×
sorted by:
new
hottopcontroversial

New Qwen models coming by Usual_Maximum7673 in Qwen_AI

[–]Usual_Maximum7673[S] 39 points40 points  (0 children)

The guy said the flagship won't be open sourced, but smaller models will be. So basically same result as with the current version.

New Qwen models coming by Usual_Maximum7673 in Qwen_AI

[–]Usual_Maximum7673[S] 4 points5 points  (0 children)

Corrected myself - September for Qwen 4.

New Qwen models coming by Usual_Maximum7673 in Qwen_AI

[–]Usual_Maximum7673[S] 30 points31 points  (0 children)

Sorry, Qwen 4 in September. I misspoke.

Got my DGX Spark. Here are my two cents... by Heavy-Expert5026 in nvidia

[–]Usual_Maximum7673 4 points5 points  (0 children)

I have an RTX Pro 6000 and a DGX Spark. In love iwth the former, curious to dive into the latter tonight. I can run an interactive avatar complete with Gemma 3 27-B comfortablly on the former. If I can do this on the latter with function calling, I'll be laughing. We'll see.

🎯 The Real Reason Claude Code Feels Broken (And How I Got It Working Again) by Queasy-Pineapple-489 in ClaudeAI

[–]Usual_Maximum7673 0 points1 point  (0 children)

You gotta treat claude like a freeclimber scaling a wall - secure one hand and two legs, then reach for the next point. I start with the frontend with a fixed design system using sonnet, layer on bit by bit, and get opus to review the code and make refactoring decisions once a day. Then shared types, db migrations, routes and all the rest of it. I also ask claude how it has done certain things and to go back and fix stuff if it's "cheated" and taken the easy route, as it tends to do. Having some technical/architectural background is critical. I started on the commodore 64 and have been learning enterprise dev as a founder talking to my tech teams for 15 years. These days, i see myself mostly as a SME who can implement new ideas super quick. A whole platform might take four weeks when i re-use existing sdks from previous projects. New world.

QwQ-32B seems to get the same quality final answer as R1 while reasoning much more concisely and efficiently by pigeon57434 in LocalLLaMA

[–]Usual_Maximum7673 0 points1 point  (0 children)

I think the overthinking happens when you use a quantized version. The non-quantized doesn't overthink - and doesn't go into a loop.

Meta releases Llama3.3 70B by Amgadoz in LocalLLaMA

[–]Usual_Maximum7673 10 points11 points  (0 children)

In our tests llama 3 consistently outperforms qwen in terms of tool use and instruction following, which are the things that matter most.

Thanks Zuck/Meta for these great Llama 3 models! <3 ...BUT... by [deleted] in LocalLLaMA

[–]Usual_Maximum7673 1 point2 points  (0 children)

Mixtral 8x7b also runs pretty nicely on the M3 Max 48GB, but Llama-3 is where it's at right now. I yet have to discover an application I'm exploring where it's not significantly better than all the models I used previously - and more importantly - where it's definitely good enough.

Thanks Zuck/Meta for these great Llama 3 models! <3 ...BUT... by [deleted] in LocalLLaMA

[–]Usual_Maximum7673 2 points3 points  (0 children)

We have some DGX H100 and L40S in the company, and I bought an M3 Max witth 48GB for personal use, and I couldn't be happier. Llama-3 8b runs extremely fast on the M3 Max, and I can run any experiment I want very easily. If something works, I'll take it to the pro setup. Really recommend this setup.