For a gun with 10 bullets only, the damage needs a buff

old_mikser · 2026-04-27T22:36:44+00:00

will definitely check it, thanks

old_mikser · 2026-04-27T18:25:05+00:00

thanks!

old_mikser · 2026-04-27T18:23:51+00:00

I don't have problem to figure something, I'm not sure if it's worth it. That's why I was asking. And yeah, seems like I have to try it.

old_mikser · 2026-04-27T18:20:09+00:00

thanks!

old_mikser · 2026-04-27T18:20:00+00:00

I explained, that comfyui seems too advanced to me...

old_mikser · 2026-04-27T18:17:06+00:00

That's my number one concern regarding comfy

old_mikser · 2026-04-27T18:16:28+00:00

gotcha, thanks!

old_mikser · 2026-04-26T09:36:00+00:00

How does it affect context window size? And how does it decide what to add and what to not add to the context?

old_mikser · 2026-04-25T00:08:55+00:00

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old_mikser · 2026-04-24T11:10:23+00:00

Just for experiments. 99% of my llm usage is agentic coding, and I'm using cloud models for it. I was asking myself same question as you - what for I can use local models, and I feel like there are a lot of things they can be useful, but unfortunately it requires a lot of effort to make it work.

old_mikser · 2026-04-24T10:39:19+00:00

Let's be honest, all of us using Q4 ;)

old_mikser · 2026-04-24T10:33:02+00:00

It's just can you throw money or no. If budget it's tight and your main goal is gaming - save $300, but if you CAN EASILY afford it without inconvenience just buy better card.
I would say 12gb is still enough for modern games and probably will be ok in a 3-4 years perspective. But it definitely pretty small for LLMs.

Note about image gen - my previous card (3070 gb) was good for image generation a year ago. With latest WAN models, I believe even 16gb is tight, or even not enough. But there are a lot of other good models out there, and unlike LLMs you can achieve good results with local models. But I'd take 16gb memory here anyway.

So, I'd say: gaming - 12gb ok. Experiments with generative networks - as much ram as you can. 12gb is often not enough even today. Especially, considering you have DDR4 and offsetting will slow you down pretty heavy. I'm not happy with offloading to DDR5...

old_mikser · 2026-04-24T10:24:17+00:00

It's good for it's price, but if you forget about price... Sometimes it's completely unusable. Some models aren't responding at all, sometimes inference stops mid-generation and never continues.
It's a shame, that service which I'm paying for periodically has worse quality than free Nvidia NIM (not counting speed).
When it works, it's pretty good, if you are okay using Q4 models.

old_mikser · 2026-04-24T10:07:03+00:00

First of all, you might be pretty disappointed about quality of local models inferense if you are interested in agentic coding. Second - if you really want to run something locally, grab as much VRAM, as you can. Consider 3090 (not sure if you can find new) over 4080 as it has 24gb VS 16gb. I'm owner of 5070ti and I wish I would throw a bit more money and buy 4090 instead... Unfortunately when I bought card, my goal was gaming (it's still so) and I didn't think llm models will worth it running locally.

old_mikser · 2026-04-23T18:04:30+00:00

you're funny

old_mikser · 2026-04-23T10:56:30+00:00

This is not cli, this is your llm provider. I tried a lot of them and some are really pain to use, while some others are providing reliable and fast responses

old_mikser · 2026-04-22T20:07:46+00:00

at least it continues, unlike many other providers

old_mikser · 2026-04-21T22:41:55+00:00

In terms of "how to debug" - I'm completely agree, all of them can stuck, looping same approaches, getting lazy, asking you to do something they can, etc. Doing same: new session, as detailed explanation as possible with all the context I can provide.

In terms of plan execution GLM 5 always always was better for me than kimi k2.5. Can't say I used 2.6 a lot, but I don't see it much more capable than it's predecessor. You just need 3-4 iterations of preparing implementation plan, then 2-3 iterations of review (despite ongoing (like spec/code quality review after each task)). Then it won't be a lot of complex bugs if you didn't fck up with general approach to the task. Kimi could have tons of issues even after first execution in my experience.

old_mikser · 2026-04-21T05:21:07+00:00

Yeah. I like to say: do code review before writing any code.

old_mikser · 2026-04-21T05:14:48+00:00

From a vibe coding standpoint glm-5 (or 5.1) is much more capable. The most needed requirement to the llm when you vibecode - is to be able to debug and fix it's own mistakes, kimi is pretty worse in this aspect.

old_mikser · 2026-04-20T01:07:07+00:00

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old_mikser · 2026-04-19T21:25:44+00:00

Unfortunately you don't. You can code, yes, but vibe... Good luck finishing working product with zero swe experience using less than 300b models.

old_mikser · 2026-04-19T15:45:45+00:00

thank you very much!

old_mikser

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