I started doing this benchmark, seems like a good way to test model's abilities. I think sometimes too you can just "roll a bad seed" where the model goes off to neverland trying to solve a problem before it even starts.. The prompt is simply this "I want you to create an internet radio streaming player for me in C#. It should stream . It only has to run a single stream. I want the UI to be a console app with a TUI. The UI should show the title of the radio station at the top, and it should have volume control with a volume bar indicator, and should also include a dynamic audio level meter that animates to the signal" This one prompt kicked the Qwen models pretty hard. Testing on an RTX 3090 system with 64gig RAM Qwen 3.8 27B (Q4_K_M GGUF from Unsloth) with 8 bit KV Cache running in Llama.cpp (llama-cpp-windows-manager) with 119K context, MTP turned on (level 2?), 70tok/sec average: I'd have to say actually that 27B does a better job of it in the *code* aspects than Qwen Next Flash did. It even found the correct streaming URL in a couple of turns and started putting code together. But I had to go round-around-round quite a bit until it played the sound correctly, and then round-the-round a lot more to get the audio level meter functioning correctly and responding properly quick to the audio (and be in sync). The model decided to use NAudio for the playback and another library for the TUI. It kept going in circles trying to get the audio to play correctly for a while, and eventually I guided it to use a simpler API in NAudio that can just play a stream directly (URL is a single parameter) and then things started working. I'd have to say though Qwen 3.8 27b definitely doesn't give up and it was excellent at creating test "probe" apps to verify if something was working correctly or not, great debugging skills. Qwen 3.8 Next Flash, IQ3_XXS, 8 bit KV Cache running in Strata with 128K context, 120tok/sec average: The first time I ran this prompt it burned up over half my tokens just trying to find the correct streaming URL MP3 link. So I canceled that session and handed it the link directly. This time it started to do a lot better, but instead of using a simply API call to play the MP3 stream it decided to just grab MP3 packets and decode them itself (somehow. I mean that's what it looked like to me in the code, but it still does NAudio). This naturally led to a lot more mistakes, so it took quite a few rounds until the sound would play without glitching or gaps. Then, same as Qwen 27b, I had to go a rew rounds to get the audio level meter working correctly. One big plus, it was much better at laying out the TUI layout the first time through. Qwen Next Flash also decided to use NAudio but it used a more complex API calls, forwarding the MP3 stream data somehow on its own (I only looked briefly at the code). It didn't use any library for the console TUI. I don't know exactly how that part works and didn't examine it in depth but I can say the TUI is great and the layout was great right away. But I did have to mess around back and forth on the audio level meter . It's still not 100% in sync with the sound IMO. Once again Qwen Next Flash did a great job at troubleshooting and creating little test apps to verify things would work or not. Both Qwen models took me at least two hours to get a proper functioning streaming player with a TUI up and running from scratch in a new directory. And they only needed to play a single station. I think this "knowledge" of how to play a stream is complex enough to test model abilities. Both Qwen models even went so far as to try and download source code from GIT for the libraries being used, and if that didn't work, they both attempted to use reflection to find the correct API's to use in the libraries they had pulled. Which was pretty neat to see. They simply kept working and trying as much as possible. GPT 6.1 Sol (High reasoning): (I tried this prompt at work) It one-shots the prompt giving me a WPF UI app with a C# playback engine, and included entire search feature that allows me to search for other stations, and favorites, and everything. And it works out-of-the box, 100% correctly. That was pretty impressive. Sol took about twenty minutes and cost 69 cents to create the app.   submitted by   /u/Perfect-Campaign9551 [link]   [comments]