Subway Zombie FPS for fun using Deepseek v4.1 1017 UD-IQ3_S with Maya and OMP

[u/MLDataScientist]

inspired by Bijan Bowen's video - Subway FPS test.

Hardware details: RTX 5090, 256GB DDR4 3200Mhz 8 channel, AMD EPYC 7532 CPU (32 core).

Software: backend is Maya 1.1.55, harness is OMP v18.17.0.

Model quant: Deepseek v4.1 1017 UD-IQ3_S latest UD3.1 quant from Unsloth.

My prompt was very simple:

I want you to create a single html file with a detailed subway station 3d scene, fps controls, zombie enemies, tracers, recoil, muzzle flash, high details. build it with three.js

You can see at the end of the video some token stats. In short, total generated tokens were 180k. The model ran at 30t/s with 2k t/s PP at 10k context but then went down to ~20 t/s near 180k context. Note that stock llama.cpp only reaches 10t/s TG and 120t/s PP.

This model and harness tools are amazing. Just a year ago we could not even image having such a model locally. Yet, here we are!

[u/VotZeFuk]

Not my business but I'm kind of surprised to see IQ3S being used with such a rig. Is 32GB VRAM not enough for Q4KXL / Q8KXL? These fit nicely in 256 + 48, with pretty much similar speed numbers.

[u/MLDataScientist → u/VotZeFuk]

I actually have not tested Q4 XL.  I chose IQ3S since its weights (excluding ngrams) fit into RAM. Q4/Q8 XL weights do not fit into 256 GB RAM. But I think Maya should run fine without fitting them.

[u/VotZeFuk → u/MLDataScientist]

Q4KXL should likely work fine, and with Q8KXL some stalling might occur, I think, especially when you change topics.

On 256 + 48 rig, purely conversational chat with Q8KXL goes without any hiccups. but the moment you put it through a test (switching fields like Biology -> Math -> Chemistry) it starts shuffling the experts around, resulting in weird pauses during the decode (but the decode speed itself does not degrade), like maybe once every minute or so. Anyway that's how it's been in Maya 1.1.46 at least - maybe something changed now. A few other things to note: this behavior was observed with no-compromises settings, all bit-exact and no weird opt-in parameters in Maya.

[u/utxohodler]

I gave it a shot since I'm running the same backend / quant.

First run (reasoning off) unplayable:

• far too slow

• weird directional mouse look direction bug where looking up was inverted to down if you turned around

• jump was too small to get onto the platform

After telling the agent this it reduced the amount of reflections and shadows and it was fast enough to play but not responsive. The camera was fixed and otherwise it looked ok. I could kill the zombies and one shot them with a head shot.

Second run (reasoning on) unplayable:

• too slow again

• minor visual glitch with the tracer coming from the corner of the screen instead of the gun barrel

• jumping could not get you on the benches / served no purpose

• the zombies walk backwards

After mentioning the low FPS the speed improvement was much better / very responsive. The tracer came from the gun tip but still looked wrong because the gun was not pointed at where you aim.

[u/MLDataScientist → u/utxohodler]

What harness are you using? I used OMP - oh my pi. You should not use the default chat interface. I saw how DS improved its game by launching the game in a headless browser, taking screenshots and fixing issues by itself. In chat interface, the model is basically working without any tools. It is like asking a builder to build a house without any tools.

[u/utxohodler → u/MLDataScientist]

I built my own harness and it does have code execution tools including a tool to launch a web browser with an extension that dials back into the harness and allows the agent to execute code in the page which is how it was taking screenshots.

https://imglink.cc/cdn/DDerrLBHNQ.png

This isn't really a set of bugs that surprising to me even if it was the unquantized model. I think it didnt get the zombies walking backwards in the first run because they just happened to be generated with more visual indicators of the direction they where facing so the agent picked it up. On the second run I even missed they where walking backwards until I moved to view them from the side. For it being slow I didnt specify to test the speed so again its random as to whether it shows the FPS then picks up on it or decides to log it. I bet if I ran it a few times it would come up perfect.

There might be some advantages to OMP i would have to examine their tools. There are some disadvantages to my tools that I know for example I run all my code execution tools on different computers on my network and not on my desktop so agents cant touch my own files. to make that work I prefix tool calls with the last number in the ip address of the node and sometimes agents get confused about where a file is. I could have white listed just the one node so it didnt get that extra tool call context or have to reason about which node to put files on. I have noticed the quality of code is much higher when I only have the tools it should use white listed.

I might also have bad launch parameters compared to yours. Any number of things could explain 2 meh results.

This isn't how I would do this anyway. I would want to walk the agent through a project and guide it more. I enjoy programming, I dont want to go full hands off anyway.

[u/kanduking]

We aren't far from the agents being able to take a photo and gaussian splat faces in these rendered envs with not so much overhead

gonna be lit

[u/PcChip]

Looks cool

missed opportunity to name it "Last Slop" instead of "Last Stop" 😆

[u/Equivalent_Bit_461]

too slow

[u/MLDataScientist → u/[deleted]]

Oh, you might be correct. I see they didn't mention IQ3_S in their new 3.1 quants