My 3.5YO daughter has been watching me play a ton of games since the beginning and has grown an interest towards gaming in general.

I let her run on the rooftops in the Arkham and Assassin's Creed games but today I remembered about this game.

I am a Linux user and I was initially skeptical about how this game would run. To my surprise it ran so well, even better than some recent games. I just downloaded it from MyAbandonware, installed using Heroic, loaded the mods and we're already playing.

The community has kept it alive, the mods are excellent, overall it's a flawless experience almost. I've turned free roam on and my daughter's is basically having a blast.

They don't make games like this anymore.

According to the docs the handheld edition of CachyOS uses the LAVD scheduler, tuned for balance of performance and battery life on handhelds. So if I put it in a PC will I see any performance hit compared to the BORE or EEVDF or whatever is the default scheduler in the desktop?

The reason I'm asking is I have my PC hooked up to this TV (ignoring the glares from my wife and mother). Right now it has Bazzite handheld edition. It runs great no complaints, but I'd pick CachyOS over anything else any day of the week.

Before anyone asks, I used AI to erase a thing or two from the image.

Some Background (if you're not interested then just skip to the Next Section)

I work as software engineer and my work involves a lot of backend engineering, some frontend and windows desktop application building and infrastructure. I have been working as an engineer for almost 10 years now so my usage of these LLM tools is complementary not necessary. I use them to do things faster, like having an extra set of hands.

For the longest time I was using the Claude Max 5x plan not because I needed a lot of tokens but because the Pro plan is honestly unusable. During my usage of Claude I could never even reach 70% of the 5 hours quota, at one point I shared my credentials with one of my close friends who works with me to see if we can exhaust the token given to us.

So I was happy with Claude and considering my open source contributions GitHub has always provided me with a generous amount of free premium request on Copilot. So why did I decide to switch right?

The problem began when Claude started to feel like an "elite" model suddenly. Copilot removed it from the Pro plan, using Claude with anything other than Claude Code became less convenient and it started to feel like as if I was getting vendor locked in some ways. I don't like that. I have been a Linux user since 2010 and I love to be able to packup my bags and leave whenever I want, no strings attached. And honestly, I never felt like I was getting $100 worth of usage out of it.

Next Section

This month I didn't renew my claude subscription and got Opencode Go for $5. I started using Kimi K2.6 with Opencode but honestly it didn't feel great. For starters it felt slow and was getting stuck quite frequently. I tried DeepSeek v4 in Opencode and got similar experience, things were getting done but in a slower pace and with more hiccups.

So I decided to change my harness, I set up Pi (https://pi.dev/) and honestly I could immediately feel it was faster. I have used Kimi K2 a lot already, I even had the $20 subscription from them for like two months when Kimi K2.5 Pro came out.

I switched to DeepSeek 4 Pro two days ago and honestly I am very satisfied with this model. It's fast and the output I'm getting is very satisfactory. I can't tell if it's comparable to Sonnet/Opus or not because I really don't care. I'm happy with what I'm getting at this price point man.

I made some UI changes on my personal website today with DeepSeek and I wasn't expecting much from it but it did a very satisfactory job. The redesigns it did to the pages I wanted, the refactor it did to some of the files was very close to if not exactly what I would've done.

Some people judge models on their ability to "oneshot" stuff but I don't agree with that. With all these years of experience under my belt I can not oneshot anything, it at least takes one extra attempt. I have written books on Docker and Kubernetes and even today when I write a Dockerfile or a docker-compose manifest I get something wrong. How can I judge these LLMs who probably have way more context than I do about what I'm trying to do (I rarely know what I want honestly until I've tried a few things out) so I don't care if it can oneshot stuff or not.

Lastly most of the models out there can make things from scratch. I don't care about that, what's more important to me is how well it works in an existing codebase, written by a human or a team of humans. So far deepseek is doing great and in one task it did better than GPT 5.5 for me. I'm usually very specific with my agents, I tell them what they need to do, what files have the relevant code and where else they should look at. I use the Context7 CLI extensively. But today I was vague about one task and DeepSeek thought about how it'd handle that and I could see it thinking "I'll just do this and if I'm wrong the user can correct me", and I liked that.

So overall it is a pleasant experience. The lack of vision was a nuisance in the beginning but I don't care honestly, if it gets a UI wrong I can tell which file or files maybe the culprit and I can point the model to those files.

So if you're looking to try out DeepSeek, definitely give it a go, I understand your use case and needs maybe very different than mine but in general paired with Pi, it is a very competent model. I like it more than Kimi K2.6 because it's coding style is very close to what I do and it feels faster than Kimi K2.6 to me. But I'm speaking from eyeball test so try out for yourself.

Finally

If you're struggling with setting up Pi or deciding on where to get DeepSeek from, please feel free to comment, I'll try my level best to help you out or if you have suggestion that can improve my experience throw them my way.

Peace.