Arsh Goyal

8.6K posts

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Arsh Goyal

Arsh Goyal

@arsh_goyal

software , tech , ai education | ai @samsung | Startups | Ex-ISRO | Educator | 700K+ YT & IG | Reachout on mail : [email protected]

United States Katılım Mart 2014
1.6K Takip Edilen41.6K Takipçiler
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Arsh Goyal
Arsh Goyal@arsh_goyal·
love this. i feel benchmarks have become marketing slides at this point, so letting people judge the real work themselves is new and this is doing that. will be interesting to see if the crowd verdict matches the official leaderboards and also curious how they'll handle voting bias at scale though. #HyperagentPartner
Arsh Goyal tweet media
Hyperagent@hyperagentapp

Most benchmarks just give you a number on a chart. We made one where you judge the actual work side-by-side. Here's Fable 5 vs GPT-5.6 Sol on a mix of design, writing, and creative work. Try Hyperbench and choose your winner: hyperagent.com/s/rcW3h5uutU4B…

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Arsh Goyal retweetledi
Arsh Goyal
Arsh Goyal@arsh_goyal·
love this. i feel benchmarks have become marketing slides at this point, so letting people judge the real work themselves is new and this is doing that. will be interesting to see if the crowd verdict matches the official leaderboards and also curious how they'll handle voting bias at scale though. #HyperagentPartner
Arsh Goyal tweet media
Hyperagent@hyperagentapp

Most benchmarks just give you a number on a chart. We made one where you judge the actual work side-by-side. Here's Fable 5 vs GPT-5.6 Sol on a mix of design, writing, and creative work. Try Hyperbench and choose your winner: hyperagent.com/s/rcW3h5uutU4B…

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Arsh Goyal
Arsh Goyal@arsh_goyal·
i feel benchmarks have become marketing slides at this point, so letting people judge the real work themselves is new and this is doing that. will be interesting to see if the crowd verdict matches the official leaderboards and also curious how they'll handle voting bias at scale though.
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Hyperagent
Hyperagent@hyperagentapp·
Most benchmarks just give you a number on a chart. We made one where you judge the actual work side-by-side. Here's Fable 5 vs GPT-5.6 Sol on a mix of design, writing, and creative work. Try Hyperbench and choose your winner: hyperagent.com/s/rcW3h5uutU4B…
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Amit Vadi
Amit Vadi@vadiamit·
yesterday set the bar. next up: I/O Connect Bengaluru. if you’re building, come say hi
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Arsh Goyal
Arsh Goyal@arsh_goyal·
Brunch with @Tejasvi_Surya in Bangalore today and we had an extended chat around some very critical topics affecting all of us. These dialogues are important for giving a platform to talk about certain issues for people from all walks of life. We talked about: - AI in Political Systems - Job Losses and government policies for AI - Research Funding - Education Reforms - Upskilling and Reskilling and more. What is the one question you would ask your MP if given a chance?
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Arsh Goyal
Arsh Goyal@arsh_goyal·
ok the Meta Iris thing is actually wild, a social media company shipping a new AI chip every 6 months through 2027. google proved this playbook with TPUs. inference doesn't need CUDA and inference is where meta's money burns.
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Hayyan
Hayyan@hayyantechtalks·
@arsh_goyal Hy3 model by Tencent looks promising and will try this weekend.
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Arsh Goyal
Arsh Goyal@arsh_goyal·
Spent the last two days testing Hy3, the new model Tencent just launched. 295B MoE but only 21B active params, 256K context, and it's free on OpenRouter till July 21. I used the preview back in April so I wanted to see what actually changed. Quick thread on what surprised me:
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Maxwell 🕊
Maxwell 🕊@MindWisdomMoney·
@arsh_goyal Amazing. Really like the look of the hy3 model by Tencent. Il certainly be spending time this weekend trying it out!
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Arsh Goyal
Arsh Goyal@arsh_goyal·
Honest take: this is not the model I'd pick for huge repo level refactors, there are stronger options for that. But for frontend work, long docs, and agent workflows, the cost to performance ratio is hard to argue with. It has three reasoning modes too, so quick tasks stay fast.
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Arsh Goyal
Arsh Goyal@arsh_goyal·
The agent stuff is where it clicked for me. Gave it one prompt: plan a feature, break it into tasks, write the code, then summarise next steps. It did the whole loop without me babysitting each step. Tool calls stayed stable too, which is usually where these workflows fall apart.
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Arsh Goyal
Arsh Goyal@arsh_goyal·
Then the 256K context test. I dropped a 70 page spec into it and asked for a build plan with timelines and open questions. It pulled details from page 60 that I had forgotten were in there. Most models lose the plot around the middle of a doc this size. This one didn't.
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Arsh Goyal
Arsh Goyal@arsh_goyal·
First test: asked it to build a small analytics dashboard. React, charts, filters, the usual. The preview used to mess up interaction logic halfway through. This one got the state handling right on the first pass. Pasted a console error, it found the actual cause instead of guessing. That part genuinely surprised me.
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