Joined March 2023
633 Photos and videos
Do yourself a favor and start claude code like this: ``` CLAUDE_CODE_SUBAGENT_MODEL="opus" claude ``` This prevents Fable from summoning Fable subagents and using up your quota.
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Xiaomi's MIMO v2.5 Pro keeps amazing me! I know GLM 5.2 and Kimi K 2.6 and DeepSeek V4 Pro exist, but my goto model these days for implementing Claude's plans is MIMO. It doesn't waste tokens like GLM and just gets the job done fast. It's also one of the cheapest APIs out there.
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The cost shown in the photo is what it would have cost me if I had used opus. MiMo in this case cost me €5!
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Anthropic charges you for classifying your sessions as blocked/ready for review/done. 😏 Go to your Claude settings and disable this feature to save on usage quota. Super important if you have many sessions running at the same time.
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Fable makes some silly mistakes that Opus would never! 🤦🏻‍♂️ For example, it wrote a long *.md file and then literally wasted tokens by writing the content of the file as the response in Claude Code too!
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Physics without math is like philosophy without language.
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Behnam reposted
もしFable5を試す人でまだClaude Max 20xを課金してない人なら、 Pro で試して(Fable5の)usage limitを使い切る -> Max 5x課金 -> usage limit を使い切る -> Max 20x 課金 -> usage limit を使い切る が最善手かな プランアップグレードごとにリセットされるので
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While it might sound smart, it's gonna dramatically slow down your workflow. IMO Opus 4.8 is capable enough for orchestration. Fable should be reserved for planning. Sonnet for implementation. Haiku for nothing!
Use Fable 5 as orchestrator and Opus Codex to execute (to save fable usage): Fable 5 (max reasoning) = orchestrator Opus = deep reasoning subagent Sonnet = mechanical work subagent Codex = peer Sr. engineer, different perspective Setup: 1. Set Fable 5 as your main model In Claude Code: /model → Fable 5 → reasoning /effort to max 2. Create 2 subagents with /agents In Claude Code: deep-reasoner → pinned to opus "Use for reasoning-heavy phases, architecture, debugging complex issues, algorithm design. Think thoroughly, return a concise conclusion the orchestrator can act on." fast-worker → pinned to sonnet "Use for mechanical tasks, boilerplate, tests, formatting, simple edits. Execute efficiently." 3. Add OpenAI's official Codex plugin (install codex cli in your computer first), In Claude Code type: /plugin marketplace add openai/codex-plugin-cc /plugin install codex@openai-codex /codex:setup 4. Drop this in your CLAUDE.md in your folder: ## Orchestration workflow You (Fable) are the orchestrator. Plan, decompose, synthesize. Reasoning-heavy phases → deep-reasoner Mechanical work → fast-worker Codex (/codex:rescue --background) is a cracked engineer on par with deep-reasoner, from a different perspective. Treat as a peer, not a reviewer. High-stakes decisions: task Opus Codex on the same problem in parallel, synthesize the best of both, without showing either the other's answer. Keep your own context lean. 5. Then prompt Fable like a tech lead: "Goal: [what you want] Context: [files, constraints] You're the lead. Delegate reasoning to deep-reasoner, grunt work to fast-worker, fresh-perspective problems to Codex. Show me your plan first, then execute." That's it.
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Fable is back, but really, what % of our tasks need that much intelligence? I'd say Opus 4.8 is already more than enough for 80% of our needs.
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From now on it's war! 🪖 GLM 5.2 is one unreliable POS model and I'll unfollow anyone who compares it with Opus 4.8, let alone Fable... It's unreliable, sucks at planning, burns too many tokens for simple tasks, does things it wasn't told to do, doesn't do things it was told to do, etc.
I tried GLM 5.2 xhigh on cline to test the model. Man, it churns through tokens like crazy! For a simple task like "remove the zig skills in codex and cline" it used 30k tokens. On the bright side, it was pretty fast and verified its work, which is nice!
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DeepSeek: “Make intelligence too cheap to matter.” Anthropic: “Make intelligence too expensive to meter.”
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"Wait, but, actually, but, wait, ..." Kimi K2.7 Code might be the most R1 model I've seen. It's so BAD at reasoning
Chinese AI models can be great implementation agents but are still very poor planners. The north star of planner models is Opus 4.8 (beats gpt-5.5 too). Best combo? Plan with Claude Code Opus 4.8, then implement using another model in Claude Code ⚡
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Cerebras is offering Gemma 4 31B (my favorite small language model) at insane speeds (and price!). It's not 1800 tok/s but it's definitely super fast.
Gemma 4 31B at over 1,800 tokens per second! Gemma 4 is now in Public Preview on Cerebras.
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Hey @cerebras, I don't see cache prices on your webpage. Do you not offer that feature?
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I was looking forward to Anthropic's Sonnet 5, but I'm a bit disappointed: Even sonnet-xhigh performs worse than opus-high in terms of how fast you hit usage limits. So the lesson is "always use Opus ∈ {high, xhigh, max}."
Introducing Claude Sonnet 5, our most agentic Sonnet yet. It makes plans, uses tools like browsers and terminals, and runs autonomously at a level that just a few months ago required larger and more expensive models.
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Chinese AI models can be great implementation agents but are still very poor planners. The north star of planner models is Opus 4.8 (beats gpt-5.5 too). Best combo? Plan with Claude Code Opus 4.8, then implement using another model in Claude Code ⚡
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I tried GLM 5.2 xhigh on cline to test the model. Man, it churns through tokens like crazy! For a simple task like "remove the zig skills in codex and cline" it used 30k tokens. On the bright side, it was pretty fast and verified its work, which is nice!
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Behnam reposted
2026 is 49% complete.
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iOS 26 animations around the edges never get old... So liquidy, so glassy
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