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Kimi Released Kimi K2.5, Open-Source Visual SOTA-Agentic Model

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Re: Kimi Released Kimi K2.5, Open-Source Visual SOTA-Agentic Model

#81

Post by johndough »

endymi0n wrote: post #45
Tepix wrote: post #8

Huggingface Link: https://huggingface.co/moonshotai/Kimi-K2.5 1T parameters, 32b active parameters. License: MIT with the following modification: Our only modification part is that, if the Software (or any derivative works thereof) is used for any of your commercial products or services that have more than 100 million monthly active users, or more than 20 million US dollars (or equivalent in other currencies) in mont…

One. Trillion. Even on native int4 that’s… half a terabyte of vram?! Technical awe at this marvel aside that cracks the 50th percentile of HLE, the snarky part of me says there’s only half the danger in giving something away nobody can run at home anyway…

The model absolutely can be run at home. There even is a big community around running large models locally: https://www.reddit.com/r/LocalLLaMA/

The cheapest way is to stream it from a fast SSD, but it will be quite slow (one token every few seconds).

The next step up is an old server with lots of RAM and many memory channels with maybe a GPU thrown in for faster prompt processing (low two digits tokens/second).

At the high end, there are servers with multiple GPUs with lots of VRAM or multiple chained Macs or Strix Halo mini PCs.

The key enabler here is that the models are MoE (Mixture of Experts), which means that only a small(ish) part of the model is required to compute the next token. In this case, there are 32B active parameters, which is about 16GB at 4 bit per parameter. This only leaves the question of how to get those 16GB to the processor as fast as possible.

Re: Kimi Released Kimi K2.5, Open-Source Visual SOTA-Agentic Model

#82

Post by testfrequency »

motoboi wrote: post #80
bertili wrote: post #34

The "Deepseek moment" is just one year ago today! Coincidence or not, let's just marvel for a second over this amount of magic/technology that's being given away for free... and how liberating and different this is than OpenAI and others that were closed to "protect us all".

What amazes me is why would someone spend millions to train this model and give it away for free. What is the business here?

Curious to hear what “OpenAI” thinks the answer to this is

Re: Kimi Released Kimi K2.5, Open-Source Visual SOTA-Agentic Model

#83

Post by jlu »

esperent wrote: post #76
mohsen1 wrote: post #71

Earlier quoted context omitted.

Parallel agents are such a simple, yet powerful hack. Using it in Claude Code with TeammateTool and getting lots of good results!

> TeammateTool What is this?

claude code hidden feaure currently under a feature flag:

https://github.com/mikekelly/claude-sneakpeek

Re: Kimi Released Kimi K2.5, Open-Source Visual SOTA-Agentic Model

#84

Post by YetAnotherNick »

motoboi wrote: post #80
bertili wrote: post #34

The "Deepseek moment" is just one year ago today! Coincidence or not, let's just marvel for a second over this amount of magic/technology that's being given away for free... and how liberating and different this is than OpenAI and others that were closed to "protect us all".

What amazes me is why would someone spend millions to train this model and give it away for free. What is the business here?

Hosting the model is cheaper per token, the more batched token you get. So they have big advantage here.

Re: Kimi Released Kimi K2.5, Open-Source Visual SOTA-Agentic Model

#85

Post by frimmy »

esperent wrote: post #76
mohsen1 wrote: post #71

Earlier quoted context omitted.

Parallel agents are such a simple, yet powerful hack. Using it in Claude Code with TeammateTool and getting lots of good results!

> TeammateTool What is this?

https://x.com/kieranklaassen/status/2014830266515382693 - agent swarms tool shipping w/ cc soon..

Re: Kimi Released Kimi K2.5, Open-Source Visual SOTA-Agentic Model

#86

Post by YetAnotherNick »

Barathkanna wrote: post #54
bertili wrote: post #48

Earlier quoted context omitted.

The other realistic setup is $20k, for a small company that needs a private AI for coding or other internal agentic use with two Mac Studios connected over thunderbolt 5 RMDA.

That won’t realistically work for this model. Even with only ~32B active params, a 1T-scale MoE still needs the full expert set available for fast routing, which means hundreds of GB to TBs of weights resident. Mac Studios don’t share unified memory across machines, Thunderbolt isn’t remotely comparable to NVLink for expert exchange, and bandwidth becomes the bottleneck immediately. You could maybe load fragments exp…

Depends on if you are using tensor parallelism or pipeline parallelism, in the second case you don't need any sharing.

Re: Kimi Released Kimi K2.5, Open-Source Visual SOTA-Agentic Model

#87

Post by XCSme »

jumploops wrote: post #4

> For complex tasks, Kimi K2.5 can self-direct an agent swarm with up to 100 sub-agents, executing parallel workflows across up to 1,500 tool calls. > K2.5 Agent Swarm improves performance on complex tasks through parallel, specialized execution [..] leads to an 80% reduction in end-to-end runtime Not just RL on tool calling, but RL on agent orchestration, neat!

> Kimi K2.5 can self-direct an agent swarm

Is this within the model? Or within the IDE/service that runs the model?

Because tool calling is mostly just the agent outputting "call tool X", and the IDE does it and returns the data back to AI's context

Re: Kimi Released Kimi K2.5, Open-Source Visual SOTA-Agentic Model

#89

Post by XCSme »

rvnx wrote: post #38
pu_pe wrote: post #35

I don't get this "agent swarm" concept. You set up a task and they boot up 100 LLMs to try to do it in parallel, and then one "LLM judge" puts it all together? Is there anywhere I can read more about it?

You have a team lead that establishes a list of tasks that are needed to achieve your mission then it creates a list of employees, each of them is specialized for a task, and they work in parallel. Essentially hiring a team of people who get specialized on one problem. Do one thing and do it well.

But in the end, isn't this the same idea with the MoE?

Where we have more specialized "jobs", which the model is actually trained for.

I think the main difference with agents swarm is the ability to run them in parallel. I don't see how this adds much compared to simply sending multiple API calls in parallel with your desired tasks. I guess the only difference is that you let the AI decide how to split those requests and what each task should be.

Re: Kimi Released Kimi K2.5, Open-Source Visual SOTA-Agentic Model

#90

Post by XCSme »

coffeeri wrote: post #17
pplonski86 wrote: post #14

There are so many models, is there any website with list of all of them and comparison of performance on different tasks?

There is https://artificialanalysis.ai

There are many lists, but I find all of them outdated or containing wrong information or missing the actual benchmarks I'm looking for.

I was thinking, that maybe it's better to make my own benchmarks with the questions/things I'm interested in, and whenever a new model comes out run those tests with that model using open-router.

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