Earlier quoted context omitted.
even calling it roll of the dice is an assumption. Can you point anything you find as mistake?
No, because I'm not going to spend a bunch of my time fact-checking obvious AI slop.
Then don't complain.
Granite 4.1: IBM's 8B Model Matching 32B MoE
171–180 of 223 posts
Re: Granite 4.1: IBM's 8B Model Matching 32B MoE
#172Re: Granite 4.1: IBM's 8B Model Matching 32B MoE
#173Earlier quoted context omitted.
Can you clarify what you mean? If you check HF you will see its Apache2 and the datasets were also permissive. It's one of the few models on the market where the creator indemnifies it against copyright claims. https://research.ibm.com/blog/granite-ethical-ai
Oh sorry. Do we have the sources like Nvidia's Nemotron?
You could have found in 5 seconds. The weights are also open sourced as well.
Re: Granite 4.1: IBM's 8B Model Matching 32B MoE
#174Earlier quoted context omitted.
If I give you an amd64 elf binary under Apache2 license, is it open source?
Can you clarify what you mean? If you check HF you will see its Apache2 and the datasets were also permissive. It's one of the few models on the market where the creator indemnifies it against copyright claims. https://research.ibm.com/blog/granite-ethical-ai
if I can't reproduce the artifact, is it really open source?
Re: Granite 4.1: IBM's 8B Model Matching 32B MoE
#175On changing the training mix, H20 did that with Danube in 2024:
https://arxiv.org/pdf/2401.16818
With those results, I would've already done that in any models I got to train. There's also the principle that the LLM's are often better at what they saw last in their training set. That also justifies putting more logic, code, and math in at the end for an analytical or coding model. So, a few precedents for that technique already.
Re: Granite 4.1: IBM's 8B Model Matching 32B MoE
#176Earlier quoted context omitted.
Woah, is this part of the future of models? Basically little models you can use as tools.
I'm pretty sure there's someone somewhere who'll create a proper harness that's equivalent to one giant model. The difficulty is mostly local hardware has lot of memory constraints. Targeting 128GB would seem to be the current sweet spot. If we could get out of the corporate market movers of buying up all the memory, we could maybe have more. Regardless, the people in the 80s capable of pruning programs to fit on sma…
What needs to happen is for companies (or individuals) tired of that to pool money together to build new, memory products. Then, sell them to consumers first and for non-AI use. If not that, then round-robin scheduling of quantities so the units are spread around more.
If costs are high, they might reserve a certain percentage for big business at market prices (or just under) to cover the chip's mask costs.
After DDR5+ RAM, then GDDR5-6 RAM for use with AI accelerators. They might try to jump right in on a HBM alternative. That could be the percentage for AI buyers I just mentioned. Especially if they could put 40-80GB on accelerators like Intel ARC's.
If successful enough, they license MIPS' gaming GPU's to combine with this stuff with full, open-source stack and RTOS support for military sales.
Re: Granite 4.1: IBM's 8B Model Matching 32B MoE
#177Earlier quoted context omitted.
Oh sorry. Do we have the sources like Nvidia's Nemotron?
You could have found in 5 seconds. The weights are also open sourced as well. https://github.com/ibm-granite
Maybe I suck but I didn’t find that in 5 seconds. Or with more time.
I meant the full training datasets and the complete recipes to make the models.
Re: Granite 4.1: IBM's 8B Model Matching 32B MoE
#178Earlier quoted context omitted.
So it’s just like, your opinion, man? edit: It was a play on The Big Lebowski, folks.
> So it’s just like, your opinion, man? Yes. That is how you empirically evaluate tools; not by reading stupid benchmarks. By actually using the tools, for hours and hours. Doing real work. Did you try using it? For hours? Do you use qwen? How about you tell us about your experience with your great 8B models that you use daily. What coding agent harness do you have then hooked up to? What context size can you get bef…
Work pays for copilot, so I use copilot. I will never spend a penny of my own money on this stuff. If it is free, I'll use it.
I'll never use any free opensource anything from china ever, so fuck no I haven't used qwen.
Re: Granite 4.1: IBM's 8B Model Matching 32B MoE
#179On the topic of local models, is there a good equivalent to something like Claude's chat interface? I've recently started transitioning to open models after getting fed up with Claude's usage limits (I'm not in a position to drop $200/month), and for coding tasks Kimi 2.6 has been about the same as Sonnet in my experience. The only thing I've found myself missing is a nice interface to ask it questions and have it he…
Yes but not exactly.
- A lot of people suggesting llama-server's web ui, but that requires you use local AI (llama.cpp), it's persisting content into your browser rather than the server (so you can lose your chats), and it doesn't support much functionality.
- There are some pure-browser chat interfaces that are like llama-server but you can use remote LLMs. This is closer to what you want, but everything is stored in the browser, so backup is harder.
- There's LocalAI, which is like the llama-server option, but more stuff is built in and it persists data to disk. It's flashy and very easy if all you want to do is local AI.
- There's LM Studio, which is another thing like LocalAI, but a desktop app.
- There's OpenWebUI, where it's like LocalAI, except you don't do local inference, you use remote LLMs. It sucks to be honest, just stops working a lot of the time, UX is terrible, lots of weird bugs.
- There's OpenHands, which is more like Codex/Claude Code web UI. You run it locally and connect to remote LLMs. Kinda clunky, limited, poor design. Like most coding agents, it doesn't support all the features you would want, like LocalAI/OpenWebUI do.
- There's OpenCode's web UI, which is like OpenHands, but less crappy.
- There's Jan, which is probably what you want. It's a desktop app rather than a web UI.
Re: Granite 4.1: IBM's 8B Model Matching 32B MoE
#180Earlier quoted context omitted.
Can you clarify what you mean? If you check HF you will see its Apache2 and the datasets were also permissive. It's one of the few models on the market where the creator indemnifies it against copyright claims. https://research.ibm.com/blog/granite-ethical-ai
if I can't reproduce the artifact, is it really open source?
If IBM themselves can't reproduce the artifact do they have the source?