The DeepSeek adapter adds the multimodal visual understanding model DeepSeek-V4-Flash-Vision-Exp. It also supports configuring native image requests. Commands such as /goal and /plan can accept text and image input, and the @ menu can reference files and sessions; MCP/ACP also supports persistent image attachments, and PTC Mode supports forwarding nested images.
离开谷歌的原因之一:小团队可以极致聚焦!
Three ~300M drafters bring speculative decoding to LFM2.5, delivering up to 3.18x faster decoding with identical greedy output. The post Liquid AI Releases LFM2.5-DSpark Draft Models That Deliver Up to 3.18x Faster Decoding Without Changing Model Outputs appeared first on MarkTechPost .
I tried this model yesterday, and it felt to me like the best one I've tried for a local model for interactive use; the responses and reasoning are very fast, and it actually performs agentic tasks well. The speed is phenomenal. I am running this on Ninfer for Windows
A quick feedback after a really major test: nearly 20 hours of non-stop goal-oriented work with Qwen3.8-27B Q6, running across an RTX 3090 and an RTX 3060. It maintained a speed of around 60–63 tokens/s throughout the session.
Here's a brand new Blackwell-native, prefill-optimized 4-bit quant that runs 50% faster on compatible hardware than a Q4 quant of the same memory footprint. And it runs 4-7% faster than other NVFP4 quants as benchmarked on RTX 5090 32GB. Quant Benchmark Speed NVFP4 pp2048 6250 t/s unsloth NVFP4 pp2048 6010 t/s Q4_0 pp2048 4130 t/s Q6_K pp2048 3210 t/s This GGUF also includes a quantized MTP draft head for a good measure. Check it out for all details and specifically recommended settings for 15%
Run Claude Code, Codex or Opencode in cloud with your repo Discussion | Link
Artificial Analysis just benchmarked them and the scores are crazy good, proving the earlier success wasn't only enabled by overthinking.
Nvidia continues to pour money into data center development — just as AI data centers bring lots of money into Nvidia.
Google DeepMind partners with game studios to prototype breakthrough AI gameplay.
When the biotech company Insilico Medicine used its computer models to propose a promising drug for pulmonary fibrosis, it enthusiastically claimed in a press release that the molecule had been “discovered by” its generative AI platform. Insilico leads a pack of companies using AI to rapidly come up with drug ideas humans might never think…
Yes, we’re confused too.
arXiv:2608.18111v1 Announce Type: new Abstract: Foundation models such as GPT and Claude now solve olympiad-level mathematics with remarkable proficiency, so much so that geometry problem solving has become a standard proxy for their mathematical reasoning. Yet solving a geometry problem and drawing the figure it depends on are not the same skill: progress often hinges on a faithful diagram with the right auxiliary constructions and incidences, and it is unclear that a model which reasons its wa
ChatGPT search now uses the site:operator at scale Promptwatch is part of the emerging "GEO" space, for Generative Engine Optimization - the chatbot version of SEO, where companies offer tools and consulting to help your site increase its presence in replies to prompts inside tools like ChatGPT. The Promptwatch product uses automation to track responses to prompts across end-user chat products like ChatGPT, Claude, and Gemini. They publish aggregate reports on this as part of their own content m
Action-conditioned video world models require low-latency causal generation and reliable responses to game-native controls. Although causal distillation enables one- or few-step video synthesis, extending it to interactive world models remains challenging, as discrete keyboard states and continuous mouse motion must remain aligned with temporally compressed latent chunks during causal training and autoregressive rollout. We introduce ForgeWM, a progressive framework that transforms a bidirection
S1-mini is a 462 MB open-weights normalizer that sits after ASR, removing fillers and resolving self-corrections locally. The post Meet S1-mini: Superwhisper’s 462 MB Open-Weights Text Normalizer That Turns Raw ASR Transcripts Into Clean Written Text appeared first on MarkTechPost .
So usually I avoid Q3 quants because I have had bad experiences with it, models were usually too degraded, so the smallest I normally do is Q4, since I only have rtx 4060 ti 16gb. But since there hasn't been a 35b-3ab released yet, I had to try it. I don't use LLMs in agentic workflows, just on Textgen since I'm not a coder so this is not the primary use case of LLMs for me - but sometimes I really need some coding capabilities or help. I'm very impressed how it one shot multiple serious coding
LinkedIn says its AI slop button is working.
My Pro subscription expired today, they killed my access at 1pm local time. I'm now using Qwen3.8-27b w/ 5090m 24gb vram and pi to do everything i was doing in claudecode. The only downside is claudecode let me code without using my gpu, meaning I have to plan things now. Last night I had ChatGPT write up a prompt for a fancy aurora predictor for Canadians. I fed it to local pi and claude sonnet 5. They took about the same time, pi's app looked better, but claude's had better science. I asked th
Identity-preserving image generation becomes increasingly unreliable when a scene must contain many specified people. Beyond retaining each identity, the model must bind every reference to a distinct person and location, while training-time identity losses must establish correspondence among several noisy predicted faces. We introduce WithEveryone, a unified framework for generating group images up to ten reference identities. WithEveryone injects each selected identity as an addressed token, pr
I have been using omarchy on my tower since nearly a year now, shortly after it was released first. I really love the experience I am having with it but I still use my macbook for daly work, so I wanted to recreate a similar experience on it. Thats why I created omacosy, a setup for tiling windows, custom menu bar, some themes from omarchy, focus follows mouse, focus rings around windwos, some mac flavors with trackpad events and a custom mission control overview for your workspaces. I used Aero
Your personal AGI on your PC. Built to finish real work. Discussion | Link
arXiv:2608.18080v1 Announce Type: new Abstract: We present a review on the applications of large language models (LLMs) in health, e.g., social media analysis, clinical conversational agents, therapy support tools, prompt engineering, multimodal learning, and ethical considerations. We integrate findings from interdisciplinary studies utilizing diverse data sources such as social media posts, electronic medical records, and multimodal inputs to enable early detection of depression, suicide risk