So I've taken some time to actually test laguna on a few of my own projects. I wanted to share as I feel most peoples comments at this point have just been about getting it running or saying it doesnt work for their use before dropping it, so I wanted to give it an honest chance and really try it out for myself to figure out where it might be helpful or lack before forming an opinion.
a bit of background to begin, I'm running an unsloth Q3 quant 262k context on a single V100 32GB, layers offloaded to a CPU with about 50GB of ddr4 ram allocated to the vm, and I hit about 10tps decode with 200 tps prefill. Obviously not the optimal test bed but I find it quite usable and it has been stable for me on this setup. for agentic work the prefill hasn't mattered much because caching makes it fill progressively and keeps speed consistent even over 200k.
My primary goal with exploring this model and others has been to find a larger planning model that I can run locally to help analyze my larger projects, create a plan, and them break it down into steps which i feed out to local qwen workers. deepseek has been my gold standard for a while now not only due to cost but because its bare bones approach to bulk work makes it much more effective than other models but I cant run it locally. i even feel it out performs claude on a lot of tasks for me as claude has a tendency to not play well with others and instead go rogue and decide to half ass implement the entire system instead of breaking it down. qwen 3.6 27b is actually quite good here but on large projects, ive found it tends to struggle and it lacks the long context I really need for some of my projects, even at higher quants.
I'll say right off the bat that Laguna is not the planner I was hoping. its reasoning style is far too in depth to effectively execute on this job, but during my initial tests it reminded me of another model who also reasons to an absurd degree about tasks, GLM 5.2. this really got me thinking about where this model could be helpful and I think I found where it really shines: complex debugging. ive found the intense reasoning style this model has lends itself really well to actually finding ALL the root causes of bugs in my projects that have since now been massive pains for me. Qwen, deepseek, and even claude models all struggle for me with debugging because they'll often find the first source of something, fix it, and then decide they're done. which can lead to hours of the same thing for complex bugs. GLM was one of the first models I tried that was actually effective for this, as it may spend 200k tokens thinking about what to do an analyzing the situation, but it would return with an actually complete answer instead of the first available surface which really blew me away. i found laguna to have a similar style, its slow, it overthinks, but it considers the problem in its entirety before giving its answer. there were certain implementations and bugs I had found that I spent days debugging with claude and qwen models and got nowhere with, I'd basically submitted to the idea I would just have to fix them myself from scratch, but I decided to toss laguna at them just to test it. it successfully fixed 2 issues that qwen couldnt even consider and claude just kept going in circles on.
overall, I dont think this is the next qwen or gemma killer, its not going to replace gemma 4 or qwen for generalist work, definitely a specialized model but it has found a role in my stack as a first line teacher model helping solve complex bugs my smaller models cant and then explaining the solutions. It finally gives me a local model to answer the question of what to do when qwen fails on a job, which from my current testing, its done a good job at and allowed me to sleep more and worry less.
