K2 Horizon: A connected fleet of six open models

piinbinary

A bit off topic, but I think I'm starting to get model fatigue. These come out 10x faster than new Javascript frameworks were coming out 10 years ago (at least new models are far easier to adopt).

kamranjon

it's funny that the tagline is Radically Open, but you're immediately hit with http login - maybe this was the wrong link?

jjordan

Fully open models really need to be a big part of the AI future. That includes all source code, open training data, how it's organized, fed to the model, processed, etc. Until that becomes a thing you're always going to be left wondering what exactly lies underneath the closed model you are using, leaving open the possibility for societal manipulation.

jon9544hn

Here’s the link (K2)[ https://ifm.ai/k2/ ] as the originally linked link is a login url.

sottol

The press release: https://ifm.ai/k2/press-release/

luckydata

both repositories for pre-training and post-training are actually empty... someone might have jumped the gun on the release.

afzalive

Not to be confused with Kimi K2. Out of all the names they could've used, they picked one that would be confusing.

mmastrac

The comparisons with other models here are odd.. the other models change depending on the task. It would be far more useful to at least compare against the more recent open models (DS4Flash/GLM53Flash/Qwen38).

a11r

It is great to see another player introduce a fully open stack. Nvidia's Nemotron is the only other prominent one I know of. All that said, the headline claims do not match the self-reported performance. For example, the dense 32B model is significantly behind Qwen3.8 27B (chart towards the bottom of https://ifm.ai/blog/k2 ). Gemma4 31B is not in the comparison set. This is the most important sweet spot for self hosted open-weight models today and real competition here will be very welcome.

uniclaude

Seeing this the day all major closed LLMs went offline is quite the reminder of how valuable open source can be.

prometheus1992

Nice! can't wait to add these in my local stack and try them out.

villish

Frontier. Everything is frontier. K2 not to be confused with the other K2, or K3 that is also frontier.

luciana1u

i'll believe 'radically open' when the training data ships alongside the weights. until then it's a very fast demo.

cesarvarela

I find it funny that while these releases are a technological miracle, the charts in the doc use tiny fonts and are hard to read. Goes with the idea that coding might be solved, but taste isn't.

TechSquidTV

I attempted their chat demo to see the speed and it stated the model couldnt be found. edit: Tried signing up and using the internal playground. Holy shit thats fast.

cogman10

My quick review of the 3.7B model (because I was interested) is that it's not to be trusted for coding. It failed my basic test I like to ask models and generated incorrect code. When prompted about the bug, it preceded to start hallucinating non-existent APIs. After doing that it got caught in a loop trying to desk check the solution that didn't work.

justin_

I'm glad to see some development in the space of "truly open" models that share training data and other recipes. As the costs for hardware fall over time (hopefully), we should see more possibility in fine-tuning and developing software to inspect the source training material. Some other open models I'm aware of: - OLMo - Apertus - Soofi - OpenEuroLLM - llm-jp OLMo is perhaps the most famous, and their Dolma training corpus has been reused in other projects. It looks like the K2 training materials haven't been released yet, but I'm interested to see what they did for training "long-horizon agentic tasks". I'm aware of SWE-smith + SWE-gym but I'm guessing there's a lot more out there now. I'm no expert, which is part of why these projects excite me. I'm hoping they can be good projects to learn from as well.

kzrdude

The Uno "diffusion adaptor" will take a while for me to understand, but sounds very interesting. https://huggingface.co/IFM/K2-Horizon-7B-Uno

throwawayffffas

While the open approach is commendable. The 32b and 36b models are inferior to qwen 3.8 27b, at least according to benchmark numbers. I would have liked to have seen both compared to 27b, not only the dense one. Also would have liked to see more coding benchmarks in the full table.

RandyOrion

Good to see new open source/weight LLM families. Waiting for the final release of https://huggingface.co/IFM/K2-Horizon-32B .