3 ms·
What about 15k tokens per second? [0] I remember looking at this earlier in the year and it being so fast that it feels fake. And, yes, this model is old - bu
by windexh8er 4mo ago
What about 15k tokens per second? [0] I remember looking at this earlier in the year and it being so fast that it feels fake. And, yes, this model is old - but still awesome for what it is.
[0] https://chatjimmy.ai/ https://chatjimmy.ai/
- Kirby64 4mo agoIt’s not just old, it’s also tiny and quantized. It’s llama 3.1 8b at 3/6-bit quant. This is the type of thing you can run on almost any device…
- windexh8er 4mo agoI get that, but not at 15k tokens/s.
- Kirby64 4mo agoBut it’s irrelevant. 750 tokens/s on a full frontier model is useful. 15000 poor quality tokens is much less useful no matter how much scaffolding you put around it.
- windexh8er 4mo agoI think you missed the point and don't understand / aren't considerate of SLM utility.
- Kirby64 4mo agoBut I’m not missing the point. If you can run one frontier model at 750t/s, then you can probably run many many instances of an SLM in parallel at a rate that exceeds 15k/s. That’s kinda the point of the flash or ultrafast variants. And they’re on something much more modern than llama3.1.
- windexh8er 4mo agoYes, you are missing the point. 1) It's a demo. [0] 2) It hasn't been updated for 4+ months. You don't need LLMs for everything. That is 100% the point. You can burn down the world with all of your frontier LLMs that are being used for simple queries OR we can do something faster and more efficient like this. Just because you can run a SotA model at "fast" speeds, again, severely misses the point. And no, you can't run anything from Anthropic or OAI on-prem, so until you can there's really no comparison. If people want to continue down the path of gate-kept models with no other options then we'll all follow you off the cliff. [0] https://taalas.com/products/ https://taalas.com/products/
- Kirby64 4mo agoWhy are you representing this as such a binary here? For SLM we don’t need the Taalas stuff at all. Just run it locally on your own device if it’s truly a small model. And there’s plenty of larger models that can be run on-premise just fine. I think it’s impressive that a frontier model can achieve 750t/s. That’s all. You can get similar insane token speeds from other open weight models too.
- windexh8er 4mo agoThe irony here is, according to you, my take is the binary one. When your response is: well, we can all just run it on our devices - we don't need any other options! You seem to be cool with a very small and gated ecosystem with whatever tech billionaires want you to have access to. I grew up in the era where compute was diverse and open. You may think this is OK, but it's not. The more options we have and the more diversified they are the better tech will move back towards. I'm not the one with the myopic view here. Enjoy your "on-device" models over in your utopia of a walled garden.
- Kirby64 4mo agoI think you’ve got things quite backwards if you think that the desire to run models on device or use any of the variety of open weight models (big or small) on premise is somehow bowing down to tech billionaires. Quite the opposite really. Once again, my statement is that the Taalas product is not a fair comparison because it runs an old outdated model. If you want to run a similar model at similar speeds (albeit not serially, but in parallel) you don’t need their product.
- Legend2440 4mo agoYou are missing the point. This is a technology demonstration on prototype hardware, and no one intends it to be seriously useful. Their architecture has fundamental speed and efficiency advantages over GPUs or Cerebras. They expect to scale up to real LLMs by splitting a model layer-wise across several chips, which they can do without incurring any throughput penalty.
- Kirby64 4mo ago> They expect to scale up to real LLMs by splitting a model layer-wise across several chips, which they can do without incurring any throughput penalty. I’ll patiently wait to see this in reality. Their demonstration hardware is a 250W chip that is enormous in die area for the model size. They’re making a lot of claims, but until they can deliver then it’s nearly vaporware in my view. I’d be happy to be proven wrong, but I think they’re going to quickly run into hardware realities quite soon if they think they can just chain a bunch of chips together to achieve the same performance on larger sizes.
- windexh8er 4mo agoWhy can't they do it? Jim Keller's company is also taking a different approach [0]. The simple fact that we think what we have now is scalable is basically what you are saying can't be done: " just chain a bunch of chips together to achieve the same performance on larger sizes". How do you think current architectures work? And what is being used today is all proprietary to one company! [0] https://tenstorrent.com/solutions/llm-inference https://tenstorrent.com/solutions/llm-inference
- __alexs 4mo agoActually it's the opposite. Per mm of silicon it's massively less efficient and making enough chips and powering them is a major bottleneck right now. Worse, scaling to larger models requires more of our absolute best quality silicon manufacturing, where e.g. an H200 mostly just needs more memory.
- huflungdung 4mo ago[dead]
- trollbridge 4mo agoI’ve been using 1,000 t/s on a near frontier model for a month now. It’s very useful for agentic coding. It does require new approaches for me personally since I get a lot less time to think or read its output.
- Sebb767 4mo agoWhich model and how can you achieve that speed, if you don't mind me asking?
- trollbridge 4mo agoMiMo 2.5 Pro UltraSpeed. Requires a brief application with Xioami and a day or two to get approved.
- partsch 4mo agoThey baked the LLM into a CPU
- calvinmorrison 4mo agoat 15K tokens/s... do you need code anymore
- selcuka 4mo agoYeah, that's the point, right? With tool calling the LLM becomes code. So instead of asking it to write an accounting software, you can hire the LLM to be your accountant.
- recursive 4mo agoBut you'd still need code if you need something done in a consistent way.
- block_dagger 4mo agoNot necessarily. Consider a human assistant who performs repetitive tasks at an acceptable cost and accuracy while dealing with edge cases often autonomously.
- saxenaabhi 4mo agoMaybe acceptable in some cases but the original example in this thread was about accounting and they use software to do the counting not humans. And even id humans/llms do it there would still be a need for systems of record with things like audit log etc.
- rafaelmn 4mo agoIf we want reliability - we come up with processes to make it reliable and not rely on individuals getting it right. Code is a way to create a reliable process in the digital world.
- recursive 4mo agoFor some things that's acceptable or even good. If I want to add up a list of a million numbers human assistants aren't bringing any advantages though.
- ehsankia 4mo agoI just tried it, and the answer is non-sense. I asked it something simple, list some good indie puzzle games, and half the answers are games that don't exist. Imo quality > speed.