Billson

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Billson

Billson

@CheungBillson

@venturesintern @AnimocaVentures NFA & DYOR Maintaining a macro view is crucial for long-term success

Katılım Haziran 2016
921 Takip Edilen78 Takipçiler
Billson
Billson@CheungBillson·
AI War 2026 🇺🇸🇨🇳 💻 Hardware: US leads. $TSMC 7nm+ block keeps China behind on silicon. 🧠 Software: China closes in. Top model gap now just 2.7%. 💡 Verdict: US controls the chips; China controls the access.
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Graeme
Graeme@gkisokay·
The LLM Cheat-Sheet for Hermes + OpenClaw Agents (04.12.26) The community has flagged Claude Opus 4.6 underperforming lately while GLM 5.1 has exploded on the scene to claim frontier capabilities. A lot has changed since the last version. Here's what moved: GLM-5.1 just proved its frontier capabilities with #1 SWE-Pro globally, 8-hour autonomous execution, and cheaper than Opus on input. It earns a Tier 1 spot. Grok 4.20 enters Tier 2 with the lowest hallucination rate of any tested model, a native multi-agent API running up to 16 parallel agents, and a 2M context window. Gemini 3.1 Pro drops to Tier 3. The price and multimodal story is strong, but the new frontier bar left it behind on reasoning. Mistral Small 4 joins Tier 3. One model replacing three specialist pipelines (reasoning, vision, agentic coding) at $0.15/M input. Apache 2.0. Here's the full landscape: 18 models in 4 tiers. Tier 1 - Frontier Models - Claude Opus 4.6: #1 agentic terminal coding; watch for inconsistency reports - GPT-5.4: superhuman computer use, real planning. and introduced a $100/month plan - GLM-5.1: #1 SWE-Pro globally, 8-hour autonomous execution, MIT license Tier 2 - Execution - MiniMax M2.7: 97% skill adherence, built for agents. API only, not open weights - Kimi K2.5: long-horizon stability, agent swarm - Grok 4.20: lowest hallucination rate on the market, native multi-agent, 2M context - DeepSeek V3.2: frontier reasoning at 1/50th the cost Tier 3 - Balanced - Claude Sonnet 4.6: 98% of Opus at 1/5 the cost - GPT-5.4 mini: 93.4% tool-call reliability, runs on OAuth - Gemini 3.1 Pro: best multimodal value, native video+audio in one call - Qwen3.6 Plus: near-frontier coding, completely free via OpenRouter - Llama 4 Maverick: open-weight, self-host at zero marginal cost - Mistral Small 4: one model replacing three; reasoning, vision, agentic coding, Apache 2.0 Tier 4 - Local / $0 - Runs on 32GB RAM or less - Qwen3.5-9B: always-on subconscious loop, 16GB RAM, beats models 13x its size - Qwen3.5-27B: stronger instruction following, 32GB RAM - Gemma 4 31B: best local reasoning, Apache 2.0, commercial-ready - DeepSeek R1 distill: best chain-of-thought at $0 - GLM-4.5-Air: purpose-built for agent tool use and web browsing, not a trimmed general model Full breakdown with benchmarks, costs, and use cases in the table ↓
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Graeme@gkisokay

The LLM Cheat-Sheet for OpenClaw and Hermes agents The goal is to choose the right models that best fit your agents' needs for as little cost as possible. Do this and you can build a proficient agent that will never die. Here's the full landscape on popular models for AI agents: 12 models, 4 tiers, every one earning its place. Tier 1 - Frontier Models - Claude Opus 4.6: #1 agentic terminal coding - GPT-5.4: superhuman computer use, real planning - Gemini 3.1 Pro: best price/intelligence at frontier, native multimodal Tier 2 - Execution - MiniMax M2.7: 97% skill adherence, built for agents - Kimi K2.5: long-horizon stability, agent swarm - DeepSeek V3.2: frontier reasoning at 1/50th the cost Tier 3 - Balanced - Claude Sonnet 4.6: 98% of Opus at 1/5 the cost - GPT-5.4 mini: 93.4% tool-call reliability - Qwen3.6 Plus: near-frontier coding, completely free - Llama 4 Maverick: open-weight, self-host at zero marginal cost Tier 4 - Local / $0 - Qwen3.5-9B: always-on subconscious loop, 16GB RAM, beats models 13x its size - Qwen3.5-27B: stronger instruction following, 32GB RAM - Gemma 4 31B: best local reasoning, Apache 2.0, commercial-ready - DeepSeek R1 distill: best chain-of-thought at $0 - GLM-4.5-Air: purpose-built for agent tool use and web browsing, not a trimmed general model Full breakdown with benchmarks, costs, and use cases in the table 🔽

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MiniMax (official)
MiniMax (official)@MiniMax_AI·
Introducing MMX-CLI — our first piece of infrastructure built not for humans, but for Agents. Your Agent can read, think, and write. But ask it to sing, paint, or show you a world it's never seen — and it falls silent. Not because it doesn't understand, but because it has no mouth, no hands, no camera. Today, that changes. MMX-CLI gives every Agent seven new senses — image, video, voice, music, vision, search, conversation — powered by MiniMax's full-modal stack, today's SOTA across mainstream omni-modal models. One command: mmxAgent-native I/O. Zero MCP glue. Runs on your existing Token Plan. Two lines to give your Agent a voice: npx skills add MiniMax-AI/cli -y -g npm install -g mmx-cli Then tell it: "you have mmx commands available." It'll learn the rest. Github → github.com/MiniMax-AI/cli Token Plan: platform.minimax.io/subscribe/toke…
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Qwen
Qwen@Alibaba_Qwen·
🚀 Qwen Code v0.14.0 – v0.14.2 are now available Channels:Control Qwen Code remotely from Telegram, DingTalk, or WeChat — send a message from your phone, get results on your server Cron Jobs :Schedule recurring AI tasks — auto-run tests every 30 min, pull & build every morning, monitor logs on a timer Qwen3.6-Plus :New flagship model with 1M token context, 1,000 free daily requests Sub-agent Model Selection:Assign different models to sub-agents — use a powerful model for the main task, a fast one for subtasks, save tokens without sacrificing quality /plan:Enter planning mode before execution — AI maps out all files and steps first, you confirm, then it executes Follow-up Suggestions:AI suggests 2-3 next steps after completing a task — "Add unit tests?" "Check similar files?" — click to continue Adaptive Output Tokens :Default 8K output, auto-escalates to 64K when truncated — no more manually tuning max_tokens Ctrl+O Verbosity Toggle :Switch between verbose and compact output mid-conversation — debug mode when you need it, clean mode when you don't 📋 Full changelog: github.com/QwenLM/qwen-co…
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Billson
Billson@CheungBillson·
The Macro Reality 🇺🇸 • Shift: Moving from Globalism to Trump's "America First" redefines supply chains and energy costs. • Debt Bomb: US debt surges, Fed’s rate cuts have diminishing returns. • Survival: AI companies with cash flow and real tech, not just dreams, will survive.
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Billson@CheungBillson·
The IPO Liquidity Black Hole 🕳️ SpaceX ($1.75T) and OpenAI (~$1T) IPOs • Opportunity: This massive liquidity drain will crush "weak" AI fluff, consolidating value into true leaders. • Smart Money: When the market panics over a liquidity drought, you buy the infrastructure kings
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Billson@CheungBillson·
The AI "Bubble" Myth 🤖 People fear a Dot-com style crash, but they’re missing the big picture. • The Trap: First movers burn billions "building the road." • The Reality: Massive R&D isn't a failure—it’s the "entry fee" for the next Industrial Revolution.
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Claude
Claude@claudeai·
Introducing Claude Managed Agents: everything you need to build and deploy agents at scale. It pairs an agent harness tuned for performance with production infrastructure, so you can go from prototype to launch in days. Now in public beta on the Claude Platform.
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Artificial Analysis
Artificial Analysis@ArtificialAnlys·
We’ve added a new pseudonymous video model to our Text to Video and Image to Video Arenas.‘HappyHorse-1.0’ is currently landing in the #1 spot for Text and Image to Video (No Audio) and the #2 spot for Text and Image to Video (With Audio). Further details coming soon. Example generations below from HappyHorse-1.0 in the Artificial Analysis Video Arena 🚀
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JAMES @ ANIMOCA VENTURES
JAMES @ ANIMOCA VENTURES@JIQQYJONES·
Wishing all a blessed and joyful Easter filled with love, hope and renewal!
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OpenClaw🦞
OpenClaw🦞@openclaw·
OpenClaw 2026.4.5 🦞 🎬 Built-in video + music generation 🧠 /dreaming is now real 🔀 Structured task progress ⚡ Better prompt-cache reuse 🌍 Control UI + Docs now speak 12 more languages Anthropic cut us off. GPT-5.4 got better. We moved on. github.com/openclaw/openc…
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Cointelegraph
Cointelegraph@Cointelegraph·
🔥 NEW: OpenClaw's next version will ship with native video generation support, with integrations from OpenAI, Google, xAI, Alibaba, and more, per creator Peter Steinberger.
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OpenRouter
OpenRouter@OpenRouter·
Qwen 3.6 Plus from @Alibaba_Qwen is officially the first model on OpenRouter to break 1 Trillion tokens processed in a single day! At ~1,400,000,000,000 tokens, it’s the strongest full day performance of any new model dropped this year. Congrats to the Qwen team!
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Qwen
Qwen@Alibaba_Qwen·
(1/8)🚀 Introducing Qwen3.6-Plus: Towards Real-World Agents! 🤖 Today, we’re thrilled to drop a major milestone in our journey toward native multimodal agents. Here is what makes Qwen3.6-Plus a game-changer: 💻 Next-level Agentic Coding: Smarter, faster execution. 👁️ Enhanced Multimodal Vision: Sharper perception & reasoning. 🏆 Top-tier Performance: Maintaining leading general capabilities. 📚 1M Context Window: Available by default via our API. Built on your invaluable feedback from the Qwen3.5 era, we’re laying a rock-solid foundation for real-world devs. Get ready to experience truly transformative ✨ Vibe Coding ✨. Huge thanks to our community! Go try it out and show us what you can build. 👇 Chat: chat.qwen.ai API: modelstudio.console.alibabacloud.com/ap-southeast-1… Blog: qwen.ai/blog?id=qwen3.6 🔔Noted:More Qwen3.6 models to come and be open-sourced! Stay tuned~ 👀#Qwen #AI #AgenticCoding #VibeCoding #Agents
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Google
Google@Google·
We just released Gemma 4 — our most intelligent open models to date. Built from the same world-class research as Gemini 3, Gemma 4 brings breakthrough intelligence directly to your own hardware for advanced reasoning and agentic workflows. Released under a commercially permissive Apache 2.0 license so anyone can build powerful AI tools. 🧵↓
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