I'm tired boss

I don’t understand? How

Chinese bride gifts her partner a flagship GPU at wedding — he breaks down in tears She handed him an ASUS ROG Astral RTX 5090 that costs around $12,000

1/ muse spark open is the most capable US open-weight model to date. 816B total params, 42B active. 1M-token context. natively multimodal. built for coding and agentic work like long-horizon tasks, hard software engineering, multi-step reasoning. america! 🇺🇲

My dear friends, I’d like to show you my latest toy project Introducing Handwired: turn your regular JavaScript code into a neural net! - no training - exact outputs vs the JS program - fully differentiable All runnable in a browser, without GPU

Ours is $19k with 192GB of VRAM

ai has massively accelerated how obvious this is all these different roles are compressing into just one be useful, that's it

Add audioascode.com to it

This hacker is truly legendary. A complete amateur. 1. He left directory listing enabled on his own server, so researchers could figure out who he was with barely any effort. 2. They found files like CLAUDE.md and went through his Claude Code sessions. 3. There were questions like, “Where can I sell this data?” 4. He’d also asked, “Can you write my résumé?” That pretty much handed them all his personal information. 5. Apparently, he’s a student at South China University of Technology living in Guangdong. His name, phone number, and where he lives have all been identified.

We aren't giving up on consumers. But they are dumb and I never made hermes for that purpose. I made hermes agent as a coding harness for me. That's why the CLI came out first, and then remote gateway channels, and then, our first actual move toward consumer with the desktop app. If anything, the mobile app means we are going way harder on consumers. I am not leading the mobile app, and I dont even lead the desktop app. My focus is and always has been on making hermes the **best** agent. Not an agent ux for normies. MoA is not for normies. 1000's of subagents is not for normies. The intense work we've done to improve terminal and coding capabilities of hermes is not for normies. It has always been this way, and anyone who thought otherwise was mistaken.

Anthropic has released Claude Haiku 5.5, scoring 43 on the Artificial Analysis Intelligence Index - up 26 points one year after the last Haiku release Haiku 5.5 is the first Haiku model with Anthropic’s effort settings and adaptive thinking, and Anthropic has introduced tiered pricing. Haiku 5.5 is cheaper than its predecessor - it costs $0.10/$0.50 per 1M input/output tokens for prompts up to 100k tokens (the same as GPT-6 Luna and 10% of the previous Haiku model). However, this pricing rises 5x to $0.50/$2.50 above 100k. The site does not yet reflect tiered pricing, so provisional cost figures for Haiku 5.5 do not include the step up cost. We are working on support and will follow up with Cost per Task coverage soon. Key takeaways: ➤ Leading small-class model performance: At max effort Haiku 5.5 sits slightly ahead of models such as GLM-5.3 Flash (42), Gemini 3.8 Flash (41) and GPT-6 Luna (38). Its score is comparable to Kimi K3 (44), a 2.8T parameter open weights model, and trails Claude Sonnet 5.5 (max, 56) by 13 points ➤ Heavy token use compared to GPT-6 Luna: Haiku 5.5 (max) uses ~162k output tokens per Intelligence Index task, ~3x GPT-6 Luna (max, ~50k). Moving from xhigh to max adds 2 points for ~1.8x the tokens. At similar intelligence it also uses more tokens than GPT-6 Luna: Haiku 5.5 (high) scores 38 with ~55k tokens per task against 38 with ~50k for Luna (max), and the gap widens at lower effort settings ➤ Highly capable at agentic knowledge work: on AA-Briefcase, our private evaluation for realistic knowledge work tasks, Haiku 5.5 (max) reaches 1578 Elo, ahead of models including Kimi K3 and GLM-5.3, and comparable to Muse Spark 1.3 (max) ➤ Improvements on terminal use: on Terminal-Bench 4.0 it scores 33%, up from 0% for Haiku 4.5. This is level with GLM-5.3 Flash, and ahead of Gemini 3.8 Flash (20%) and GPT-6 Luna (13%) ➤ Lower factual knowledge, but relatively low hallucinations: as expected for a smaller-class model, Haiku 5.5 has lower factual knowledge than its siblings. AA-Omniscience accuracy is 36%, against 55% for Gemini 3.8 Flash and 44% for GPT-6 Luna, but this is partly driven by more willingness to admit when it doesn’t know - its hallucination rate is lower, at 40% against 55% and 77% ➤ AutomationBench-AA result likely understated: Haiku 5.5 scores 35%, against 53–60% for GPT-6 Luna, Gemini 3.8 Flash and GLM-5.3 Flash. During pre-release testing, a safety refusal issue caused the model to over-refuse. Anthropic is working on resolving this - we will re-run this evaluation with the fix, and expect this score to rise Other model details: ➤ Context window: 1 million tokens, up from 200k for Claude 4.5 Haiku ➤ Pricing: $0.10/$0.50 per 1M input/output tokens up to 100k tokens, $0.50/$2.50 above. Cache reads $0.01 ($0.05 above 100k), 5 minute cache writes $0.125 ($0.625 above 100k) ➤ Multimodality: Text and image input, with text output

Haven't tried Constellation Gate yet? Today's the day! We just released Gate Chat! Chat with hundreds of AI models in one secure place and only pay for what you use. Just curious? Play with two free models. - Sign up at constellationgate.ai/ - Open Gate Chat from the menu - Start chatting Enjoy!

Introducing Beam: a highly efficient agentic open model with 501B total parameters and 23B active. - Frontier reasoning efficiency - Advances the Western open frontier on coding & agentic tasks - Trained end-to-end from scratch Full weights release this month. Learn more about Beam: reflection.ai/beam