or via an NGC Community Product Helm chart, without a paid subscription or enterprise support entitlement. Ecosystem partners including Crusoe, Mirantis, Nebius, OpenNebula Systems, Rafay, Saturn Cloud, Spectro Cloud, and vCluster are integrating the platform or its components into their offerings.
OCP Summit 2026: Powering AI with Open Innovations in Scale-Up, Scale-Out, and Scale-Across Networks
At OCP Summit 2026, Meta unveiled next-generation open networking infrastructure for AI, including IcePack, its first liquid-cooled network rack, and IceCube, a 102.4T switch blade delivering 128×800G non-blocking capacity. The Flattened Planar Fabric (FPF) introduces a multiplane scale-out design where each GPU connects via eight independent 100G links to different switches, reducing latency and enabling larger clusters. Meta also shared its BAG super-spine for multi-site aggregation and Tahan, an Ethernet-based 51.2T scale-up switch for MTIA 300 systems. The company launched the Open Switch Platform Architecture (OSPA) initiative with Microsoft and Alibaba to standardize switch platform hardware and software interfaces. Additionally, Meta announced open-source implementations of MetaRoCE, its RDMA transport protocol optimized for AI cluster networks over Ethernet.
Introducing Clef-omni with full multimodality, plus a faster Clef and a cheaper Clef-flash
Cloudflare introduced Clef-omni, a decision model that natively handles audio, video, image, and text inputs in a single pipeline, built on a Qwen3-Omni mixture-of-experts backbone with text-to-speech components removed. Unlike cascading pipelines, it directly embeds media into a unified sequence and uses two-stage attention routing with lexical grammar to compute confidence scores, trained by freezing the backbone and applying LoRA adapters with label-smoothed cross-entropy and Brier score calibration. The company also cut Clef-flash’s price to $0.038 per million input tokens while reducing its context window from 64k to 24k for the hosted version, based on usage data showing only 0.24% of requests exceed that limit. Clef’s hosted version received speed optimizations at the infrastructure layer without new model weights, and Clef-omni is available open-weight on HuggingFace. Benchmarks show Clef-omni scoring 98.2 on BFCL case exact and 92.7 on API-Bank accuracy, with median text-only decision latency around 130 milliseconds.
Solving defense supply chain visibility through governed data sharing
The Department of War cannot obtain cost transparency across its supply chain of over 200,000 suppliers due to reliance on manual data calls and fragmented spreadsheets. The proposed solution is a federated data exchange where each contractor publishes validated cost and pricing evidence from existing records to named government recipients using open-source sharing protocols. Databricks provides the platform, enforcing governance, access controls, CUI markings, and audit lineage without storing raw records centrally or requiring contractors to adopt Databricks. Small and mid-tier suppliers submit through validated intake forms that produce the same governed data contracts as large primes, requiring no new accounting systems. The reporting obligation already exists through CSDR, FlexFile, and DD Form 1921, so a pilot exchange can launch in months by defining two data contracts on a single program.
Deno is joining Cloudflare
The Deno team is joining Cloudflare to merge workerd and celld, aiming to make self-hosting Workers and Durable Objects radically simpler for developers. Ryan Dahl, creator of Node.js and Deno, explains that Durable Objects provide a powerful abstraction: a distributed singleton with a SQLite database that scales by sharding state and WebSocket connections across machines. He started celld to run this model outside Cloudflare with a single Rust binary and object storage as its only external dependency. Kenton Varda counters the theory that Workers’ unique design creates lock-in, noting that workerd is open source and that celld provides an escape hatch for migration. The merged effort, led by Ryan and Bert Belder, will make self-hosting a first-class supported way to build and run apps using the Workers programming model.
Introducing the Anthropic Cyber Mission
State-sponsored adversaries have gained footholds in critical infrastructure such as power grids, water systems, and transportation networks, while open-source software faces increasing vulnerability exploits. To support defenders, Anthropic launches the Cyber Mission, a long-term commitment that includes the Critical Infrastructure Defense Program and OSS Scanner. The Critical Infrastructure Defense Program provides frontier Claude models, on-site engineers, and threat research to trusted providers like Accenture, CrowdStrike, and Rockwell Automation to secure operational technology. OSS Scanner offers open-source projects free regular security scans from Anthropic’s strongest models, and the expanded Cyber Verification Program gives more defenders access to advanced cyber capabilities. The mission aims to reduce cyber risk over years through collaboration, but challenges remain as verifying and fixing vulnerabilities is slow and depends on people.
Mellum2.1 Gets to Work: A Fast Open Model for Coding Agents
JetBrains open-sourced Mellum2.1, a compact 12B mixture-of-experts model with only 2.5B active parameters, released under the Apache 2.0 license. The architecture is unchanged from Mellum2, so all improvements come from post-training through reinforcement learning now the main training phase. The model trained on millions of sandboxed runs across thousands of real environments to develop agentic coding skills like exploring codebases, editing files, and checking its own changes. Performance evaluations show substantial gains in agentic coding, general coding, competitive programming, math, tool calling, and general knowledge compared to Mellum2 and similar open models like Qwen3.5-9B and Gemma 4 E4B. Mellum2.1 matches Mellum2’s speed and with multi-token prediction serves almost twice as many tokens as Qwen3.5-9B under heavy load.
Introducing Falcon ASR
The Technology Innovation Institute in Abu Dhabi released Falcon-ASR, a 1.6 billion parameter speech recognition model focused on Arabic, especially the Emirati dialect, while also supporting English, French, Spanish, and Portuguese. On the Open Universal Arabic ASR Leaderboard, Falcon-ASR achieved a 20.92% average word error rate across six test sets, outperforming the best published average of 23.17% in the reference snapshot. The model recorded a 22.73% word error rate and 10.19% character error rate on an internal Emirati evaluation, 4.07% better in word error rate than the next best system compared. Training data included background noise, overlapping speech, music, reverberation, telephony effects, speed, and pitch variations to handle diverse recording conditions. Falcon-ASR builds on the Falcon3-Audio architecture and provides word-level timestamps linking transcribed words to audio positions.
JetBrains Joins the Open Source Security Foundation
JetBrains has joined the Open Source Security Foundation (OpenSSF) as a general member. OpenSSF is a cross-industry Linux Foundation initiative that works to secure the software supply chain, hosting projects like Sigstore for signing and SLSA for supply chain integrity, and its AI/ML Security Working Group publishes guidance on signing ML models and safe instructions for AI code assistants. The foundation announced the membership at OpenSSF Community Day Europe in Prague. JetBrains cites the rise of coding agents and AI as creating new security challenges, making it more important for developers to understand and verify code and dependencies, and notes that its own product JetBrains Air addresses these questions. The company aims to collaborate with the industry through OpenSSF to help shape the future of secure software development, as stated by Katherine Druckman, Head of Community and Partnership Engagement.
Everything we launched during Birthday Week 2026
Cloudflare marked its 16th Birthday Week with 46 announcements spanning open source, application security, AI agent economics, and developer platform upgrades. The week began with a new agentic CLI called cf, an open-source generation pipeline called Forge, and EmDash, a serverless CMS with sandboxed plugins. Tuesday focused on Cloudflare’s intention to become a public certificate authority and post-quantum security tools. Wednesday introduced Pay Per Use and the Monetization Gateway, creating an economic model for AI agents to pay creators when using their content. The week closed with features for faster connectivity and broader accessibility.
Together Link: open models in the harness you already use. Start with one command today.
Together Link connects coding agents to over 40 production-tier open models on Together AI, cutting model spend by over 50% compared to premium closed models. It integrates with Claude Code, Claude Desktop, Codex, OpenCode, and Pi without requiring any workflow changes. Open models such as Kimi K3, GLM 5.3, DeepSeek V4.1 Flash, and GLM 5.3 Flash now handle both complex architectural tasks and everyday fixes at a fraction of the per-token cost. A per-session router reads each session’s first task and routes it to either a fast, low-cost model or a frontier model; when no Anthropic key is provided it routes between GLM 5.3 and GLM 5.3 Flash, and Together AI serves the largest share of OpenRouter tokens for these models. Billing uses the existing Together API key with pay-as-you-go or credit packs, and a per-session tracker shows what the session would have cost on Opus 5.5.
Unlocking Data Portability: Preventing Catalog Lock-in with REGISTER and UNREGISTER APIs
The post explains how the REGISTER and UNREGISTER APIs in the Apache Iceberg REST catalog specification enable table portability between catalogs without copying or moving data files. REGISTER attaches an existing table to a new catalog by providing the metadata location, but using it alone creates a split-brain scenario where two catalogs both think they own the table, leading to inconsistent writes and data loss. The UNREGISTER endpoint, contributed to the specification, cleanly removes the table from the old catalog and returns the latest metadata pointer needed by the next catalog. The handoff process combines unregister, receiving the location, and register to ensure exactly one managing catalog at all times. Unity Catalog supports these endpoints in private preview, allowing organizations to move tables between catalogs as their architecture evolves.
Open-sourcing AstaBrief, the fast report-generation model in Asta
AstaBrief is an open-weights 8B-parameter model developed by Ai2 for generating cited scientific reports from a research question and literature excerpts, designed for evidence-grounded outputs. It was trained from Qwen3-8B using supervised fine-tuning on 47K filtered real user queries and direct preference optimization, focusing on data quality. Unlike Asta’s Thinking mode, which uses a multi-step pipeline, AstaBrief writes the full report in a single pass to reduce generation time. In Asta’s Fast mode, it averages 51.1 seconds per report versus 178.5 seconds for Thinking mode, roughly 3.5× faster, while competitive on answer and citation quality. The model and training data are open-sourced on Hugging Face, enabling institutions to deploy behind their own firewall and supporting future open scientific models.
Introducing Clef: our open-source decision models, and new RL fine-tuning platform
Cloudflare released two open-source decision models, Clef and Clef-flash, hosted on Workers AI under an Apache 2.0 license and fully compatible with the Jev API. These models produce bounded structured outputs for agentic workflows, classifying inputs like customer support messages or website domains with typed probabilities and confidence scores. Clef includes a vision encoder and a 64k context window, distinguishing it from text-only decision models such as Jev, and currently leads the Jev Decision Index benchmark. The models demonstrated lower latency than alternatives, with Clef classifying a website in 2.2 seconds versus 4.7 seconds for Cloudflare’s fastest general LLM, while Clef-flash offers even faster inference at 38.8 ms median latency. Cloudflare also debuted a reinforcement learning fine-tuning platform that lets customers adapt Clef to their specific use cases using their own data.
Introducing Olmo-core 3: Open, scalable training infrastructure for large MoEs
Olmo-core 3 is an open training infrastructure upgrade for large mixture-of-experts (MoE) models, designed to scale to trillion parameters while preserving efficiency. It switches from FSDP to a DDP-based system that keeps experts resident on GPUs and routes data to them, avoiding weight gathering overhead. The system combines expert, pipeline, and distributed optimizer parallelism with optimizations like rowwise expert parallelism, GPU-resident routing, and grouped GEMM. In a benchmark, increasing experts from 8 to 128 while routing each token to four experts kept active parameters at ~3.2B, total parameters grew from 4.6B to 47B with throughput falling less than 5%. The infrastructure supports MXFP8 lower-precision format, achieving about 21% higher throughput than BF16, and has been tested on a 1.2-trillion-parameter model.
One year later: Sovereign AI and the fight for choice
A year after arguing that AI sovereignty means choice, Cloudflare adds two European open models—EuroLLM and Apertus—to Workers AI, reflecting a year where access to frontier models became constrained and attacks using AI increased. EuroLLM supports 35 languages including all 24 EU official languages, many underserved by existing open models, and was trained on the MareNostrum 5 supercomputer. Apertus, Switzerland’s first fully open multilingual model, was trained on 15 trillion tokens across 1,500+ languages on the Alps supercomputer (10,000+ GH200 GPUs) and outperforms leading models on rare and regional languages. Cloudflare also launches hands-on workshops for government cyber agencies and critical infrastructure operators to build model-agnostic AI security defenses, starting in Singapore in October. The company open-sourced its own security harness that coordinates multiple AI models for vulnerability hunting, ensuring defenses remain operational even if access to one model is lost.
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