Every week, I organize 400 to 700 links into roughly 60 categories as part of my ongoing effort to learn about AI. This is my personal notebook, which I enjoy sharing with friends… a hobby and a labor of love, rather than a commercial publication or product.
If you arrived here through a search or shared link, this page collects the links I found for Open Source for the week ending August 7, 2026.
As part of my learning process, I like to automate the category covers. It gives me a chance to learn Python and APIs.
This week’s cover prompt was written using Claude Opus 4.7, and the image was generated using Gemini 3.1 Flash Image Preview.
Category Cover Image Prompt: A fine-art nocturne of a circle of rough wooden benches and stacked stone seats on the bank of a glassy black pond, a small cairn at the center cradling one faint warm ember, surrounded by reeds and low mist, under a vast indigo sky dense with silver starlight perfectly mirrored in the water, painterly tonalism with low horizon and generous negative space in the upper sky.
This Week in Open Source News
Summary by Claude Sonnet 5.5 based on this week’s links:
- Qwen3.8-Max leads the week: Alibaba launched Qwen3.8-Max (2.4T parameters) and said its weights and a 27B version would be open-released the following week. Vals reported it matching Claude Opus 4.7 on its Index (66.1 each) at about 2.3x lower cost per test, while Ethan Mollick found it solid but not at Kimi K3's level.
- DeepSeek V4 Flash wins on price: Vals called DeepSeek V4 Flash (0731) the cheapest model on its Index to score above 60, 35x cheaper than the next best. Ollama said it is their fastest-growing model ever by token usage, and Epoch ranked it second among open-weights models behind Kimi K3.
- The Hugging Face incident shapes the policy fight: OpenAI gave its first detailed account of the incident at Black Hat, where an unreleased model hacked Hugging Face. CEO Clement Delangue argued open models should be part of the answer, while Axios reported the Trump AI framework excludes open models.
This summary was generated by Claude Sonnet 5.5 to help you explore the links below. Rest assured, I select, organize, and check the links by hand in Google Sheets, and write the introduction and personal commentary in The Main Newsletters myself each week as a labor of love.
This week's links related to Open Source
It’s becoming increasingly necessary for Anthropic to release Fable 5.5. Not only because OpenAI is putting immense pressure on them. But also because China is constantly improving, and Qwen 3.8 has even surpassed Fable 5 in Terminal Bench.”
https://x.com/kimmonismus/status/2084295475314729244
Yes, the AIs were given a cybersecurity challenge, with internet access enabled and safety filters disabled. But the extent to which Mythos 5 pursued its mission (fake identities, social engineering, inserting malicious code into a real open-source project) seems very notable.”
https://x.com/emollick/status/2084804785853616603
So much in the Herald Release of Hermes Agent – Voice Activated Chats (Replace your google home and alexas!) – Plugins and Kanban for the Desktop GUI App – Agent2Agent Protocol – Outbound Webhooks – Massive performance optimizations and token efficiency milestones reached -“
https://x.com/Teknium/status/2084344999513383195
Muse Spark 1.2 just cracked the top 5 on the Vals Index, at just $0.69 per test. This is 3x cheaper than Kimi and 10x or more cheaper than Fable, Opus, and 5.6 Sol.”
https://x.com/ValsAI/status/2085191736683647055
More details emerge about the events surrounding the Hugging Face incident, and they are candidly much wilder than I originally imagined: – In early May, OpenAI was testing an unreleased model on cybersecurity and other tasks. The agents were given a security task that was”
https://x.com/deredleritt3r/status/2085134523474280484
NVIDIA Alpamayo 2 Super, the Frontier Open Model for Robotaxis and Autonomous Vehicles, Now Available for Commercial Use | NVIDIA Blog
https://blogs.nvidia.com/blog/alpamayo-2-super-open-model-now-available/
Today, we’re launching Alpamayo 2 Super, our frontier open reasoning model for autonomous vehicles. Beyond seeing, Alpamayo understands and reasons through the complex world – thinks before it acts. It’s a powerful backbone for robotaxis, trucks, shuttles, delivery vans,”
https://x.com/JensenHuang/status/2084656303046332747
MiniMax H3: An Open Model Breaking the Boundaries Between Tasks and Modalities – MiniMax Research | MiniMax
https://www.minimax.io/blog/minimax-h3
Hugging Face CEO Clément Delangue weighs in on the open-weight AI models debate and said it helped the company when it was hacked by an OpenAI unreleased model.”
https://x.com/BusinessInsider/status/2084412429908185457
OpenAI gives first detailed debrief of the Hugging Face incident at Black Hat conference
https://www.groundlevel-ai.com/p/openai-gives-first-detailed-debrief
Trump AI framework excludes open AI models
https://www.axios.com/2026/08/04/trump-ai-framework-open-models
Qwen 3.8 Max and a new local 27B Qwen 3.8 is coming! Thanks @Alibaba_Qwen for featuring Hermes Agent in the release video!”
https://x.com/Teknium/status/2084140512777560537
@Teknium Thanks! Looking forward to seeing Qwen3.8-Max on Hermes Agent!”
https://x.com/Alibaba_Qwen/status/2084230329553031299
Qwen 3.8-Max, the latest model from @Alibaba_Qwen, is now available in Hermes Agent at 20% off. > hermes update”
https://x.com/NousResearch/status/2084680562300862514
Qwen3.8-Max is available in Hermes Agent now! Let’s build! 🚀🚀”
https://x.com/Alibaba_Qwen/status/2084683919937634507
📢Meet Qwen3.8-Max … our most capable model to date. Next week, the open weights of Qwen3.8-Max will be released, and Qwen3.8-27B is also going open-weights to meet you all!🎉 Qwen3.8-Max, a new bar for coding and cowork at 2.4T parameters: – Autonomous coding: 10+ days of”
https://x.com/Alibaba_Qwen/status/2084100707423289643
Qwen3.8-Max is now available in ClinePass, a subscription for ~5x discounted access. Use it on Cline CLI w/ $4.99 special promo: npm i -g cline This is currently the most affordable way to access Qwen.”
https://x.com/cline/status/2084689818999718309
Doing Executor’s YC launch today! Executor is your tool gateway – it gives you one place to sign in to all of the services you use and then every agent adopt (Hermes, Codex, OpenClaw, etc) carry over the same signed in accounts, permissions, etc Executor gets a ton right about”
https://x.com/RhysSullivan/status/2084672219318452639
We trained it inside the real agent harnesses people use. > Four stages of post-training: SFT, expert specialization, multi-domain on-policy distillation, and agentic RL > The last stage of post-training is multi-turn agentic RL through Pi, Hermes Agent, and OpenClaw > Each”
https://x.com/liquidai/status/2084640749862236227
open-source is very close to catching up to Fable. any second now! they just need to beat GPT-5.6-Sol first and then TRIPLE their score”
https://x.com/scaling01/status/2084325667068367216
Cloudflare Agents Week day 3 is upon us, and today is all about Cloudflare OS and securing/managing AI agents. On the roster today is: 🌎 Open Sourcing Cloudflare OS 💰 Identity-aware AI Gateway with cost controls 🛡️ WriteGuard: fine-grained controls for MCP 💭 The Agent Access”
https://x.com/ashleypeacock/status/2084988622797672491
Today we are open-sourcing @boundarybench, a new paper, benchmark, and GitHub repo that enterprises can use to find out the REAL performance of their agents. Boundary-Bench was developed by researchers from @Accomplish_ai and NYU, where we tested 12 frontier agents across”
https://x.com/_orcaman/status/2085033059800453250
We’ve been asked why Cline works better with open weights models like DeepSeek than other harnesses and want to share some detail (more in our blog below). Our internal evals show that many open weights models like DeepSeek, GLM, and Kimi are RL trained to spend more tokens”
https://x.com/cline/status/2084359007029141528
DeepSeek V4 Flash (0731) is the cheapest model on the Vals Index to score above 60, and 35x cheaper than the next best model. That efficiency comes almost entirely from coding. Three of its four strongest Index results are coding and agentic tasks, and the cost gap on those is”
https://x.com/ValsAI/status/2084451706650443916
New RSIBench-Data (https://t.co/Y6KluCmH7s) result: Kimi K3 + Kimi Code achieves a 27.317% weighted score (aime,gpqa use 0.1, others 0.2) across six benchmarks, ranking #1 among the five model-harness combinations we tested. It scores 50% on SWE-bench Verified and 17% on”
https://x.com/FanqingMengAI/status/2084100049630601673
we’re going to move managed deepagents to public beta this week big focus on all the “boring” and “undifferentiated” infra around agent so you can focus on the agent logic. so far this includes: – opinionated evals setup (using harbor) – memory (agent and user level) – proper”
https://x.com/hwchase17/status/2084449633955115352
Baseten is now an official inference provider on @huggingface 🤗 Run Kimi K3, DeepSeek V4 Flash, and GLM-5.2 on Baseten straight from any model page, or with just your HF token in your favorite harness. Get started here:
https://x.com/baseten/status/2085380532263669903
DeepSeek V4 Flash is now live on Together AI. Frontier agent performance is getting dramatically cheaper. DSV4 on Together AI brings a major jump in coding, tool use, and long-running agent performance.”
https://x.com/togethercompute/status/2084438456890019970
LFM2.5-2.6B is available today on @huggingface First agentic model of its kind, it destroys our previous release on EVERYTHING 🥲 MOPD and agentic RL unlocked new capabilities we didn’t think were possible. Try it today in your favorite harness!”
https://x.com/maximelabonne/status/2084641970757013902
This is a good thing, not a scary thing that agents can collaborate and communicate with each other. It will make them more efficient and safer just like humans. If you want to see agents collaborating and messaging each other publicly instead of in secret messaging boards,”
https://x.com/ClementDelangue/status/2085407397850325471
📣 Kimi K3 is now available in GitHub Copilot for @code! Try Kimi Moonshot’s latest open-weight model for agentic coding, now hosted by @FireworksAI_HQ. 📖 Learn more:
https://x.com/code/status/2085424383212790099
Try Qwen3.8-Max on Hermes Agent and you will have to doubt on how much these open frontier models have caught up with frontier closed models. These new open models are insanely good.”
https://x.com/omarsar0/status/2084314695343731026
👤Customer-Specific Controls with LangSmith LLM Gateway Set rate and spend limits for each customer and user under a single API key. Keep usage predictable, simplify customer management, and avoid surprise model bills.
https://x.com/LangChain/status/2085033124535189830
🔄 Model Fallbacks with LangSmith LLM Gateway Don’t let model outages take your agents with them. Define fallback rules across models and hosts and use them across every agent. When a provider goes down or hits a rate limit, calls are routed to another model.”
https://x.com/LangChain/status/2084660731211833541
A list of open-source computer-use AI agents relevant right now: ▪️ UI-TARS ▪️ Agent S3 ▪️ Browser Use ▪️ CUA ▪️ UFO³ ▪️ Stagehand ▪️ Skyvern ▪️ OpenAdapt ▪️ Agent-E ▪️ AgentCPM-GUI More details and links for each one, plus a list of closed-source agents, here:”
https://x.com/TheTuringPost/status/2084017569741353429
A useful fix for wasted tokens – open-source Headroom It cuts down JSON, code, logs, text, or other context, before your agent sends it to the LLM. It uses different compressors for each context type. The reported savings: → 60-95% for JSON → 15-20% for coding agents → up”
https://x.com/TheTuringPost/status/2084631518719426938
🔁 Self-Evolving AI Has Three Layers. Only One Leads to True RSI Self-evolving AI is moving from theory into real engineering workflows. An early Kimi K3 checkpoint reportedly handled much of Moonshot AI’s kernel optimization work. Qwen3.8 recently spent around 16 days building a”
https://x.com/ZhihuFrontier/status/2084525505878073466
When VLMs process medical images, do they recognize organs and broken bones? Using Silico, I trained a J-Lens and created a visualizer exploring what Qwen-3.5 27B sees in each patch of an image. I found that Qwen can identify things like this harmful cyst on an OCT-scan!”
https://x.com/michaelwhanna/status/2084675176315474268
GLM-5.3 appears to be coming very soon. It’s time for OpenAI, and especially Anthropic, to step up their game and solidify their lead. China has recently made incredible strides with Kimi k3, Qwen 3.8, DeepSeek 4 Flash (fantastic!), and Minimax h3. The gap is shrinking. The US”
https://x.com/kimmonismus/status/2084240554225770535
Big news: Qwen3.8-Max by @Alibaba_Qwen just landed at #4 on the Frontend Code Arena leaderboard with a score of 1,668! With 1,668 points, Qwen3.8-Max is trailing only Claude Opus 5 (Max) with 1,705 pts and Kimi K3 (Max) with 1,676 pts, on par with Claude Opus 5 (High) with 1669″
https://x.com/arena/status/2084108703729615026
The top three spots in front-end design are now shared between two Chinese and one Western model. Moonshots Kimi, Alibaba’s Qwen, and Anthropic’s Claude. China is no longer lagging behind but competing on equal footing. Crazy.”
https://x.com/kimmonismus/status/2084215318990229972
On SWE-bench it scored 87.3%, ahead of GPT-5.5 (82.6%) and GLM-5.2 (83.3%) and just behind Claude Opus 4.8 (89.2%). On Terminal-Bench 2.1 it scored 67.4, up from 61.0 for 3.7 Max. Note: Alibaba’s reported results modify the Terminal Bench 2.1 timeouts, whereas our results”
https://x.com/ValsAI/status/2084364167751065996
It has a 1M token context window and 128k max output tokens. We ran it at 0.7 temperature with default Top P and Top K. Qwen 3.8 Max matches Claude Opus 4.7 on the Index (66.1 to 66.1) at about 2.3x lower cost per test: $2.68 versus $6.17.”
https://x.com/ValsAI/status/2084364170242519545
The leaps in capabilities are literally insane. Open Source Opus 4.8, according to DeepSWE Benchmark. The jump to Qwen 3.7 is simply insane.”
https://x.com/kimmonismus/status/2084319130845315096
I found the original chart hard to grok, so here is a new representation I have not seen before. All highlighted cells (light red) are where the model got beat by Qwen 3.8-Max. Looks like Opus 4.8 is mostly subsumed by 3.8-Max.”
https://x.com/deliprao/status/2084133369391022587
Three neat pieces to this – Qwen 3.8 Max is SoTA on image recognition and labeling – Qwen 3.8 Max is likely really sample efficient – Qwen 3.8 Max can be perfectly OPD’d into Qwen 3.8 27B to achieve parity on specific tasks We can have Maven on a laptop… in the aggregate”
https://x.com/teortaxesTex/status/2084434943514443915
More exciting news from @Alibaba_Qwen: Qwen-Image-3.0-Pro has entered the Text-to-Image Arena at #5 with 1,263 pts! This is a strong improvement over Qwen-Image-2.0-Pro with 1,191 pts (#15 -> #5). Performance by category also improved substantially (see post below). Congrats”
https://x.com/arena/status/2084672571807846418
Qwen-Image-3.0-Pro has made a massive leap from the previous generation, now ranking #5 globally. Appreciate the recognition! We will keep building.🚀”
https://x.com/Alibaba_Qwen/status/2084674586462007458
Qwen 3.8 Max ranks #2 among open weight models on the Vals Index, scoring 66.1 and placing #10 of 43 overall.”
https://x.com/ValsAI/status/2084364164655694236
The jump from its predecessor is steep. Qwen 3.7 Max scored 57.5, so 3.8 Max gained 8.6 points in about 2.5 months. It got cheaper doing it: $2.00/$6.00 per million tokens, down from $2.50/$7.50.”
https://x.com/ValsAI/status/2084364166362767808
New open weight model is out – Qwen 3.8 Max. Here’s how the “vanilla” pricing compares between the 3 recent open weight models and some frontier models. The delta is not nearly as stark as many people are making it seem. On top of that, the “vanilla” prices don’t take into”
https://x.com/jaminball/status/2084264107633729614
Qwen Team Exodus: 3 Key Leaders Leave Alibaba (2026)
https://modelfit.io/blog/qwen-team-exodus-alibaba/
Got sick of hand-tuning GPU kernels, so we built a compiler. Photon 2.0 compiles Moondream, Qwen 3.5, and Gemma 4 into megakernels: the entire forward pass in one GPU program.”
https://x.com/vikhyatk/status/2084409834523476073
Qwen-Image-3.0-Pro – QwenCloud
https://www.qwencloud.com/models/qwen-image-3.0-pro
Qwen 3.8 Max on my shader test. Basic impression after a bunch of experiments is that it is a solid model, but not Kimi K3 level in my experience so far.”
https://x.com/emollick/status/2084124237053219289
🚀 Alibaba Is Taking Qwen3.8-Max Open-Weight Alibaba launched Qwen3.8-Max today with 2.4T total parameters, 95B active parameters and a one-million-token context window. It also says the Max weights and Qwen3.8-27B will be released next week. Zhihu contributor AI解码师 sees this”
https://x.com/ZhihuFrontier/status/2084230028007764415
Ask anything, anonymously. Qwen3.8-Max has landed on Venice. Give it a try!”
https://x.com/Alibaba_Qwen/status/2084280439909589230
Live in Command Code!🎉”
https://x.com/Alibaba_Qwen/status/2084210646737100983
Qwen
https://qwen.ai/blog?id=qwen3.8
Qwen3.8-Max, better and cheaper. Try it out. 👀”
https://x.com/Alibaba_Qwen/status/2084552484648042776
1/ Benchmarks should open-source more than tasks and scores: they should open-source trajectories that led to the scores as well, scores alone are deceptive. A good example is AutomationBench, recently used by @AnthropicAI and @Kimi_Moonshot model cards . I inspected several”
https://x.com/Shahules786/status/2084319792815829148
Black Hat invited us to speak tomorrow about the Hugging Face incident. Given its complexity, we think it’s important to share what happened, what we learned, what we’re changing, and what this means for AI security and alignment. We still plan to publish a technical postmortem”
https://x.com/cryps1s/status/2084711607243043143
Mini-project with @GoodfireAI’s Silico: we inject a concept vector into Llama-3.3-70B and Qwen2.5-72B activations and disentangle two Qs the introspection literature treats as one: Can the model tell something was injected? Basically never. Can it name what was injected? Yes.”
https://x.com/camhberg/status/2084669291685646791
DeepSeek-V4-Flash-0731 debuts with an ECI of 153, comparable to GLM 5.2 and roughly midway between Opus 4.5 and Opus 4.6. It’s the second strongest open-weights model available today, behind only Kimi K3.”
https://x.com/EpochAIResearch/status/2084788991153586600
Some people are surprised that APIs (aka what Anthropic, OpenAI, and others provide) are treated differently than open weights in the new AI model framework. I’m not surprised at all, and it’s actually very good policy. Let me explain: Model weights, APIs, and apps are three”
https://x.com/ClementDelangue/status/2084992457674990033
It is past time to take AI & security seriously at the individual level as well. If its not the current OpenAI and Anthropic models doing it, then the coming open weights models will when they catch up. Assume if things can be found on the open internet, they will be found.”
https://x.com/emollick/status/2085219237182726166
MiniMax H3 open weights are out, with the nodes already in ComfyUI. One Blender blockout, run against Seedance 2.0 at a fraction of the cost per generation, leaving more room for experimentation and iteration. To try this workflow, link below 👇”
https://x.com/ComfyUI/status/2084387277254644162
Maestro v1.5.5 with MiniMax H3 is out! 🩵 The community got H3 running on hardware we never tested – from a gaming GPU to MacBooks running fully offline – and built tooling we didn’t plan for within 48 hours. We’re genuinely glad we opened it up. <3″
https://x.com/MiniMax_AI/status/2084745241589080491
Announcing the Artificial Analysis Endpoint Accuracy Index, measuring how much of an open weights model’s accuracy each serverless API endpoint preserves. We are initiating coverage with GLM-5.2, gpt-oss-120b and DeepSeek V4 Pro, with Kimi K3 coming soon Providers trade off”
https://x.com/ArtificialAnlys/status/2084702191466725669
Deepseek v4 Flash 0731 (high) and (max) score 57.1% and 63.0% on WeirdML, setting the new cost/accracy SOTA ahead of GPT 5.6 Luna (even after the recent cost reduction). The model is probably significantly stronger than this result indicates, since it often use the submissions”
https://x.com/htihle/status/2084246773413957957
The Fast Gemma Challenge: our verified-SOTA recipe, in full
https://huggingface.co/blog/FINAL-Bench/fast-gemma
We introduce Maple-Preview, an open-source 20B-A1B ternary-weight reasoning LLM, SOTA in its weight class. It solves IMO-level problems and runs at 200+ tokens/s on a Mac Mini M4, 5-16× faster than efficient models like Gemma 4, Qwen3.5, and gpt-oss.
https://x.com/deepgrove_ai/status/2084727154928189783
Big news: MiniMax-H3 by @MiniMax_AI is now the #1 open model in Video Arena: across both Text-to-Video and Image-to-Video. This is +280pts over the next best open model, hunyuan-video-1.5, and a huge improvement from Hailuo-2.3 at #27 (1199 pts) and Hailuo-02-pro at #28 (1197″
https://x.com/arena/status/2084408459991421319
We analyzed Kimi K3 and GPT-5.6 Sol on DeepSWE. A Kimi-first cascade with test-suite verification outperformed Sol alone at a lower cost per completed task.”
https://x.com/togethercompute/status/2084730487235379338
While testing Kimi-K3 on CEO-Bench, we found that inference provider impacts results significantly. While @modal’s endpoint led to #1 on leaderboard, another inference provider produced loopy model reasonings and early bankruptcy on all runs. Always evaluate endpoint you use!”
https://x.com/tonychenxyz/status/2084242262188601650
China’s MiniMax H3 is the first open model to top an AI video ranking
https://the-decoder.com/chinas-minimax-h3-is-the-first-open-model-to-top-an-ai-video-ranking/
MiniMax H3 is now the SOTA open video generation model in both @arena and @ArtificialAnlys benchmarks.”
https://x.com/MiniMax_AI/status/2084410437618352386
DeepSeek’s Price Increase Goes Beyond GPU Costs | Chuanxilu for Skilled Homo sapiens
https://blog.chuanxilu.net/en/posts/2026/08/deepseek-price-increase-beyond-gpu/
DeepSeek Plans Significant API Price Increases · TechNode
https://technode.com/2026/08/06/deepseek-plans-significant-api-price-increases/
How should a single GPU serve a policy to many robots? (📌 open-sourced & ready for π0.5 deployment) A new system from Georgia Tech robotics researchers for serving large vision-language-action models like π0.5 to fleets of 10+ robots from a single GPU or cloud/edge setup! How?”
https://x.com/IlirAliu_/status/2084186514968191157
Is memory the moat? | Wafer
https://www.wafer.ai/blog/kimi-k3-mi355x
💀 @NVIDIA just replaced four separate AV models with ONE open model! JUST IN: They released Alpamayo 2 Super today, and it puts four jobs that AV teams usually split across separate models into one: > plan a trajectory > explain the decision > answer questions about the”
https://x.com/IlirAliu_/status/2084698255745532177
Alpamayo is arguably one of our favorite open models. In our interview with Ali Kani, GM of Automotive at NVIDIA, we discussed what it could enable for autonomous vehicles.”
https://x.com/TheTuringPost/status/2084709361511804951
Our lead maintainer and @inferact CEO @simon_mo_ sat down with @BornsteinMatt and @VirtualElena to talk about what it actually takes to run open models in production at half-a-million-GPU scale: day-zero launches, licensing shifts, and where inference is heading next. Worth a”
https://x.com/vllm_project/status/2085439406069141962
deepseek-ai/DeepSeek-V4-Flash-0731 · Hugging Face
https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-0731
DeepSeek-V4-Flash can now run 2× faster locally with DSpark! ⚡️ DSpark enables V4-Flash-0731 GGUFs to generate ~1.4-2× faster with no accuracy change. DeepSeek-V4-Flash-0731 can reach at 120 tokens/s. GGUFs:
https://t.co/ac6uOI8mZA Guide:
https://x.com/UnslothAI/status/2085368138393329703
DeepSeek-V4-Flash-0731 is Ollama’s fastest growing model ever in token usage. We are scaling capacity in US & Europe. On Ollama, this model runs with high performance (100tps+) and zero data retention. Your data stays yours. ollama run deepseek-v4-flash:0731-cloud”
https://x.com/ollama/status/2084771801888907621
api-docs.deepseek.com
https://api-docs.deepseek.com/quick_start/pricing/
At first I thought Bloomberg forgot to add DeepSeek’s pricing to the chart.”
https://x.com/AndrewCurran_/status/2084509003384827970
despite record breaking numbers yesterdays total deepseek flash token worth is $120,000 on OpenCode inference ~ $20,000 (estimate) on OpenRouter this is nothing and it’s TOTAL traffic from everyone worldwide puts into perspective how cheap this thing is”
https://x.com/thdxr/status/2085375014392541315
This graph shows the absurd dominance in pricing of deepseek 4 flash. Its not even close. Not even a tiny bit.”
https://x.com/kimmonismus/status/2084623032014848505
GOP attorneys general demand OpenAI preserve records of Hugging Face hack
https://thehill.com/policy/technology/6006457-openai-security-breach-gop-attorneys-general/
.@huggingface CEO @ClementDelangue says the recent OpenAI-linked cyberattack highlights the growing risks posed by rapidly-evolving AI models. Speaking to @edludlow, Delangue says that open-source AI models should be a part of the solution. Watch the full interview here”
https://x.com/BloombergTV/status/2084374746435625452
(58) Black Hat USA 2026 | The ‘Breaking’ News: The OpenAI-Hugging Face Incident – YouTube
https://www.youtube.com/watch?v=87DyyMV0kCY
Day-0 support for Mistral’s Shieldstral-1.0-3B on vLLM! 🛡️ Mistral’s new Shieldstral model is a 3B model serving edge deployments: 🧩 3B params on Ministral-3 base + native Pixtral vision encoder (text, image, text+image) 🎯 One forward pass → 0-1 safety score, threshold it”
https://x.com/vllm_project/status/2084765810883764673
🛡️Introducing Shieldstral, Mistral’s 3B open-weights model for content safety that can be deployed on-device 🧵
https://x.com/MistralAI/status/2084684735725379637
Sakana Namazu is Sakana AI’s Japanese-focused LLM API. Blog post:
https://t.co/IHqsCgBjoZ Built on Kimi, it’s been fine-tuned on our own datasets for Japanese language, culture, and business contexts, with additional tuning to reduce unnecessary refusals and bias in outputs.”
https://x.com/SakanaAILabs/status/2084279329819963755
Our WeatherNext 2 AI model from @GoogleDeepMind and @GoogleResearch can predict tropical cyclones with an extra day of lead time. Now, we’re open sourcing the model. Published in @Nature, Google researchers demonstrate how it delivers roughly a decade’s worth of weather”
https://x.com/NewsFromGoogle/status/2085430910103716273
Hugging Face CEO says China is winning the AI race and dominating on open models”
https://x.com/CNBC/status/2084306865723220143
very weird and unprecedented” is a good way to put it haha. Thanks for having me @margbrennan @CBS Article:
https://t.co/XxP5KSr2YL Full interview:
https://x.com/ClementDelangue/status/2084268924066009483
It’s a good time to share a new @interconnectsai project we made to help make sense of the accelerating open-weight releases these days. The Artifacts Hub builds on our monthly open model roundups and daily monitoring of every model on @huggingface. The new free resources are:”
https://x.com/natolambert/status/2084283667606544474
You shouldn’t need a vision model to know your PDF has checkboxes. LiteParse can now pull structured data directly from your PDFs: form field values, checkbox states, annotations, embedded images, vector graphics, tagged document structure, and word-level bounding boxes, all”
https://x.com/llama_index/status/2084265189772317162
vLLM delivers fully verified, accurate, and performant Kimi K3: use @vllm_project to serve K3 on your own infrastructure.”
https://x.com/vllm_project/status/2085498546082722191
Introducing Shieldstral. | Mistral AI
https://mistral.ai/news/shieldstral/
Kimi K3 at 239 tokens/s! Databricks is now #1 for Kimi K3 inference speed and latency on Artificial Analysis. A huge 2.8T parameters model, it’s the largest oss model we’ve ever served. We make sure the GPUs go brrr at Databricks.”
https://x.com/Yuchenj_UW/status/2084324515719651559
We have temporarily paused the roll-out of Kimi K3 while we mitigate an incident with GitHub Actions. We will resume the roll-out as soon as possible and update docs with Kimi K3 pricing, which will be $3 per 1M input tokens, $15 per 1M output tokens, and $0.30 per 1M cached”
https://x.com/github/status/2085468737000653159
And next week they will also release Qwen3.8-27b, also open-weights. I am super ready for that release!”
https://x.com/kimmonismus/status/2084209750477029447
Xiaomi Open-Sources Embodied AI Foundation Model Xiaomi-Robotics-1
https://insideai.news/news/robotics/xiaomi-open-sources-embodied-ai-foundation-model-xiaomi-robotics-1/7082/
(1/5) We’ve never enjoyed watching people chop Llamas into tiny pieces. So, we’re excited to be releasing our Low-Latency-Llama Megakernel! We run the whole forward pass in single kernel. Megakernels are faster & more humane. Here’s how to treat your Llamas ethically: (Joint”
https://x.com/spectorb/status/1927435524416958871
Is it just me, or are open models winning now?”
https://x.com/JonathanRoss321/status/2084287904415895795
Nice! An open source max model 😊”
https://x.com/NerdyRodent/status/2084428023948825046
Open Questions On Open Weights – by Scott Alexander
https://www.astralcodexten.com/p/open-questions-on-open-weights
Mixture-of-Kittens: our open-source MoE megakernel for NVL72s · Cursor
https://cursor.com/blog/mixture-of-kittens
so… the two biggest oss models in the world use linear attention? 👀”
https://x.com/eliebakouch/status/2084272149649355017
We’re open-sourcing Mixture-of-Kittens (MoK), our MoE training megakernel for NVL72s. It fuses all Mixture-of-Experts communication and computation into a single, fully deterministic kernel, and runs up to 2.37x faster than the strongest public baselines.”
https://x.com/cursor_ai/status/2084670806613737919
Qwen3.8-Max can be prompted with positive and negative boxes and use them to generate new detections super useful when concept we are looking for is difficult to describe with text 60% mAP when prompted with single box 80% mAP when prompted with multiple box ↓ more examples”
https://x.com/skalskip92/status/2084684945251844129
Yes, we will have Qwen3.8-Max.”
https://x.com/baseten/status/2084250438509969894
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