One click and your OpenClaw/Hermes/Codex/ Mercury or DeepSeek Harness agents are live 24/7 Team: @skinbagwbones @gladkos

Joined February 2026
Run @opencode in the cloud Your laptop goes to sleep, OpenCode keeps going Now available on Atomic Bot -> atomicbot.ai/opencode
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Big love to @thdxr @jayair @adamdotdev @kitlangton and the whole @opencode team, we’re huge fans of what you’re building
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Don't want to send everything to the cloud? We just launched our local AI agent. So proud of the Atomic Agent team! Download → atomicagent.io
Meet Atomic Agent Desktop! ✦ Local AI-first agent for Mac, Windows & Linux ✦ 4x bigger context window on local models with TurboQuant ✦ Atomic Fusion orchestrates cloud and local models to reduce costs Download Free & Private Agent → atomicagent.io
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Mercury Agent is now available on Atomic Bot! Say it once and every session after already has your context. The longer you work together, the less you have to explain. One click and @mercury__agent is live 24/7 in the cloud!
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Fable 5.1 crushed GPT-5.6 Sol at rebuilding Claude's release video! Outputs: • Claude Fable 5.1: 3 versions, 9.36M tokens, $22.70 • GPT-5.6 Sol: 1 version, 1.47M tokens, $0.83 Fable checked its own render against its own shot list, found five places where it had got itself wrong and went back twice before calling it done, while GPT shipped version one for 27 times less. Try Claude Fable 5.1 on Atomic Bot in one click!
We’re introducing Claude Fable 5.1 and Claude Mythos 5.1. They're the world’s most advanced models for coding and knowledge work.
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OpenClaw 2.0 is available on Atomic Bot! We ran a battle: OpenClaw 2.0 vs Hermes Agent on GLM 5.3. Four prompts: movie scenes with the OpenClaw mascot in the lead role. Outputs: OpenClaw 2.0: ~2.1M tokens, ~$4.5, 10 self-fixes Hermes Agent: ~2.9M tokens, ~$4, 20 self-fixes OpenClaw screenshotted its own frames at exact timestamps, counted pixels to check its work, and filed fixes like "coat tail whip direction was inverted". Hermes went further and built itself a render harness: it measured frame times, checked the loop seam was invisible, and audited every scene against the spec before we ever opened it. That double-checking is where its extra tokens went. Run OpenClaw 2.0 in the cloud via Atomic Bot in one click!
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Run Codex 24/7 in the cloud with Atomic Bot! Just hand it a repo and close the laptop. One click to start. We ran it on ours first and it found a bug nobody had answered. Codex fixed it before we got back.
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atomicbot.ai retweeted
Run Qwen3.8 27B locally via Atomic Chat💥 We released Atomic Dynamic GGUF quants, from 8-bit (28.9 GB) down to 1-bit (8.5 GB), and measured all other Qwen3.8 GGUFs in the community AD-IQ3_S runs on a 16GB MacBook Air and picks the same next token as the BF16 original 92.4% of the time
We promised open weights for Qwen3.8. Now, time to meet them! 🎉 ⚡ Qwen3.8-27B: - A native multimodal dense model. With just 27B parameters, it outperforms Qwen3.7-Plus overall and shines in real-world coding & office workflows. - 262K native context, easily extendable to 1M tokens via YaRN. - Built for builders. Highly efficient, high-quality, and licensed under Apache 2.0. 🚀 The open weights for Qwen3.8-2.4T-A95B (Max-level) have also been released recently. Whether you're shipping lightweight applications with Qwen3.8-27B locally or building agents with Qwen3.8-2.4T-A95B, they're yours now! Download, deploy, and build something we haven't imagined yet. 👀👇 - Hugging Face: huggingface.co/collections/Q… - ModelScope: modelscope.cn/collections/Qw…
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atomicbot.ai retweeted
Run DeepSeek V4 Flash 0731 locally 🐳 We released 14 quants on Hugging Face, from lossless BF16 to 1-bit AD-IQ2_M is the best fit for 128GB hardware. It matches the original's token choice 83.6% of the time, measured against all other V4 Flash GGUFs in the community
🚀 DeepSeek-V4-Flash Official API is now LIVE in public beta! 🔷 We’ve massively upgraded its Agent capabilities—benchmark scores are now far surpassing the V4-Pro-Preview. Check out the massive performance leap below! 👇 🔷 The official V4-Flash now natively supports the Responses API format and is fully adapted for Codex! Check out the configuration details in our official API docs: api-docs.deepseek.com/quick_…
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atomicbot.ai retweeted
Qwen3.8-Max became the brain of Atomic Agent, Hermes and OpenClaw. We gave the same task: Turn a photo of a hand-drawn floor plan into an interactive 3D walkthrough of that apartment and open it in the browser. Outputs: – Atomic Agent: 66 min, 557K tokens, $2.01 – OpenClaw: 32 min, 1.2M tokens, $1.12 – Hermes: 2 h 14 min, 4.2M tokens, $6.42 Before the start we leveled the field: one model endpoint, equal step and token budgets, equal timeouts, full autonomy, memory wiped on all three. Atomic Agent reads images through its vision tool, so it interrogated the sketch 14 times until every room, door and window turned into data. Then it drafted the whole scene in its head six times, threw away five drafts, and wrote the finished 19.8 KB file in one single write. After that it opened Chrome, checked its own render, and only then replied. The only agent of the three that verified its work, and the only one that stopped on its own. OpenClaw was twice as fast and the cheapest of the three, but its image tool kept timing out mid-run, and it shipped the palest apartment of the day: white rooms, no floor colors, one texture visibly glitched, and furniture you have to squint to find. It read the full plan three times, cut 11 room crops, wrote the scene in chunks, and landed the fastest and cheapest apartment of the day in 32 minutes. Then it kept polishing the finished file until we pulled the plug. Hermes worked the longest: two hours, 97 model calls, 4.2M tokens, and the apartment came out wrong anyway: doors standing loose in the middle of rooms, a 2 by 1.8 bath sprawled across a quarter of the flat, furniture drifting away from the plan. It measured everything twice and still built the least accurate apartment. Atomic Agent will run Qwen3.8-27B locally on day zero, next week!
📢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 self-evolving development, from empty folder to production without hand-holding, complete project trace in the GitHub:github.com/qwen-code-dev-bot… - Real work, real results: Production-quality deliverables across hundreds of professions. - Long-horizon mastery: System-level autonomous planning with closed-loop adaptive learning, driving 500+ turns of chip design optimization and 365 days of e-commerce strategy. - Native multimodal intelligence: Vision isn't just input — it's a continuous feedback loop for planning, execution, and self-correction. 💰Pricing: Input: $2.0 / M tokens Output: $6.0 / M tokens Implicit Caching: $0.25 / M tokens Start building with Qwen3.8-Max! 🚀 📖 Blog: qwen.ai/blog?id=qwen3.8 ✅ Qwen Studio: chat.qwen.ai/?models=qwen3.8… ⚡ API: qwencloud.com/models/qwen3.8…
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