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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

#211

Post by 2001zhaozhao »

The directionally interesting part is that according to the announcement, K2.5 seems to be trained specifically to create sub-agents and work in an agent swarm usefully. The key part is that you don't need to manually create or prompt sub-agents, K2.5 creates them automatically, so from the looks of things it's similar to Claude Code dynamic sub-agents except the model is trained to scale to many more agents autonomously.

I wonder whether Claude is doing the same kind of training and it's coming with the next model, and that's why the agent swarm mode in Claude Code is hidden for now. We might be getting very very good agent orchestrators/swarms very soon.

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

#212

Post by culi »

I posted this elsewhere but thought I'd repost here:

* https://lmarena.ai/leaderboard — crowd-sourced head-to-head battles between models using ELO

* https://dashboard.safe.ai/ — CAIS' incredible dashboard

* https://clocks.brianmoore.com/ — a visual comparison of how well models can draw a clock. A new clock is drawn every minute

* https://eqbench.com/ — emotional intelligence benchmarks for LLMs

* https://www.ocrarena.ai/battle — OCR battles, ELO

* https://mafia-arena.com/ — LLMs playing the social deduction game Mafia

* https://openrouter.ai/rankings — marketshare based on OpenRouter

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

#213

Post by PlatoIsADisease »

simonw wrote: post #194
PlatoIsADisease wrote: post #182

Earlier quoted context omitted.

Is there a catch? I was not getting anything like this on a 70B model. EDIT: oh its a marketing account and the program never finished... who knows the validity.

I don't think Awni should be dismissed as a "marketing account" - they're an engineer at Apple who's been driving the MLX project for a couple of years now, they've earned a lot of respect from me.

Given how secretive Apple is, oh my, its super duper marketing account.

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

#214

Post by mohsen1 »

Alifatisk wrote: post #156
mohsen1 wrote: post #154

Earlier quoted context omitted.

tell me more...

Go to kimi chat, there will come up multiple suggestions of use cases. One of them will be the bargain robot. If you download their mobile app, the challenge to bargain will probably popup too! Depending on how well you bargain with the robot, you can go as low as 0,99$ (difficult). Either way, their moderate plan doesn’t have to be 20$. The agent wants a good reason for why it should lower the price for you. Here’s…

omg this is so funny!

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

#215

Post by tucnak »

PlatoIsADisease wrote: post #177
tucnak wrote: post #151

Earlier quoted context omitted.

Mac studio way is not "AI on CPU," as M2/M4 are complex SoC, that includes a GPU with unified memory access.

If it worked IRL for anything useful, I'd be more interested in the technical differences. But it was a mere toy for a few tests at my fortune 20 company. Language is full of issues of particulars vs universals, and you could debate if its just an integrated GPU with different marketing. Whatever the case, we couldn't use it in production, and NVIDIAs stock price reflects the reality on the ground.

Well, I've been using a fine-tuned variant of Gemma 3 model since it came out, and some embedding models, on a laptop. It's not "useless" by any means, in fact it still beats the latest Claude for my use-case in Ukrainian. Not to mention that if you travel by train a lot, you will find it quite useful. I own a Mac studio M2 Max (96 GB) variant at home, and I'm routinely using the larger models for the kind of stuff I don't wish to share with model providers.

My 2 cents

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

#216

Post by Alifatisk »

in-silico wrote: post #207
Alifatisk wrote: post #93

Earlier quoted context omitted.

Yup, I experience the same. I don't know what they do to achieve this but it gives them this edge, really curious to learn more about what makes it so good at it.

A lot of people point to the Muon optimizer that Moonshot (the creators of Kimi) pioneered. Compared to the standard optimizer AdamW, Muon amplifies low-magnitude gradient directions which makes the model learn faster (and maybe gives Kimi its unique qualities). Muon paper: https://arxiv.org/abs/2502.16982

Wow! Thank you

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

#217

Post by spmurrayzzz »

zozbot234 wrote: post #131
spmurrayzzz wrote: post #128

Earlier quoted context omitted.

When I've measured this myself, I've never seen a medium-to-long task horizon that would have expert locality such that you wouldn't be hitting the SSD constantly to swap layers (not to say it doesn't exist, just that in the literature and in my own empirics, it doesn't seem to be observed in a way you could rely on it for cache performance). Over any task that has enough prefill input diversity and a decode phase th…

> hitting the SSD constantly to swap layers Thing is, people in the local llm community are already doing that to run the largest MoE models, using mmap such that spare-RAM-as-cache is managed automatically by the OS. It's a drag on performance to be sure but still somewhat usable, if you're willing to wait for results. And it unlocks these larger models on what's effectively semi-pro if not true consumer hardware. O…

I've tested this myself often (as an aside: I'm in said community, I run 2x RTX Pro 6000 locally, 4x 3090 before that), and I think what you said re: "willing to wait" is probably the difference maker for me.

I can run Minimax 2.1 in 5bpw at 200k context fully offloaded to GPU. The 30-40 tk/s feels like a lifetime for long horizon tasks, especially with subagent delegation etc, but it's still fast enough to be a daily driver.

But that's more or less my cutoff. Whenever I've tested other setups that dip into the single and sub-single digit throughput rates, it becomes maddening and entirely unusable (for me).

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

#218

Post by codexon »

WhitneyLand wrote: post #129
johndough wrote: post #81

Earlier quoted context omitted.

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 t…

Its often pointed out in the first sentence of a comment how a model can be run at home, then (maybe) towards the end of the comment it’s mentioned how it’s quantized. Back when 4k movies needed expensive hardware, no one was saying they could play 4k on a home system, then later mentioning they actually scaled down the resolution to make it possible. The degree of quality loss is not often characterized. Which makes…

Didn't this paper demonstrate that you only need 1.58 bits to be equivalent to 16 bits in performance?

https://arxiv.org/abs/2402.17764

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

#220

Post by overfeed »

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?

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

How many millions did Google spend on Android (acquisition and salaries), only to give it away for free?

Usually, companies do this to break into a monopolized market (or one that's at risk of becoming one), with openness as a sweetener. IBM with Linux to break UNIX-on-big-iron domination, Google with Android vs. iPhone, Sun with OpenSolaris vs. Linux-on-x86.

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