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🚨SHOCKING: StepFun's Step 5 Preview just hit #1 on OpenRouter Trending. It's a 600B MoE with only 27B active, a 1M context window, and it was built for long-horizon agent work with finance-focused reasoning. So I plugged it into Claude Code and had it build a playable finance game... show more

Jaynit Makwana

59,747 subscribers

59,140 просмотров • 5 дней назад •via X (Twitter)

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Комментарии: 10

Фото профиля Jaynit Makwana

Jaynit Makwana5 дней назад

The game starts with a simple idea: You get a starting balance and move through different money decisions. Each round forces a choice: → save money → invest money → spend on lifestyle → build emergency fund → high-risk opportunity The final result depends on the decisions you make.

Фото профиля Jaynit Makwana

Jaynit Makwana5 дней назад

I connected Claude Code to Step 5 Preview by @StepFun_ai and gave it the task. The model had to plan the game logic, create the UI, write the code, handle state, track score, and make the experience playable in the browser. Not just generate a static page.

Фото профиля Jaynit Makwana

Jaynit Makwana5 дней назад

This is what makes the test interesting. A finance game needs both: → software engineering → finance reasoning The model has to understand how decisions affect money over time, then translate that into rules, feedback, scoring, and interaction. That is closer to real agent work than a one-shot coding prompt.

Фото профиля Jaynit Makwana

Jaynit Makwana5 дней назад

Step 5 Preview is built for long-horizon agentic work: → 600B total / 27B active MoE → 1M context window → vision support → coding workflows → finance-focused reasoning → professional knowledge work It has now reached #1 on OpenRouter Trending. If you are building agents for serious workflows, this is worth testing. Try Step 5 Preview on OpenRouter:

Фото профиля Jaynit Makwana

Jaynit Makwana5 дней назад

That's a wrap! If you enjoyed this thread: 1. Follow me @JaynitMakwana for more of these 2. RT the tweet below to share this thread with your audience

Фото профиля Winston B.

Winston B.5 дней назад

27B active on a 600B base is what makes this fun to try, since a Claude Code loop on it stays cheap enough to iterate on. And with BF16 weights due October 15, anyone can rerun this test off the API soon.

Фото профиля Dhaval Makwana

Dhaval Makwana5 дней назад

this model is amazing to use

Фото профиля Vipul Kumar Kewat

Vipul Kumar Kewat5 дней назад

The interesting part is testing a long-context model inside a real coding workflow.

Фото профиля EW | Personal Finance & Investing

EW | Personal Finance & Investing5 дней назад

wow, Step 5 Preview is amazing!

Фото профиля Andrew Bolis

Andrew Bolis5 дней назад

Nice test of both coding and finance reasoning together.

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19,445 просмотров • 21 дней назад

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MIKE

32,199 просмотров • 2 месяцев назад

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18,861 просмотров • 3 месяцев назад

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114,671 просмотров • 4 месяцев назад

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47,331 просмотров • 3 месяцев назад

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How Jason Calacanis Got Claw-Pilled: An AI Agent Prompted Itself to Build Him a CRM in Seconds “ The moment I became Claw-pilled, I was like, ‘Hey, I want to build my network, I know these 20 people in Japan, I had dinner with them during my recent trip, I want to know who they know, so check out LinkedIn and other things, and who they're associated with, and make me a mind map of it, and then the next trip I want to meet with the next circle of those connections.’” “It's like, ‘Okay, I got the results,’ and it said, ‘Where do you want me to put them?’” “I was like, ‘Well, where can you put them?’” “And it said, ‘I can put it in a Google sheet, I can put it in a Notion table, I can put it here, I could give you a PDF, I could give you a CSV file, or I could write you a CRM.’ And I was like, ‘Yeah, sure, make me a CRM system…’ and it made a CRM system.” “I think maybe 1/1000 people working with AI have had that experience. Maybe it's 1/10,000, where your agent says, ‘I'll make you bespoke software.’ The context is so good because the memory's getting better. When did that happen?” Perplexity CEO Aravind Srinivas: “I think it happened with Opus 4.5. That was the inflection point when models started being amazingly good at orchestration, and reasoning, and tool calls.” “The models started becoming very good at handling the context, so the context window no longer became a problem, and that made it suddenly so good at doing very long orchestration tasks.” —------------------------------------------ Our episode is sponsored by the New York Stock Exchange - a modern marketplace and exchange for building the future. It all happens at the NYSE 🏛 -

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171,016 просмотров • 6 месяцев назад

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116,014 просмотров • 1 год назад

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𝗞𝗶𝗺𝗶 𝗞𝟮.𝟲 𝗶𝘀 𝗖𝗵𝗶𝗻𝗮'𝘀 𝗻𝗲𝘄 𝗼𝗽𝗲𝗻 𝘀𝗼𝘂𝗿𝗰𝗲 𝗮𝗻𝘀𝘄𝗲𝗿 𝘁𝗼 𝗖𝗹𝗮𝘂𝗱𝗲 𝗖𝗼𝗱𝗲. It has 1 trillion parameters but only uses 32 billion at a time. Context window holds 256,000 tokens. It scored 85% on Live Code Bench. Claude hit 64%. It plugs into OpenClaw, Cursor, and Cline with no restrictions. Kimi Claw deploys in the cloud in 2 minutes. It's way cheaper to run than Claude day to day. Save this. Your coding stack just got a real rival.

Julian Goldie SEO

102,245 просмотров • 5 месяцев назад

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someone just rebuilt claude code in pure python and made it 230x cheaper to run it's called clawcodex. a full from-scratch port of the claude code agent loop. 230k+ lines of python, MIT licensed it keeps your request prefix byte-stable, so DeepSeek's prompt cache covers your entire system + tools + history on every turn cache-hit input then bills at ~$0.0435 per 1M tokens the same 1M tokens on Claude Fable 5 runs you $10 so the longer you code, the more the cache pays off what you actually get: → 25 LLM providers (Claude, GPT, DeepSeek, GLM, local ollama) → 1M token context window → real agent loop: tools, skills, REPL, session history → one-line install, mac/linux/wsl and it's sitting at 860 stars. basically nobody is looking yet bookmark this before it gone

alex

14,212 просмотров • 1 месяц назад

someone just rebuilt claude code in pure python and made it 230x cheaper to run it's called clawcodex. a full from-scratch port of the claude code agent loop. 230k+ lines of python, MIT licensed it keeps your request prefix byte-stable, so DeepSeek's prompt cache covers your entire system + tools + history on every turn cache-hit input then bills at ~$0.0435 per 1M tokens the same 1M tokens on Claude Fable 5 runs you $10 so the longer you code, the more the cache pays off what you actually get: → 25 LLM providers (Claude, GPT, DeepSeek, GLM, local ollama) → 1M token context window → real agent loop: tools, skills, REPL, session history → one-line install, mac/linux/wsl and it's sitting at 677 stars. basically nobody is looking yet bookmark this before it gone

someone just rebuilt claude code in pure python and made it 230x cheaper to run it's called clawcodex. a full from-scratch port of the claude code agent loop. 230k+ lines of python, MIT licensed it keeps your request prefix byte-stable, so DeepSeek's prompt cache covers your entire system + tools + history on every turn cache-hit input then bills at ~$0.0435 per 1M tokens the same 1M tokens on Claude Fable 5 runs you $10 so the longer you code, the more the cache pays off what you actually get: → 25 LLM providers (Claude, GPT, DeepSeek, GLM, local ollama) → 1M token context window → real agent loop: tools, skills, REPL, session history → one-line install, mac/linux/wsl and it's sitting at 677 stars. basically nobody is looking yet bookmark this before it gone

alex

158,896 просмотров • 2 месяцев назад

someone just rebuilt claude code in pure python and made it ~230x cheaper to run it's called clawcodex. a full from-scratch port of the claude code agent loop. 230k+ lines of python, MIT licensed it keeps your request prefix byte-stable, so DeepSeek's prompt cache covers your entire system + tools + history on every turn cache-hit input then bills at ~$0.0435 per 1M tokens the same 1M tokens on Claude Fable 5 runs you $10 so the longer you code, the more the cache pays off what you actually get: → 25 LLM providers (Claude, GPT, DeepSeek, GLM, local ollama) → 1M token context window → real agent loop: tools, skills, REPL, session history → one-line install, mac/linux/wsl and it's sitting at 677 stars. basically nobody is looking yet bookmark this before it gone

someone just rebuilt claude code in pure python and made it ~230x cheaper to run it's called clawcodex. a full from-scratch port of the claude code agent loop. 230k+ lines of python, MIT licensed it keeps your request prefix byte-stable, so DeepSeek's prompt cache covers your entire system + tools + history on every turn cache-hit input then bills at ~$0.0435 per 1M tokens the same 1M tokens on Claude Fable 5 runs you $10 so the longer you code, the more the cache pays off what you actually get: → 25 LLM providers (Claude, GPT, DeepSeek, GLM, local ollama) → 1M token context window → real agent loop: tools, skills, REPL, session history → one-line install, mac/linux/wsl and it's sitting at 677 stars. basically nobody is looking yet bookmark this before it gone

Argona

51,369 просмотров • 3 месяцев назад

install these before your next long Claude Code session if your Opus 5.5 bill hurts and you don’t know where to start, copy this: claude-code-router: sits in front of Claude Code and sends each request to the cheapest model that can do it. Haiku does the grep, Opus only gets the hard part. 37k stars rtk: shrinks test, build and git output before the model sees it. one binary, up to 90% less bash output in your context. 83k stars claude-mem: remembers what happened in your past sessions and feeds back only the relevant part, so you stop paying to re-explain your project every morning. 100k stars context-mode: a huge tool output goes into a local database instead of your context window, and Claude pulls out only the lines it needs. 18k stars caveman: makes Claude answer in short telegraphic sentences. code stays identical, and output is the expensive side on Opus 5.5 ($20 per million). 51k stars token-optimizer: a local dashboard that shows where your tokens actually went, and keeps your work alive across compactions. 1.9k stars token-savior: replaces whole-file reads with symbol lookups, so Claude reads the function and not the 2,000 lines around it code-review-graph: maps your repo as a graph and gives Claude only the code connected to the change you’re reviewing jev-ultrafast: a browser agent where Jev picks every click, and a text model wakes up only when something has to be typed. 16,758 stars none of them makes Opus smarter. every one stops it from paying for work it never needed to do the full setup with scripts is in the article. do the measuring step first, so you know what you actually saved

install these before your next long Claude Code session if your Opus 5.5 bill hurts and you don’t know where to start, copy this: claude-code-router: sits in front of Claude Code and sends each request to the cheapest model that can do it. Haiku does the grep, Opus only gets the hard part. 37k stars rtk: shrinks test, build and git output before the model sees it. one binary, up to 90% less bash output in your context. 83k stars claude-mem: remembers what happened in your past sessions and feeds back only the relevant part, so you stop paying to re-explain your project every morning. 100k stars context-mode: a huge tool output goes into a local database instead of your context window, and Claude pulls out only the lines it needs. 18k stars caveman: makes Claude answer in short telegraphic sentences. code stays identical, and output is the expensive side on Opus 5.5 ($20 per million). 51k stars token-optimizer: a local dashboard that shows where your tokens actually went, and keeps your work alive across compactions. 1.9k stars token-savior: replaces whole-file reads with symbol lookups, so Claude reads the function and not the 2,000 lines around it code-review-graph: maps your repo as a graph and gives Claude only the code connected to the change you’re reviewing jev-ultrafast: a browser agent where Jev picks every click, and a text model wakes up only when something has to be typed. 16,758 stars none of them makes Opus smarter. every one stops it from paying for work it never needed to do the full setup with scripts is in the article. do the measuring step first, so you know what you actually saved

rvaniaaa

17,873 просмотров • 1 день назад