One click and your OpenClaw/Hermes/Codex/ Mercury or DeepSeek Harness agents are live 24/7 Team: @skinbagwbones @gladkos
Joined February 2026
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Run @opencode in the cloud
Your laptop goes to sleep, OpenCode keeps going
Now available on Atomic Bot -> atomicbot.ai/opencode
Big love to @badlogicgames @mitsuhiko @davidbrai @vegardstikbakke and the whole @pidotdev team, we’re big fans of Pi and the way you build it
Run Pi @pidotdev in the cloud
Your minimal agent working while your laptop sleeps
Try Pi → atomicbot.ai/pi-agent-in-clo…
Big love to @thdxr @jayair @adamdotdev @kitlangton and the whole @opencode team, we’re huge fans of what you’re building
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
NanoClaw is now available on Atomic Bot!
A security agent that asks before it does anything.
One click and @NanoClaw_AI is live 24/7 in the cloud!
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!
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!
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!
OpenClaw 2.0 has arrived
openclaw.ai/blog/openclaw-2-…
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
ALT Quality vs size chart and hardware table for Atomic Chat's Qwen3.8 27B GGUF quants. The chart plots mean KL divergence vs BF16 against file size for every Qwen3.8 27B GGUF in the community: the blue AtomicChat AD line runs from 8.5 GB to 28.9 GB, with unsloth, lmstudio-community and ggml-org files as separate markers, and shaded zones showing where each side is closer to BF16. Measured on eval_neutral held-out, 4096 ctx, reference BF16, 4x RTX 5090, CUDA 13.0. The table below recommends a quant per memory size: 12 GB takes AD-IQ2_XS at 9.9 GB with top-1 83.5%, 16 GB takes AD-IQ3_S at 13.8 GB with 92.4%, 24 GB takes AD-Q5_K at 20.2 GB with 97.3%, 32 GB takes AD-Q6_K at 25.0 GB with 98.7%, and 48 GB takes Q8_0 at 28.9 GB with 98.9% and mean KL divergence 0.0006.
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…
