WEBVTT

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Were you looking for America's next top model?

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Meta's Muse Spark might be for you.

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On this channel, we look at AI models that you can run on your own

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infrastructure, and typically that means the GPUs and

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the Apple Silicon Macs that you already have at home.

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Today it doesn't.

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We're going to look at something that was run on 2 rented B200 GPUs.

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Now, Meta's Spark Open is basically Lennie from Of Mice and Men.

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It's a giant at 842 billion parameters.

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It's mentally handicapped, getting about the same score as

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a model literally 30 times smaller than it

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on Bob-Bench.

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And if you've read the book recently, you'll know that Lennie absolutely

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adores small fluffy animals.

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And so does Spark.

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All right, the end of last year, we're like, all right, we are quite

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excited about the progress.

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We haven't seen the models yet.

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You sure this is gonna work?

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Now, Bob-Bench Wide is a specific comparable

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test set, okay, it measures a model configuration

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on the same 86 tasks on the same hardware,

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a single 4090.

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And let's take a look at a few specific dots on this plot.

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I know it's complicated, but even if you're a consumer of Meta's

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AI offerings, I know that you're smart enough to follow along.

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The highest score in Bob-Bench goes down to

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Qwen 3.8 Flash Next, running on a fork of Strata.

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On specifically, the IQ3_XXS quant.

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It got a 92.9% in almost 5 hours.

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This ran upstairs at my house.

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On a GPU that is relatively pricey at around $2,300

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and that GPU has been increasing in value

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exponentially since I bought it.

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Another spot on the frontier here goes to Qwen 3.6

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ThinkingCap, which is a 27-billion-parameter model coming

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in at just over 4 hours.

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It got an 89%, which is worse than Spark Open.

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Good job, Lennie.

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You beat up a model 30 times smaller than you by one point.

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So Spark Open.

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We set it up on stream today.

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According to the model card, it needs an incredible 700 gigabytes

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of VRAM to run.

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You could literally buy a house with that kind of hardware.

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Now, regardless, we rented

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2 B200s, and we downloaded the

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IQ3_XXS quant.

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Now, if you're good at math, you'll remember that that's the same quant that we

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used earlier for 3.8 Flash Next, okay?

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Again, 3.8 Flash Next is

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like 4 or 5 times smaller than Lennie.

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Anyways, we fired this thing up on llama.cpp with low reasoning.

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The entire mess fits into VRAM this way on 2 B200s.

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You get 128K context with

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a Q8 KV cache.

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And this was rented for less than the starting average

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wage at In-N-Out Burger.

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I paid $16 per hour on RunPod for this run.

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So the llama commit is here.

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We ran the Unsloth IQ3_XXS quant, Q8 KV

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cache, like I said, 128K context, sampling from the model card.

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No spilling the system memory.

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We were getting 569 tokens per second prompt processing, and

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41 tokens per second decode.

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So, again, let's compare that to Flash Next, all right?

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2500 prompt processing, and 93 tokens per second.

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So it was much faster for Flash Next.

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And this configuration for Lennie used a

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staggering 324 gigabytes of VRAM.

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So moral of the story is, if you

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want to run on tremendously

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expensive hardware and get the same score as Qwen 27B,

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this could be America's next top model for that use case.

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Otherwise, I'm not too interested in it.

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There is a couple problems with comparing it this way, and one is that the hardware

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needed to run Lennie is just impossible to come by.

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And then the other is that we ran it on light reasoning or

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low reasoning as opposed to medium for Qwen 3.8

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Flash Next, but the difference in score is

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phenomenal here.

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And because it's so expensive to test, and I can't run it at home,

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it's not likely for me to go back and revisit this with different

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sampling parameters or with different reasoning.

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It's just not impressing me enough to

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look like it's worth it, especially when it's 842 billion

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parameters, and, you

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know, hundreds of gigabytes to download a different quant.

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So, um, in any case,

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we'll settle this like men do with

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a skateboarding game.

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We'll start here with the version of the 2D skate

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game that was created by Qwen 3.8 Flash Next.

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Check it out.

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I'm not going to read the

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I'm not going to read the instructions.

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Okay, we'll see if that makes any difference.

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Here we go.

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Go off the ramp.

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It looks like we need the ollie.

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Okay, so it looks like the controls for

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ollie are.

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Yeah, so you have to kind of front load it with a spring, which is kind of cool.

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Ouch.

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Okay, don't hit the green box.

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I think I'm getting it.

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Can we clear this gap?

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No, you have to, you have to kind of race the jump.

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So it seems like the mechanic of this game and this version of it

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is all about how you ollie.

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So yeah, hold the charge space.

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You can tap left or right in midair to spin.

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Oh, and you can kickflip.

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Ooh, changes color after you kickflip.

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All right, we kickflip twice and got a big air with a bonus.

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All right, I think I'm I think I'm seeing how it works here.

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I'm going too fast.

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So if you hold If

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you hold D to get a bunch of speed, it's pretty difficult to get through the map.

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So it seems like slowing down and braking

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would really help.

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Can you just do a stationary kickflip?

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Slightly better at skateboarding than I am.

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So, I mean, this seems to be reasonably,

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whoa, front flip.

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So you'll notice that the character did a backflip, but then got points for a front flip.

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So Qwen 3.8 Flash Next.

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Should have figured that out.

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Let's try that again.

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Okay, so that was a double backflip, and then we fell into the gap.

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So if you do a backflip, you get points for doing a front flip.

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All right.

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That's enough.

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That's enough.

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So that's how Qwen 3.8 Flash does it.

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And let's see, Neon Grind.

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So this is implemented by Meta's Muse

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Spark Open.

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You guys think it's going to be good?

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Whoa, bailed.

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We got a 112.97-66-7876.

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There's our guy.

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Um, Oh,

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whoa, you can really get a lot of velocity

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on those turns.

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Holy cow.

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If you get into the air, you can really spin and do a front

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flip like 70 times.

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That's crazy.

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Dude, this is way worse than I thought it was going to be.

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Okay, so W and S allow you to accelerate.

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And then as soon as you press space to ollie.

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You are doing a flip.

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Okay, this is terrible.

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Holy crap.

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This is way worse than I thought it would do.

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The character has like no definition.

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It's just like a air hockey puck.

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And by the way guys, this is the first time I'm seeing this.

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Not at all in the same league as this game, which has some

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had some gameplay, had sort of a loop to it, had some mechanics,

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The scoring seemed pretty reasonable.

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The front flip was not very reasonable.

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So that's actually a backflip.

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But, you know, I can't really complain too much.

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And also, the control scheme is just a lot more a

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lot more sane and comfortable here in terms of using

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A and D to go left and right as opposed to W and S.

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And we'll decide who the real winner is based on

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the results of these 2D skateboarding games.

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In conclusion, I'm not going to spend any more time on this model

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until I get 2 B200s at home.

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What I've seen isn't promising.

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It's possible that in higher reasoning modes, it could act differently, but it's

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not a very verbose model.

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It gives up really early, even when it's successful

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and completes the task fast.

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It does it with very few tokens used.

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So even though it ran slowly on these 2 behemoth GPUs.

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Not that interesting.

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All right, guys, thank you for listening.

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Appreciate you watching the short video on Lennie,

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and I will see you in the next one.
