Ornith 1.0 First Look & Test – The BEST New Local Coding Models?

Its happiness level is at 0%, which is just kind of disturbing. Today, we're going to be taking a look at Ornith 1.0. This is a family of models that have been getting a lot of praise recently, and in my most recent video, which was quite a few days ago, and I do apologize for the gap, a lot of the recent comments are suggesting that I test these out on the channel. So, for today's video, we're going to be testing two of the four available, I should say three available versions of these, the 9 billion parameter dense version and the 35 parameter mixture of experts version. I say three available because as of the time of this filming, the 31 billion parameter dense version is not currently publicly available at least on their hugging face, and the 397 billion parameter version I don't have an available system to run that on. So, we're going to be using the two right here, which we can play with for today's video. So, before we get into it, please do feel free to subscribe as I do want that 100k plaque, and I will continue to focus more on open weight models being that the currently newest model, GPT-5.6, is not something really anyone can access, and that does seem to be sadly a point in time where restricted access to frontier intelligence may now become the norm, which is sad, but also shifts focus more onto open weights models like this. However, this is a fine-tune of existing models, mainly the ones we're going to be testing are Qwen models. The only one here that is Gemma 4 would be this 31 billion parameter dense model, which is not currently available, so it's listed but not accessible. And really, the future of open weights, at least in terms of the models these are based on, which the ones we're testing are based off of Alibaba Qwen open weight models, there has not been a lot of noise from them in terms of whether or not they're even going to release any additional Qwen variants. So, seeing what level of performance one can get out of existing models may become something that is more and more popular as time goes on, depending on what the open weight situation is in terms of big labs who are actually still putting out models that are accessible and democratized to those who are not one of the selected Fortune X companies who can access state-of-the-art models. So, with that, let's take a look at some of the interesting things here. These do seem to benchmark very impressively. Now, I have not at all tested these. I ran one prompt to ensure that my config was set up. So, we'll be looking at these results for the first time. So, further down in this blog post, they do talk a bit about what was included in the improvements to these models based off of their previously existing versions, and they talk about the self-improving training framework that jointly learns to solve tasks and to construct the scaffolds that guide those solutions, rather than relying on a fixed human design harness shared across the task category. It treats the scaffold as a learnable object that co-evolves with the policy, and they do talk about using RL right here with GRPO. Now, if anyone's more interested, and I do want to specifically take a moment to show this resource here with all of the stuff that's going on with model accessibility perhaps not being as confidence-inspiring as it was a couple of weeks ago, there is a lot of available resource online. In specific right here, this is Hugging Face's LLM courses, and they do have a lot of good and palatable information about a lot of the techniques that will appear in blog posts for things like this. So, in this case, GRPO is called group relative policy optimization. And if we scroll right here, the core innovation of GRPO is its approach to evaluating and learning from multiple generated responses simultaneously. So, multiple responses will have been generated here, and then it compares outputs within the same group to determine which one should be reinforced. So, basically, the best answer then kind of is used out of that group, and then that pushes the model towards the correct um answer of a group, or just let me read They also give some additional information right here and then we get some scary-looking math on the page as well as a full benchmark table for the different variations of size that are currently available right here, one of which the Gemma 431B is not yet out, but it will be very interesting to see assuming these do stack up how that is. To note for the benchmarks here, these are not one-shot scores. I think they are Okay, so they're averaged over five runs and interestingly they ran them at a higher temperature than the suggested sampling parameters for just like general use, which I do believe based on the Hugging Face model card were 0.6. So, they ran them at one. I don't know why I'm mentioning that. It's probably not as important for a first look and test video. So, with that, let's go ahead and take our first look at the model we're going to start by testing, which is the 9 billion parameter dense version of this. I am going to be running this locally right here at a Q8 quantization on a laptop 5090, which is a 9 24 GB. It's a 24 GB video card. So, of course, we're going to be starting with the Browser OS test V2.5. This is the one where it needs to create functional 3D games. Now, because these models are tunes of existing models, I want to be honest about the potential that some of these prompts may have made their way into the specific training set. It can't be discounted, especially for a fine-tune on an existing model. So, with that, we're going to look at these results for the 9B and the 35B MOE. However, we may try some things that have not really been tested on the channel before just to get a proper test of how these perform on things that would not have been seen in a data set. All right, at a screaming 18 tokens per second, we have received the Browser OS test for the All right, this is our Browser OS result for the 9 billion parameter model. Interesting. Oh, wow. Oddly oddly looking is the term that came to mind. Let's see if there's a right click. Okay, there isn't a right click, which makes me more bullish that it wasn't specifically benchmarked on this test. Now, the main issue we're probably going to notice is this somewhat of a cluster of uh the way that these apps are arranged on the screen and I don't see the ability to actually get rid of them, remove them. Let's try with our start menu. Okay. We do seem to be having some functional issues right here. So, let's take a look and see if we have any specific errors that could be attributed here. Okay. And I'll just because we're using Open Code with the 35B to generate the browser OS, I have just instructed it from within the LM Studio chat to fix these issues. So, I'm going to be running the same browser OS test just using Open Code with the 35B model. This is running through VLLM on the 6000 Pro box behind me. It is not quantized, so this is like the full performance level of this model. I had to change a setting here because the timeout was set too low, so it kept erroring out because the generations are going to take longer, so I fixed that and now I'm rerunning this here. So, we'll be able to side-by-side compare these. I have also noticed that in initiation of giving this the troubleshooting task with the errors for the browser OS, this is back to the 9B in LM Studio. I am looking through the chain of thought and getting a little concerned we may be entering some form of thought loop cuz I keep seeing like a wait {exclamation point}. Sometimes this happens for a while and then the actual result gets spit out properly, so we'll see what happens here, but I'm a little concerned. All right, so it did take quite a while, but as we saw right there, or maybe not depending on when I started re-filming this, this is like a 1,700 or 1,800 line browser OS test that it just created. Again, this is the 35B model version. Sadly, the 9 billion parameter one, I don't know that this is specifically a thought loop. Maybe if this was running at like a thousand tokens per second, it would have actually found the issue. But, as we see right here, this is not looking too good in terms of being able to fix the specific issues we noticed. So, for the time being, let's just go ahead and look at the result we received for the 35B version of this model, which is in its own Web OS folder right here. Okay, so far so good. Not bad. Hey, I'm your new desktop pet. That is actually kind of cool, and I don't believe that is something I've seen from a Qwen model before. I've seen stuff like this from MiniMax. Hello, friend. I kind of like it. Can I move it? Oh, no, but there is a right click. Unintentional right click discovery. Oh, look, it moves. >> [laughter] >> It's kind of cute, like to be honest with you. I like that. It's uh it's a waving at us, I think. All [laughter] right. Toggle pet. Oh, no. All right. Let's Let's leave it there. I like it. I'm back. Good, I like that. It actually has awareness of when it returns to the screen when you re-toggle it, which is actually some level of depth. I know that seems silly to focus on, but I'm actually happy to see that. Look at the little animations, too. It's like Yeah, I'm not quite sure what it's doing. Okay, it's asleep now. Let's check our start menu. Very good. With a search settings. Files. We'll just run through these sequentially. Okay, this is a very well-formed and aesthetic and pleasing non-functional file manager. So, these are all just static. They look good, but they don't unfortunately allow us to click anywhere further. Play with me. Uh not right now, but maybe later. With that hand movement, I think not. Let's turn the pet off for now. Terminal. Neofetch. Let's see if it has anything like cool here. Very good, it has a Okay. Next up, notepad. Save. Does this save it as a text file? >> Yeah, it does. >> Very good. Maybe this one was benchmarked and just not the not the 9B cuz that was quite terrible. So, next up, we have a browser. And it opens to Wikipedia. Excellent excellent and well done. Look at this. We're in a browser in a browser. All right, our settings here. Geometric. Charcoal, sky blue, sunset fire, purple, turquoise, pick a custom background color. That seems to override the other options. All right, GTA clone time. Uh, disgustingly not 3D, but not bad. This is very Look, there's Okay, this is going to be difficult to see at least All right, well, full screening that did absolutely nothing. There's actually like leg animation movements here. This seems to have a penchant for like interesting little sprite style animations. The buildings are interesting. We have a truck right there. The vehicles actually have visible headlights and windshields as well. This really isn't half bad. Health, money, wanted, area, midtown, on foot. The The pet has come in. That may look like a very odd GTA game if someone were to just click to this point in the video and be like, "Uh, from my recollection of Aquantis, if we run over one of these, there may be a red Uh, okay. Good. F is to punch. Yo, what's up? Oh. Oh, okay, they ran inside. So, if you press F, it just kind of yeets them cuz that's punch. Downtown, midtown, uptown, east side. And void. I'm so hungry. Okay, you're you're going you're only away for now. That was good. Next up, we have dungeon, which is like a 3D dungeon. It's actually pretty all right. All right, so unfortunately, we're stuck in this room. We can't get to any of our enemies, but the actual game itself was not bad at all. Then finally, we have pet. Oh, we can perform actions with the desktop pet. So, let's bring it back. It had said it was hungry, so we can feed it. Can we overfeed it and make it bigger? No, that's that's messed up. Where's the GLP-1 button? Nap time. Okay, we'll wake it back up. Oh, play. That was fun. Pet. Purs loudly. And it actually has pet stats. So, its happiness level is at 0%, which is just kind of disturbing from like a empathetic standpoint. Okay, we're going to close this, but this is definitely a very interesting special feature. I do believe I've only seen something like that with Minimax. And then of course, we have the date and time in our locale. Was there a special feature? Oh, that would have inevitably been the pet. Not bad. Definitely definitely a significant improvement over this garbage, which I'm going to go out on a limb here and say this is still not made any progress in terms of actually fixing the issues we saw. Is it still thinking? Yeah. All right, so I'm going to stop this cuz it's just not. Next up, we're going to be doing a version of the beautiful static subway scene. I don't know if this is the exact same prompt that I tend to run in all of the other model tests, but I'm okay with some slight differences because it can throw things a little off, which we do want when testing something. So, I have run this both through OpenCode for the 35B version and as well as the 9B version right here just running locally on this laptop. All right, let's take a look at our subway results. These are just a beautiful static subway scene. This is what we got with the 9 billion parameter model. Okay, now if I can get to the lighting slider, which I can't. This is always a gotcha that stumps less capable models where we do have the adjustable brightness slider. Unfortunately, the only way to get to it is to escape out of the movable scene where it is then locked by the interscene station portion. So, that is kind of regrettable, but nonetheless, we're still able to see at least some artifacts here and perhaps without the bright studio lights pointing at me, this will be a bit more visible in the actual video than what I see right here. We have some elements of a 3D scene and I would say just from what is visible, which there really is not too much visible, this is not a bad 3D result for a model of this size. Although, it is a dense model, so this one's tough to judge, but we do have some individual elements and some interesting artistic posters uh as well as some red and some other things. So, here's the 35B version. Okay. Oh, okay, good. I was about to say, "Okay, the 9B did better." Wow, this is >> [laughter] >> incredibly incredibly laggy. We do have a mini map in the top left, which is interesting, as well as some other This is like really really really clean. Very sterile. I am not even going to begin to question what these things are. These almost look like they were supposed to be conduit on the ceiling, but they're oriented in the wrong way, which is, you know, it happens. We have a tube there as well, which I'm wondering if we can go in it if that is the train. And space is to rise, C is to crouch. Interesting. Oh, okay, so those are actually not like you can't crouch and then uncrouch. It just as you press C, you just continue to go down. So, Okay, so these do seem to be elements of the subway car that are unfortunately just not 100% properly put together. If we go into this tube right here, there are seats and things like this. So, it has some of the elements available, just not necessarily oriented in the correct way. Interesting nonetheless and very clean and sterile as I said. A bit laggy. Lights look good on the ceilings. Interesting. Now, I've instructed both of these two turn their results into an FPS with zombie enemies, weapon recoil, sound effects, etc. and we'll see what we get from that. All right, the results for turning these subway stations into FPS games have been completed. Let's start with the 9 billion parameter model. Oh, click to survive and then you just can't actually click. That's, you know, Now, we also have the 35B version. Okay, subway survival. Enter the station. Did both of these fail? >> [laughter] >> That's just That's just a >> [sighs] >> bit frustrating. I'm giving the 35B one through open code the issues we're facing where the enter the station button doesn't do anything as well as the specific error we got here in the developer tool. I don't really know what to do because this will take so long and I'm worried it will get into a thought loop just because we are using the 9 billion parameter one through LM Studio. All right, so I am glad to see that the 35B subway station results seem to be fixed very quickly. So, let's refresh it and see if we can now actually enter the game. Okay. >> [music] >> Very interesting. A bit significantly more laggy than it was previously, but all right. This sounds like a Maybe that's not a enemy. Oh, I don't think that was an enemy. All right, these definitely are. Yes, so my mistake. All right, let's Interesting grouping of sound effects it chose to use. >> [music] >> All right, I don't think we can actually attack any of these enemies. Oh, hello. All right, [clears throat] try again. And then try again is just like the most like W3Schools tutorial-looking button you've ever seen in your life. All right, let's >> [laughter] >> Let's Yeah, I don't think we can actually do any damage to these things, which is All right, well, it was an improvement because it did fix the issue we were having. So, that's good to see. Now, in lieu of just continuing this stellar result, I'm probably going to exit this and run the same front-end test now here that we are currently running with the 9 billion parameter model. So, I'm giving the 9B a new front-end test that I've been running recently in some of our newer videos, where it needs to create a beautiful website for Slappies Watch Company. The point of the website is it needs to create these assets in 3D, and the hero section needs to have a very cinematic panning good-looking shot of the 3D watch. Then it should have two cards featuring 3D models of the watches as well, just for pricing sales cards. So, it'll be interesting to see what it does for one 3D modeling capability and two overall front-end design capability with this test. So, we will also get our Slappies Watch Company result here from the 35B. All right, so here's the front-end watch website result from our 9 billion parameter model. Okay. Unfortunately, the assets are just not loading properly. Okay, it does say 2026 in the footer, which is good. However, I wonder if there's a trivial error here, maybe like a missing import map or something. Okay, there isn't, unfortunately. I'm going to let this agentically try to fix some of the results that it has generated that have not properly worked at a later point because we're going to use it through open code, and right now I'm waiting for the 35B to generate this result, but I will not just leave the 9B1 through LM Studio entirely, so that's something we're going to do as well. Is see how it can agentically in a coding agent, like Open Code, fix some of its results. In the meantime, we have our preliminary result from the 35B. Now, this yes, it looks a bit silly. I'm going to say for a mixture of experts model at this size, although it is not at all quantized, even in a bit quanted probably have knocked this out pretty similarly. This is not bad. As a matter of fact, that crown there is actually the face, everything. This is a better result than I would have expected to receive here. This is something I've been testing with a lot of new frontier models, at least until we stopped having access to them. But, I'm going to say this >> [laughter] >> this is actually really not bad. This is an impressive result. The 35B1 definitely seems to have some proper chops. With that said, I don't have full recollection of my general Qwen 35B MoE testing, so it is possible that it's not a huge leap, but from what I'm seeing here, independently judging this, I am impressed. Now, this is where the tests are going to start to differ a bit from within Open Code for the 35B model, and I'm just starting it from within build mode, not in plan mode. I'm giving this a C++ test, however, not the skateboard one, because that is probably pretty decently known at this point for a C++ test. This is to generate a 3D racing game with retro rally game style aesthetics to it. Okay, it is asking for permission now, which is good. So, it has created or written some of the script for our skate game. Oh, it's not a skate game. The problem is that I put it in a folder named skate. So, this is a 3D racing game. Keep that in mind. I had just tripped myself up. So, this really took this prompt and the combination of what I'm trying to say here is this is about as like bare-bones in a way that it's trying to make it that it could have to the point where I'm not 100% confident that it's actually going to produce a successful result, especially because for some reason there has skake or skate. I don't think that's a mistake that I made. I should probably check, but yeah. Okay, that's All right, we'll see what happens. All right, unfortunately, the C++ racing game just needed to be stopped. It wasn't likely to work. And it was taking quite a while. So, unfortunately, regrettably, we're probably going to have to omit that from this specific test. So, I'm giving this very simple instruction here with an image, of course, as well to create an interactive functional 3D model of this image. I would imagine this will probably just end up using 3.js or something. Looks like a plywood box. Uh no, that is high-quality PLA plastic 3D printed, but we can excuse that. All right, so here is our image to 3D model replication test from the 9B. Okay, uh unfortunately, and keep in mind, this is a pretty difficult prompt for this to have knocked out. So, at this point, I think I'm probably going to hold off on running additional tests through LM Studio from the 9B because I'd like to see how capable it will be in fixing some of its initially generated but broken results. But, something I would like very much to do now is swap this so the 9 billion parameter model is in open code and we'll give it a chance to fix some of the issues it had with the scripts that were generated just through LM Studio. All right, so we now have the 9 billion parameter model from the system working in Open Code and I want to start with having it try to fix the image to 3D model generation test. So, I will just say fix this issue and paste in the specific error that we had. It is in a directory with only the script. We now supposedly have a fix to at least that specific error that was happening. I should also make note that I moved it into its own specific folder, which is why the file had disappeared there. Let's see if we You know what? That's not half bad because Yes. Okay, it's half bad. The reason that I say it's not half bad is because it did do a decent job of actually replicating some of the things that were on screen. The vision capabilities in the bundle that this is based on, which is the Qwen 3.5 9B dense, were always pretty good. Unfortunately, we don't have the full picture here of the shape of the arcade machine, but there are elements of it that are included such as the red joystick and the screen. So, I'll say that this is actually for a 9 billion parameter model at a Q8, especially trying to replicate something from an image into 3D, I'm okay with this, which may seem weird because it's not a great result, but it shows some promise. Next up, I'm going to try to tackle the Subway FPS game. So, I've just given it the script in its own directory and said the game is too dark and the game can't be initiated when clicking the button to start it. So, we'll see if we get a functional result. All right, we now supposedly have a fixed Subway result as well. So, this was the 9 billion parameter model. Okay. Well, unfortunately, this one did not work. This was a more complex fix, likely. It is a little disappointing as I I kind of feeling excited and hopeful that this would work, but regardless, it's just interesting to see to what level of completion we can get some of these. The last one that I would like to attempt to have this fixed is the watch website where it needed to create the 3D models, and unfortunately, those just never really showed up. So, we do have a specific error to give it here. So, we're going to have it try to fix the watch website where basically none of the 3D models were appearing, and it'll be interesting to see if we get it because the 35B result for this was actually quite good all things considered. That was a very quick fix. So, if we look at the reloaded version here. All right, unfortunately, we're still not getting our 3D models. However, it is possible that a new error has appeared. Interesting, it's saying the fix is correct. You may need to hard refresh, which I did do prior to sending it that. So, let's refresh it one more time. We'll hard refresh it. It is still giving me the same issue. I want to verify just that like we're actually working from within the same directory, which we are. Okay, let's try opening it in Firefox then. And we still are not getting functional watch models. Interesting. So, I'm giving it some pushback saying it's a console issue. It still shows after a hard refresh, and the watch models don't appear at all. All right, unfortunately, this just didn't quite work out. However, I do have one final thing that I did do as a bonus on the machine behind me. So, I gave it a very simple prompt, the 35B version at a Q8 quant. I said, "Make me a 3D speedboat game." And we now have that file. I've not looked at it, and I'm excited to see what it did. So, let's see if we got a decent speedboat game or not. Okay, so, that is huge letdown. And unfortunately, I don't really have the desire to try to fix this right now. It was just like a one final thing. So, that is going to lead us into probably the closing thoughts for these models. They do seem good, but I want to preface saying that with I don't fully have recollection in my mind freshly how the 9B or the 35B A3B for these Qwen models performed that these are based on. So, I can't definitively give a judgment like it's significantly better, it's significantly worse. I will say I was impressed with mainly the 35B model that I saw. Some of the things it generated, especially for a mixture of experts with such few active parameters, were really quite decent. Things like this watch website, not that one, the one that actually worked, this 3D watch model right here that this knocked out, as well as the proper spinning hero section was really not half bad considering that this has proven to be quite a challenge for models significantly larger than this. So, I was quite happy to see that right there. Additionally, let's see, what else do we have? So, I had moved some of these one just trying to have the 9B fix them. The arcade machine that was multimodal coding test base that the 9B model initially failed to produce anything at, and then subsequently fixed through open code, it did a really good job replicating the screen and everything on there because the vision component to the model this is based on was very strong and still is. It also had some aspects or elements of it like the joystick and the black base. Not great, but something that started out as not even showing anything and we were able to fix it with that model, which was nice to see. Unfortunately, the 9B never really got the subway station or the watch website working properly. Additionally to that, the web OS that the 35B model created was really actually quite good. This little like desktop pet was very cool except for when it's like satisfaction or happiness just stayed at 0%. It was a little concerning. The 3D game that it implemented here was quite neat. Really something I was quite enamored with even though it wasn't fully 3D was this GTA clone. It had a lot of interesting immersiveness even to the walking animation in these little sprites and then the ability to punch was kind of funny. So, I very much liked this result. This was a very proper result. Unfortunately, the 9B1 had some interesting hope or potential to it with the aesthetics that we see here. It just never really quite worked properly and I didn't think it was worth trying to have it fixed through open code cuz it's more of a simple test. The subway game that was created with the 35B again. This was really very clean. Now, oh look at that. Some of the logic unfortunately didn't really work where we couldn't actually put damage on any of these enemies, but they could put it on us. Nonetheless, this was a very sterile and clean result in terms of the 3D items that were created and this was a follow-up test to turn it into this survival game with zombie enemies. So, that was cool to see. I would say just in a light testing here, the 35B definitely seems to be the winner of the two with the caveat that it was run on the Blackwell card at full precision. So, it wasn't quantized at all. So, that'll give it a little boost in strength as well versus running the 9B as we did in a Q8. But, the 9B definitely seems decent if you have a card that is a good fit for that 9 billion parameter model. I would definitely say it's worthy of trying and really the thing to do would probably be a head-to-head just to see how the results stack up compared to the model it is based off of as sometimes the fine-tunes can make things better or make things worse. In this case, I don't believe it made things worse. I could definitely see that there's a genuine improvement here just based off of some of the performance we saw on a few of these tasks. So, that is probably going to conclude our first look and test of the Let me get the name right so I don't butcher it. The Deep Reinforce AI Ornith 1.0 models, mainly the 9B and the 35B MoE. I am very interested to see two things. One, if they come out with the 31B that is based off of Gemma 4, that could potentially be a pretty potent option. Additionally to that, I would love to see a version of this that is created from the dense 27B Quen model, which still is probably one of the best local coding models that exists. And I am slightly concerned it may continue holding that position for the foreseeable future, just depending on the way Open Weights goes and access to frontier models. So, there's definitely a change going on, and I would imagine a lot of folks are going to be more interested in Open Weights models and things that run locally like this. So, I absolutely wanted to test these, and that's going to wrap it up. So, if you have any questions, please feel free to leave them in the comments, and thanks for watching.