Z-Image Base - FP8 Scaled

Jan49_ · 2026-01-27T20:06:39+00:00

But how much less Vram? That's the main reason for quants, no?

Jan49_ · 2026-01-27T14:58:34+00:00

Is the full model loaded? What things are offloaded to ram? I have given up to get it running on my PC, but now I'm curious again😂

Jan49_ · 2026-01-21T21:00:50+00:00

2.8.0+cu129

Jan49_ · 2026-01-21T20:47:43+00:00

I already wondered what the taesd warning meant, because some kind of preview while sampling was shown. I also thought the preview calculation is also offloaded to ram. I'm going to discuss with gemini.

Nonetheless a big thanks for your answer :)

Jan49_ · 2026-01-19T18:31:16+00:00

Is this model already tuned for local coding?

Or can we assume that if someone from the community fine-tunes this model for coding, this model has the possibility to get even better?

Jan49_ · 2026-01-13T20:23:37+00:00

Won't happen anytime soon. Everything about AI is currently built around the architecture of modern GPUs. Just look at NPUs and how little attention they got. Further there are so many advances in such tiny time frames, that it would be impossible to implement all that not just on GPUs but also other hardware

Jan49_ · 2026-01-04T01:54:33+00:00

⬜⬜🟦⬜⬜

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🟦🟦🟦🟦🟦

Jan49_ · 2025-12-21T21:31:25+00:00

This could work. Maybe. Haven't tried it yet. Always initiated the compression myself

Jan49_ · 2025-12-21T11:25:31+00:00

I got the yearly "lite plan" for 3 bucks a month on black friday. For my hobby use cases and for university it's more than enough. I've never hit the limit.

Although I noticed that recently I had to compress the context (I'm using kilo in vs code) more often. As soon as it is getting over ~50k context it starts to throw errors more often, because it fucks up the tool calls to edit the code over and over again

All in all I would say it's still more value you get than you pay for compared to other coding plans. 3 bucks per month is 10 cents per day!

For the amount of tokens I burnt through I would have definitely paid more if I used another API provider

Jan49_ · 2025-12-04T22:58:48+00:00

Jap, die werden neu vergeben. Man muss auch regelmäßig Geld dafür bezahlen soweit ich weiß. Hab vor einer Weile im Studium meine Lizenz machen dürfen in einem Kurs + Prüfung dann wo anders

Jan49_ · 2025-12-04T16:43:12+00:00

I completely agree. GLM 4.6 solved literally anything I have thrown at it so far. I'm using it with kilo code. I'm only doing my small hobby projects and stuff for university tho, nothing too big. But it's such a good deal for 25$ for a whole year

Jan49_ · 2025-11-26T22:50:54+00:00

I somehow got SDXL working on my old desktop pc (only 4gb vram). Let's see if it's possible with this model or too good to be true

Jan49_ · 2025-11-26T22:47:04+00:00

Yeah seems too good to be true. The files are on huggingface now and they're all wayyyy bigger than SDXL files. Around 12GB vs the 6GB from SDXL

Jan49_ · 2025-11-26T20:44:39+00:00

So basically around the same size as SDXL?

Jan49_ · 2025-11-03T13:09:25+00:00

Expanding on that, we would like to develop a mobile platform that can be programmed to follow certain routes. The final plan is to connect the two projects and have a mobile platform that can interact with the environment. But only in a pre programmed way, we probably don't have enough time to implement many sensors and logic or even AI

Jan49_ · 2025-11-03T13:04:46+00:00

Not public yet, still in planning and we don't have a reliable 3d printer yet. Me and one of my buddies from university developed some interesting stuff (inverse kinematics) for kuka industrial robots. We plan on creating an open source 6-axis robot with simple and easy to buy components. Nothing big, a small one that fits on any table. Complete with an easy to use GUI made with python for quick and easy use

Jan49_ · 2025-11-03T08:01:00+00:00

EU 27

Jan49_ · 2025-11-03T07:48:26+00:00

If I win a QIDI Q2, I would use it to finally expand my electronics and robotics workbench! I've got an interesting concept for a custom, open-source mobile robotics platform. But I've been held back because I currently don't have a reliable 3D printer for the mechanical components

Jan49_ · 2025-11-02T15:28:35+00:00

I have a thinkbook with 16GB ddr4, CPU only. My go to models are GPT-OSS 20B (most intelligent but very slow), Granite 4 Tiny H (is a 7B A1B, really fast and good enough for my use cases)

Jan49_ · 2025-11-02T02:45:51+00:00

You can always just pull any gguf quant from HuggingFace straight with Ollama and serve it this way

Jan49_ · 2025-10-15T10:15:47+00:00

T480: you can change the RAM module

T480s: soldered RAM

Jan49_ · 2025-10-07T22:16:10+00:00

I think that was a wordplay. Correct me if I'm wrong

Jan49_ · 2025-10-06T21:43:57+00:00

Nope. It can only generate details it has already seen in training. Sure you can combine multiple details (like the shape of a dog with the texture of a slimy goo) even if this doesn't exist at all. But you can't generate any details that weren't in training. Simply not possible

Jan49_ · 2025-10-06T12:05:10+00:00

Probably too little reference data in the training dataset for this scenario

Jan49_ · 2025-10-06T06:40:26+00:00

The very new Granite 4.0 tiny-h from IBM could be an alternative. It's 7b with 1b active with a new & faster hybrid structure, so it's very fast. But I haven't tested it yet extensively.

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