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撮影の時は清楚に…✨ 新人グラドル #遠山茜子# のデビュー㊙話に迫る❗ 週プレ編集部(@shupure)で #MAX「GET# MY LOVE!」をダンス❤ 『紺野、今から踊るってよ』 🎶無料配信中👉 @odorutteyo

ギャルオーディション・グランプリ美女と踊る🎉 #MAX「GET# MY LOVE!」😆💘 『紺野、今から踊るってよ』 🎶無料配信⇒ @odorutteyo @akane_016

Okay, the @VulcanBench results for Qwen3.8-Max are in, and it is not what I expected. First, for anyone new to VulcanBench, here's a quick TL;DR on the eval suite: 23 frontier-hard software engineering tasks taken from real merged OSS PRs, run in a Docker sandbox, 3 runs per task across all three of its effort levels. No puzzles, no random abstract stuff, all real things engineering teams would do with these models. It looks like Qwen3.8-Max has a major overthinking problem, it uses a LOT of tokens and is very slow, period, no other way to see it. My cost to run this benchmark was $126.25, to run the exact same eval suite with DeepSeek V4-Flash was only $13.60. This makes Qwen3.8-Max an insanely expensive model. The tasks Qwen genuinely can't solve fail at every effort level, extra reasoning didn't help. The regression is almost all in work it already handles: six tasks that low solves every single time account for 83% of the 26-point drop, three of them collapsing to zero. It's not losing the hard problems. It's losing the ones it already knows how to do. Since Qwen3.8-Max hit a lot of wall clock budget caps, I thought I'd share more about this. - VulcanBench caps both steps (50–200) and wall clock (5–60 min), each scaled by repo size. - This is aligned with how comparable harnesses bound agents, DeepSWE caps rollouts at 100 environment steps, sitting right inside my step range; Terminal-Bench enforces a per-task wall clock; SWE-bench Verified scaffolds typically allow 20–60 min per instance with 250–350 step limits. - Every model on my chart gets the identical budget, and Qwen is the slowest model I've tested at 20–25 min/task. Soooo... Alibaba positions Qwen3.8-Max as trailing only Claude Fable 5. But on the kind of real coding work engineering teams would actually throw at it, under a fixed budget, its best setting lands mid-pack and its default lands last, so common. If you want to optimize for accuracy, Grok 4.5 is the move. If you want accuracy per dollar, DeepSeek V4-Flash is hard to beat, heck it's 10× cheaper than Qwen and you get higher accuracy. Qwen just isn't in the game at this point, this is not a model I could see engineering teams using for daily coding work.

Why manage separate AI tools for the script, the image, and the video? The Alibaba Cloud Token Plan gives you one shared credit pool across supported models and tools, with visibility into usage and access to newer models like Qwen3.8-Max-Preview, HappyHorse1.1, DeepSeek V4, and GLM-5.2. One plan for every modality, to build more, spend less. Get started from just $4 in your first month. Explore the Token Plans: #AlibabaCloud# #TokenPlan# #Qwen# #Wan# #HappyHorse# #GenerativeAI# #AIContent# #MultimodalAI#

I’m running Fable, K3, 5.6 and 4.5 like 10 hours a day and they are all sick. At work, at home. I have subscriptions for many of them at both locations. But you know which model legit doesn’t get enough hype? GROK. I’m so serious. Even on 𝕏 it doesn’t get enough hype cause we assume oh yeah it’s Elon’s network of course they are gonna hype grok. But I don’t care about benchmarks. It absolutely crushes in usefulness and im quickly using it more and more. It gets the job done well, and fast, and it doesn't spend all day thinking about nothing. But its not just fast and cheap. Sometimes it WORKS BETTER than 5.6 or even Fable. Check this. I told Grok and Codex to help design a level that I could dynamically spawn some quest monsters and players on using the level tools available for my game. Sol on max settings took forever to put out garbage and Grok's level was pretty sick right away. I have many other dramatic cases of Grok outperforming so called frontier models on genuinely useful tasks. I can’t wait for the 2 parameter model.

If you aren't yet bold enough to install the Codex app, you can stay in the presence of your orange crab and point it at GPT 5.6 Sol. Takes 5 minutes. Kudos to Theo for explaining one of the ways to get this done. Step 1: Install CLIProxyAPI Step 2: Connect Step 3: Define following alias and enjoy claudex ``` alias claudex='CLAUDE_CODE_SUBAGENT_MODEL=gpt-5.6-sol \ CLAUDE_CODE_ALWAYS_ENABLE_EFFORT=1 \ CLAUDE_CODE_MAX_TOOL_USE_CONCURRENCY=3 \ ENABLE_TOOL_SEARCH=false \ claude --model gpt-5.6-sol' ``` If this gets blocked, I owe you a reset.

Chamath reveals his company's AI token costs are doubling every 45 days but productivity is only up 5% "I sat down with my CTO today, I said how are we doing on token spend. And he said the most incredible thing, he said right now, our token costs are doubling every 45 days. I said well what is the downstream productivity? And he said maybe 5% max." "So my costs are doubling every 45 days, my upside is essentially flat. He said honestly, what we're finding out is that you need to use a lot more tokens to get to this next iteration of improvement because we've effectively already asymptoted." "We're going to take a step back and try to figure out what to do. I don't know how many other companies will actually go through this reckoning now, but the point is everybody in the next three or four years will for sure go through it." "I suspect that if you can get out now, you should get out now before all of that starts to seep into the water table. Because I think that's probably what allows you to get out at a huge price and raise a huge amount of money."

Max Muncy told Madison Bumgarner to "go get the ball out of the ocean" after hitting a home run into McCovey Cove 😳 This story is hilarious 🤣 Full episode:

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Someone ran Claude Code on an e-ink notebook and the slowest screen in the world suddenly turned out to be the best home for an AI that already thinks one word at a time. This is the reMarkable Paper Pro, a paper tablet for notes with no browser and no social media and not a single app. He went into it over SSH and brought up Claude Code on Opus 4.8 on Claude Max and typed right into the terminal on the paper screen: "hello reddit, this is ssh terminal on rmpp". For years this screen got slammed for one thing. E-ink is too slow and it draws with a delay and it ghosts and it is no good for real work. But Claude itself puts out a thought one word at a time. And here is what came out of it: the very thing that killed the paper screen for normal software lined up perfectly with the pace of the AI. There is no more lag because there is nothing left to lag. And then come the things no monitor can give you. Your eyes do not get tired. You can watch Opus think on max effort for an hour and it feels like reading a book and not staring into a backlight. Nothing distracts you. Not a single notification and not a single tab and just a cursor and an agent that writes code while you simply watch the page. The charge lasts for days. E-ink barely touches the battery so Claude can grind on a task all night long and the tablet is still alive by morning. And it weighs as much as a notebook. The whole work setup now fits into a bag like a notepad with a stylus on top. Everything on the screen is for real: Claude Code v2.1.162 and bypass permissions on and Opus going off to think on max effort right on the e-ink. In my opinion this is the most unexpected home for an AI this year. Not a farm of graphics cards and not a wall of monitors but a quiet sheet of paper on a coffee table where the most powerful Claude writes code one word at a time like a pen.