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VibeThinker: 3B param model that beats Opus 4.5 on reasoning with novel SFT+GRPO

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Re: VibeThinker: 3B param model that beats Opus 4.5 on reasoning with novel SFT+GRPO

#91

Post by fjsoxjdnwk »

3eb7988a1663 wrote: post #27
numlock86 wrote: post #26

Earlier quoted context omitted.

This has been my dream ever since. Instead of encoding "all the knowledge" into those parameters, how about just making a model that has the same size, but all (or rather most) it does is reasoning? Just give it the ability to browse the net (e.g. language specifications, documentation and best practices) and just have it do its thing. Why does my coding agent need to know the population of New York, know a cheese ca…

It would also reduce training costs to nothing. Current methodology requires continual retraining to scoop up new facts. If you can do a one time "this is how to think" - that could conceptually work forever, just plug in a new database layer that can be queried as required.

But isn’t that what “training” is anyway? They train LLM today like that and the database becomes the parameters. You can post train on smaller corpus for purpose-built stuff.

Re: VibeThinker: 3B param model that beats Opus 4.5 on reasoning with novel SFT+GRPO

#92

Post by [deleted] »

secretslol wrote: post #23

Am I right in thinking this is a tiny model which has been trained well to reason, and that's it? Makes me think of a smart person who doesn't know anything about a given topic, but with the right tools will go and research the heck out of it. I really like the sound of this... why have models train on learning anything when you can just train them how to learn and let them get on with it from something as small as a…

[deleted]

Re: VibeThinker: 3B param model that beats Opus 4.5 on reasoning with novel SFT+GRPO

#93

Post by le-mark »

nsingh2 wrote: post #39
nsingh2 wrote: post #25

Earlier quoted context omitted.

Lots of confusion about what this model is actually focused on. It is a cheap specialist for closed-world, verifiable reasoning tasks like math, self-contained coding problems, and similar. "Closed-world" means the needed information is already in the context. It is not a tool-using agent that can discover missing context. "Verifiable" means answers are hard to generate but easy to check. So no open ended research, r…

To follow up on this, I had it solve a nasty ODE problem that I saw in the recent Mathematica 15 release post: Solve the following first-order ODE for f(x): ((-1 - 2*x)*f(x)*tan(1 + x - exp(-61 - 2*x)*f(x)/x) + exp(61 + 2*x)*x*(1 - x*tan(1 + x - exp(-61 - 2*x)*f(x)/x)) + x*tan(1 + x - exp(-61 - 2*x)*f(x)/x)*f'(x)) = 0 Find the general solution f(x). And surprisingly it found a valid solution! Extra impressive because…

How do you know it’s a valid solution? Are you able to verify it yourself?

Re: VibeThinker: 3B param model that beats Opus 4.5 on reasoning with novel SFT+GRPO

#94

Post by le-mark »

pants2 wrote: post #35
NotSuspicious wrote: post #29

The interesting thing about models this small is they should be able to be put on a single Taalas chip (the HC1 already runs a Llama 3.1 8B model). We're already at the point where half-decent reasoning could be run on an ASIC (and at mind-boggling speeds).

Yeah, if they can fit an 8B model that's really good at improving the output by thinking, running at 16K tok/s on Taalas would be mind-blowing.

Given this and the quality of open models, it makes no sense to me that there’s a future for Anthropic et all?

Re: VibeThinker: 3B param model that beats Opus 4.5 on reasoning with novel SFT+GRPO

#95

Post by soulofmischief »

secretslol wrote: post #23

Am I right in thinking this is a tiny model which has been trained well to reason, and that's it? Makes me think of a smart person who doesn't know anything about a given topic, but with the right tools will go and research the heck out of it. I really like the sound of this... why have models train on learning anything when you can just train them how to learn and let them get on with it from something as small as a…

Choosing between a model that can only "reason" and a model that has extensive knowledge and "reasoning", the latter will be undeniably better. Advanced reasoning requires cross-domain knowledge, superb pattern recognition, which can only be gained through the same mechanisms which give you a knowledgeable model.

Except for the most basic of tasks, such as "turn on my lights" or "cross-reference these two lists", I wouldn't trust a small model to be as conscientious and reliable as one with deep knowledge.

Re: VibeThinker: 3B param model that beats Opus 4.5 on reasoning with novel SFT+GRPO

#96

Post by swiftcoder »

avereveard wrote: post #69
swiftcoder wrote: post #58

Earlier quoted context omitted.

I don't see what reading has to do with knowing not to reverse on a highway. It's not like they put up big glowing signs that say "wrong way" like in a video game.

There literally are "no u turn" signage where you are supposed not to do that. They literally put up signs for it. It is not glowing in the sky, and it doesnt need to be, and doesnt help making a point strawmanning it.

> There literally are "no u turn" signage where you are supposed not to do that

These signs, you mean? https://en.wikipedia.org/wiki/Prohibitory_traffic_sign#No_U-...

Re: VibeThinker: 3B param model that beats Opus 4.5 on reasoning with novel SFT+GRPO

#97

Post by rbbydotdev »

Looks like we are seeing small but mighty model breakthroughs, outpacing the pure capital firepower of SOTA providers. I love rooting for the little guy, but is it too soon to call it? To play devils advocate, could it just be the benchmarks are not efficient enough to capture success of real developer workflows?

Re: VibeThinker: 3B param model that beats Opus 4.5 on reasoning with novel SFT+GRPO

#98

Post by mejutoco »

Lerc wrote: post #44
secretslol wrote: post #23

Am I right in thinking this is a tiny model which has been trained well to reason, and that's it? Makes me think of a smart person who doesn't know anything about a given topic, but with the right tools will go and research the heck out of it. I really like the sound of this... why have models train on learning anything when you can just train them how to learn and let them get on with it from something as small as a…

I think you could probably train a model to consider boolean logic, modal logic, and mathematics reasonably well, but there is still a pretty big leap between that and thinking about things. Even the most basic questions such as put a ball in a cup and place it on a table upside down then pick up the cup and put it in a box. Requires knowledge of things not mentioned in the question (notably gravity). Strict definiti…

> Even the most basic questions such as put a ball in a cup and place it on a table upside down then pick up the cup and put it in a box.

I do not think this is a great example. First, it is not a question. Second, it seems very related to robotics. A model itself cannot put a ball anywhere, it can just call tools and answer in text, image, etc.

An LLM seeing "put a x in a y and place it on a z upside down then pick up the y and put it in a z2." and then a question about what happens could check a rag for properties of those x,y,z,z2 and still answer. Alternatively, this could be useful for coding, for example. And that is a very extreme example. Some basic language plus tool use could go quite far. I think it is a very interesting direction vs here is a gpu the price of a car.

Re: VibeThinker: 3B param model that beats Opus 4.5 on reasoning with novel SFT+GRPO

#99

Post by uberex »

hypfer wrote: post #36
noperator wrote: post #8

Having some success while testing this model out as a replacement for GPT-5 nano in source code security review. Running on RTX 3090 (24 GB VRAM) via vLLM. It's not great on structured output (as noted in the model card) but I'm working around that in my harness.

> but I'm working around that in my harness. How?

Maybe limiting logits to what is syntactically correct? E.g. {"hello" has to be followed by whitespace or colon. Any other logits get dropped.
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