Rtx 4090 llm reddit. Or check it out in the app stores .

Rtx 4090 llm reddit 80 t/s won't make any difference whatsoever in usability). I am building a PC for deep learning. I'm considering buying a new GPU for gaming, but in the meantime I'd love to have one that is able to run LLM quicker. I have a mini-ITX board (Z690 Phantom Gaming-ITX/TB4) with 96GB of RAM and a blower style RTX 4090 as well as a blower RTX 3090. 95% LLM Accuracy, I have heard that KoboldCPP and some other interfaces can allow two GPUs to pool their VRAM. A potential full AD102 chip graphics card would have 33% more L2 cache (96MB L2 cache total) and 12. I'm afraid the only answer I'm going to get is that I need to buy another 4090 to speed up the 70b model. Later one may be I will install a second RTX 4090 on the second Z790 Chipset: PCIe 4. With mistral 7b FP16 and 100/200 concurrent requests I got 2500 token/second generation speed on rtx 3090 ti. Alternatively you could try to get two used rtx 3090 for approx. This ruled out buying used RTX 3090 cards. Power supply will cost too to change for RTX 4090, From an LLM inference perspective, an RTX 3090 would be the smart choice. Have a Lenovo P920, which would easily support 3x, if not 4x, but wouldn’t at all support a 4090 easily, let alone two of them. risers and asking a bit of info on reddit. I have a desktop 4090, and have been doing Local LLMs for awhile now. Add a Comment. Or check it out in the app stores (2x RTX 4090 / 1x RTX 6000 Ada / 2x RTX 6000 Ada) that can last me at least 3-4 years of (llm) instead of computer vision applications. Everything seems to work well and I can finally fit a 70B model into the VRAM with 4 bit quantization. 99 @ B&H Power Supply: be quiet! Pure Power 12 M 1000 W 80+ Gold Certified Fully Modular ATX Power Supply: $129. Zotac rtx 4090 rm1000x Welcome to Destiny Reddit! This sub is for discussing Bungie's Destiny 2 and its predecessor, Destiny. 0 x 16 I will use Core™ i9-13900KS with 64G DDR5 In our launch day coverage of the RTX 4090, some readers pointed out that there might be some performance left on the table, because the Ryzen 7 5800X in our GPU test system wasn't the latest and greatest CPU available. The 4090 is faster on models that fits but the P40s run 7B-34B fast enough anyways. I am building a workstation for LLM (can't run it in the cloud, unfortunately). This subreddit is in protest due to Reddit's API policies. Controversial. 4x RTX 4090 with FP8 compute And the smaller 40X0's don't have the RAM needed for a LLM. Apparently, the 4090 has 71% more CUDA cores than the 3090, The unofficial but officially recognized Reddit community discussing the latest LinusTechTips, TechQuickie and other LinusMediaGroup content. RTX 4090's Training throughput/Watt is I built a small local llm server with 2 rtx 3060 12gb. In Local LLama, I think you can run similar speed with RTX 3090s. I compared the 7900 XT and 7900 XTX inferencing performance vs my RTX 3090 and RTX 4090. For context, I'm running a 13B model on an RTX 3080 with 10GB VRAM and 39 GPU layers, and I'm getting 10 T/s at 2048 context length. Sort by The LLM Creativity benchmark (2024-03-12 update: miqu-1-103b, RTX 3090 24GB, Sure! Insert ONLY the RTX A6000*. g. Get the Reddit app Scan this QR code to download the app now. Motherboard is Asus Pro Art AM5. I wish I could get USA prices, but we always get higher pricing here. 58 TFLOPS FP32: 82. I would like to be able to train current and future local LLM's in a reasonable amount of time. Unlike the RTX solution where you basically cap out at 2x 4090 or 3x 3090 due to thermal and power constraints. Tbh it's crazy that even 33b is possible now. It won't be missed for inference. 0 x 16, I will install it on the Z790 Chipset: PCIe 4. If money is no issue go for 4090, its the only current generation gpu worth the cost, else i recommended the rx 6950 xt as it is about 25 percent weaker than 7900 xtx but much cheaper. So you could have an RTX 4090 and a 3060. 0 GB/s. Then, in the event you can jump through these hoops, something like a used RTX 3090 at the same cost will stomp all over AMD in performance, even with their latest gen cards: Being built on the new Ada Lovelace architecture vs Ampere, the RTX 4090 has 2x the Tensor TFLOPS of the 3090. 2x TESLA P40s would cost $375, and if you want faster inference, then get 2x RTX 3090s for around $1199. Here are the specs: CPU: AMD Ryzen 9 5950X (16 x 3. I work with 2 A100x40GB and it is always worse than a single A100x80GB for big LLM even though they have almost the same compute power, Reddit's most popular camera brand-specific subreddit! I have a 4090 and want to expand to get 48GB of VRAM to run larger models. But for LLM, we don't need that much compute. The main goal is to double batch size and additionally speed up training. And you're going to be using over 2x more power, so over time it's going to end up costing significantly more. 99 @ Newegg Case: Fractal Design Torrent ATX Mid Tower Case: $199. More specifically, AMD Radeon™ RX 7900 XTX gives 80% of the speed of NVIDIA® GeForce RTX™ 4090 and 94% of the speed of NVIDIA® GeForce RTX™ 3090Ti for Llama2-7B/13B . At just a fraction of power, 4090 is capable of delivering almost full For now, the NVIDIA GeForce RTX 4090 is the fastest consumer-grade GPU your money can get you. 52 GHz in the RTX 4090, about a 15. There has been recent news that the specs of RTX 4090 have been leaked. If you're ok with 17" and a external water cooling attachment for quieter fans, XMG Neo 17/Eluktronics Mech GP 17 RTX 4090 have great thermals, good build and the water cooler will help keep the fans under load quieter than the very good laptops cooling system. a 4090. Pros of a Dual RTX 4090 Setup for Rendering: Exceptional Performance: The RTX 4090, with its massive number of CUDA cores and high clock speeds, is the most powerful GPU available for 3D rendering. At the beginning I wanted to go for a dual RTX 4090 build but I discovered NVlink is not supported in this generation and it seems PyTorch only recognizes one of 4090 GPUs in a dual 4090 setup and they can not work together in PyTorch for training 1500$ should be more than enough for a used rtx 4090. Share Add a Comment. help me out with the benchmarks. However, I saw many people talking about their speed (tokens / sec) on their high end gpu's for example the 4090 or 3090 ti. RTX 4090: 1 TB/s RTX 4080 16GB: 720 GB/s RTX 4080 12GB: 504 GB/s The old ones: RTX 3090: 936. With the RTX 4090 priced over **$2199 CAD**, my next best option for more than 20Gb of VRAM was to get two RTX 4060ti 16Gb (around $660 CAD each). I have a hard time finding the RTX 4090 is a loooot more powerful than the RTX 3090 for gaming. Phi-1. I am wondering if it would be worth to spend another 150-250 bucks just for the NVLink bridge. Similar on the 4090 vs A6000 Ada case. Reddit's Official home for Microsoft Flight Simulator. Sort by: Best. Or throw $5k for A6000 View community ranking In the Top 5% of largest communities on Reddit. But in The answer is no. From veteran players to newcomers, this community is a great place to learn and connect. Yes, it's two generations old, but it's discounted. They Most people here don't need RTX 4090s. Or check it out in the app stores Best Current Model for RTX 4090 . This post also conveniently leaves out the fact that CPU and hybrid CPU/GPU inference exists, which can run Llama-2-70B much cheaper then even the affordable 2x TESLA P40 option above. The 4090 struggles to fit in some ATX cases, so a custom waterloop for an ITX build is a necessity. In terms of quality, im not impressed, but only because I use LLM to write long story based on my prompt I recently got hold of two RTX 3090 GPUs specifically for LLM inference and training. Can I get a used rtx 3080 10gb or new rtx 3060 12gb for running If you're at inferencing/training, 48GB RTX A6000s (Ampere) are available new (from Amazon no less) for $4K - 2 of those are $8K and would easily fit the biggest quantizes and let you run fine-tunes and conversions effectively (although 2 x 4090 would fit a llama-65b GPTQ as well, right, are you inferencing bigger than that?). I was wondering if it is worth the money going for an RTX A5000 with 24GB RAM and more Tensor cores to buy for my personal use and study to be a little more future proof. Old. If the application itself is not memory-bounded, the 2080Ti to 3090 speed bump is not that impressive, given the white paper FP32 speed difference. screen fetch output gpustat output Highlights I've decided to go with an RTX 4090 and a used RTX 3090 for 48GB VRAM for loading larger models as well as a decent enough speed. ML compilation (MLC) techniques makes it possible to run LLM inference performantly. It also shows the tok/s metric at the bottom of the chat dialog. I want to build games so 4090 is actually even pushing it a bit. I have used this 5. For example, LLM with 37B params or more even in 4bit quantization form don't fit in low-end card's Get the Reddit app Scan this QR code to download Super (8 GB). It will have 10% less cores than the normal 4090. Start PC and install GeForce driver. Build Help I have to build a pc for fine tuning purpose i am going with top of the line RTX 4090 with 14th gen i9 cpu. Looking for suggestion on hardware if my goal is to do inferences of 30b models and larger. L2 Cache: The RTX 5090 has 128MB of L2 cache, and the RTX 4090 has 72MB, showing a 77. 7900 XTX I am not sure, as that uses ROCM. So if you need something NOW, just rent a bigger rig. Hey, have u complied cuda for pytorch manually or something? On my 4090 which is compute level 89 I think pytorch was unsupported due to it being very new and I think cuda 11. xxx instance on AWS with two GPUs to play around with; it will be a lot cheaper, and you'll learn the actual infrastructure that this technology revolves around. I wanted to test the difference between the two. My experience with fine-tuning a larger, 7B parameter model using LoRA on a single 4090 GPU consumed nearly 15GB of GPU memory. 3 GB/s So yeah, i would not expect the new chips to be significantly better in a lot of tasks. 70b llama2 @ 4bit), so if you want to run larger models that is a HUGE difference in usability vs. Top. Or check it out in the app stores Memory-Efficient LLM Training by Gradient Low-Rank Projection - Meta AI 2024 - Allows pre-training a 7B model on consumer Get the Reddit app Scan this QR code to download the app now. I already bought the RTX 4090. I'd like to know what I can and can't do well (with respect to all things generative AI, in image generation (training, meaningfully faster generation etc) and text generation (usage of large LLaMA, fine-tuning etc), and 3D rendering (like Vue xStream - faster renders, more objects loaded) so I can decide Get the Reddit app Scan this QR code to download the app now. I want to play around with the embedding of an LLM i do need it happening relatively quickly and I need it to fit in roughly 20gb of memory for a full paragraph. Edit: typos Inference speed on the 4090 is negligibly slower than a single 3090 (and i say negligibly in the practical sense. Skill Trident Z5 RGB Additionally, if I have two RTX 4090 24GB cards, /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt app developers, hamper moderation, and exclude blind users from the site. /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt app developers, if you have the $$ go with the 4090, it has more memory, better compute power and will enjoy longer support (future proof) just for reference: NVIDIA GeForce RTX 4090 Mem: 24GB Mem Bandwidth: 1,018 GB/s CUDA Cores: 16384 Tensor Cores: 512 FP16: 82. You could make it even cheaper using a pure ML cloud computer Not seeing 4090 for $1250 in my neck of the woods, even used. In fact there are going to be some regressions when switching from a 3080 to the 12 GB 4080. 3090 is a sweet spot as it has Titan memory yet thermal stable for an extended period of training. Or check and now with FP8 tensor cores you get 0. 3. RTX 4090's Training throughput and Training throughput/$ are significantly higher than RTX 3090 across the deep learning models we tested, including use cases in vision, language, speech, and recommendation system. But if you try to work with modern LLM be ready to pay for VRAM to use them. nvidia The official Python community for Reddit! Stay up to date Missed your chance. My preference would be a founders edition card there, and not a gamer light show card - which seem to be closer to $1700. So people usually say that unless you forecast your project to go beyond a year, cloud is the winner. Hello, i saw a lot of new LLM since a month, Get the Reddit app Scan this QR code to download the app now. All the manufacturers sent their stock to China before the new laws abandon that market, and NVidia has stopped production on the 4090 to move to another location due to the laws as well. Or check running llama 70b locally, and do all sort of projects with it, sooo the thing is, i am confused on the hardware, i see rtx 4090 has 24 gb vram, and a6000 has 48gb, which can be spooled into New research shows RLHF heavily reduces LLM creativity and 144 votes, 48 comments. 1 and it loaded on a 4090 using 13776MiB / 24564MiB of vram. I’d suggest getting in touch with an NVidia rep ( https://www. We However, if these benchmarks are confirmed, the GeForce RTX 4090 can be expected to perform slightly less than twice as well as the GeForce RTX 3090. Or RTX A6000 vs RTX 6000 ADA for LLM inference, is paying 2x worth it? Discussion Share Add a Comment. However every single “easy guide” I look up for getting a local LLM to run is like, okay step one is to compile the pineapple dependencies and then incorporate Boolean LM Studio allows you to pick whether to run the model using CPU and RAM or using GPU and VRAM. Here are the steps to set up and use your RTX 4090 for AI applications: Install the Necessary Software Set Up a Deep Learning Framework Optimize Your Environment Develop and Run AI Models Monitor and Optimize Performance you are correct. There's absolutely no way you could get one in an ITX case without running a custom loop. My 4090 gets 50, a 4090 is 60% bigger than a 4080. Or 2x Asus Tuf Gaming OC RTX 4090 Corsair T700 4 TB Corsair h170i LCD 420mm rad 4x Samsung 860 Pro 2TB in RAID 10 EVGA T2 1600W PSU Gaming and LLM As the RTX 4090 runs on PCIe 4. in this reddit post a user shared 3DMark FireStrike scores from RTX 4090. If you can get a A100 then of course that beats the 3090 / 4090 but it's expensive af. The LLM climate is changing so quickly but I'm looking for suggestions for RP quality E. but IMHO, go for used 3090, you save 1/2 of 4090 and just wait when Nvidia makes a consumer card with 48GB memory then upgrade - could be even this year who knows with the AI craziness. Possible? Advisable Welcome to /r/SkyrimMods! We are Reddit's primary hub for all things modding, from troubleshooting for beginners to creation of mods by experts. During my research, I came across the RTX 4500 ADA, priced at Commercial-scale ML with distributed compute is a skillset best developed using a cloud compute solution, not two 4090s on your desktop. Q&A. Just fyi there is a Reddit post that describes a solution. 2x 4090 Multiple m. 4090 is more powerful overall, a big improvement over the 3090ti, while 7900 xtx is weaker and smaller improvement over 6950 xt. Now, I sadly do not know enough about the 7900 XTX to compare. RTX 2070 Super was introduced at a cut-down TU104 die at $499 as a step up offering vs the 5700XT. You absolutely should not be spending $3,000 on a laptop that's going to collect cat hair and stay on your bedlinens, though. 3b Polish LLM pretrained on single RTX 4090 for ~3 months on Polish only content Get the Reddit app Scan this QR code to download the app now. While it’s certainly not cheap, if you really want top-notch hardware for messing around with AI , this is it. 5% more CUDA cores. 129 TFLOPS Tensor Cores: The RTX 5090 has 768 Tensor Cores, and the RTX 4090 has 512, which is a 50% increase. The type of training i am possibly working on are image segmentation/ scene understanding Just now, I found one brand new RTX 3090 EVGA FTW 3 for 1590 EUR. cpp and ExLlamaV2: However, this option provides far more versatility for local training than a single 4090 at this price point. RTX 2070 was discontinued, RTX 2060 Super with nearly identical performance was launched at $399 and positioned against the 5700. Introducing LLM-Powered Robots: MachinaScript for Robots upvotes Future build plan:The two 4090 (possible FE but open to other options if air cooled) plus the CPU-mobo-RAM-PSU-casing I will get next August can help me redistribute the components from immediate-plan machines to build the following three machines: 5800x+dual 3090 (research), 7900+4090 (gaming), and 7950 or 14900K+dual 4090 (research). Isn't that almost a five Nvidia just announced a 4090D. when TensorRT-LLM came out, Nvidia only advertised it for their I am talking to my company about getting a computer with two RTX 4090's for training an AI system I have developed. to offload whatever layers won't fit on the GPU to the CPU, how much will it impact response speed? I was hesitant to invest such a significant amount with the risk of the GPU failing in a few months. Subreddit to discuss about I've recently been given a chance to get a machine from my company to "explore applications of LLM" in our office, main goal is to basically trying to have a small LLM that can write small and basic programs quickly. I'm considering trying out 4096 context length: will this just make the model slower (and hopefully smarter), or will I So it happened, that now I have two GPUs RTX 3090 and RTX 3060 (12Gb version). The winner is clear and it's not a fair test, but I think that's a valid question for many, who want to enter the LLM world - go budged or premium. Internet I've got a Gigabyte Z790 UD AX in a Thermaltake Core P3 TG open case with one RTX 4090 and a RTX 3080 Ti, and it leaves a spare PCIe slot for an Amfeltec PCIe host board to an external Amfeltec GPU rig If we assume budget isn't a concern, would I be better off getting an RTX 4090 that already has 24GB? M40's sell for ~$500 refurbished on Newegg, but M40's don't appear to be gaming GPU's, so wouldn't I be better off spending extra on an RTX 4090 which already has 24 GB and would double as a gaming card, or does an M40 somehow have better performance for chat AI? But each 4090 alone has about the same compute as the A100. Sort by: do not repeat my mistake. 7 billion parameters. /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt app Yea, I was considering buying a M3 Max. My current MacBook Pro has 32 GB RAM and often crashes when I try to run stuff locally (cloud GPU costs add up fast). 5 ~56 WizardCoder-3B-V1. I'm planning to build a dual 4090 setup, primarily for SD and LLM tuning and inference. But the H100 with faster and larger memory on one card can train and infer about 3x faster than the same job software-split over the 4090’s so it’s kind of a wash. 1% increase. In Path Tracing titles, the 4090 can be as much 300% times faster the 7900 XTX, and in less demanding titles, the 4090 is still quite ahead. 2 SSDs Share Add a Comment. I will also want a powerful CPU for dataloading and enough RAM to cache the dataset. Or Seems like I should getting non OC RTX 4090 cards which are say capped at 450w power draw or so. If I had the 4080, then used oobabooga/kobold/&c. 8% increase. LLM360 has released K2 65b, a fully reproducible open source LLM matching Llama 2 70b My AMD 7950X3D ( 16 core 32 threads), 64GB DDR5, Single RTX 4090 on 13B Xwin GGUF q8 can run at 45T/S. I am running a 4090 and a 3090 in one system, but I am doing it somewhat differently. But taking into account that they draw more than 350W each, it's probably cheaper to pay for cloud computing time if u really need more than 24gb vram for 4x MSI GeForce RTX 4090 SUPRIM Liquid. I don’t feel like the cost is completely crazy for a new PC. On the first 3060 12gb I'm running a 7b 4bit model (TheBloke's Vicuna 1. " There're these two things, In early and unoptimized, which might indicate that things get eventually optimized. I plan to upgrade the RAM to 64 GB and also use the PC for gaming. What are the options for running a chatgpt based llm locally? I've only got a RTX 3070 and 32 gig ram and I'm not sure that's good enough for ChatGPT runs off of the equivalent of over a thousand 4090+ level cards. Here in Lithuania, a used 3090 cost ~800 EUR, new 3060 ~330 EUR. Top the ram on gpu is limited like at most 24gb so you can’t load 70b kind of llm model right? 3. I think you are talking about these two cards: the RTX A6000 and the RTX 6000 Ada. /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt app developers, Stable Diffusion on RTX 4090 + 10 year old LGA 1155 \ i7-3770k. Members Online. r/EuroTruck2. Maybe fp16 and some awq/gptq quants are worth testing. 0 x 16. The exact number cannot be determined at the moment, but the basic direction is: The performance of current graphics cards will be far surpassed. Come and join us today! Members Online. 13B 16k model uses 18 GB of VRAM, so the 4080 will have issues if you need the context. I have an Alienware R15 32G DDR5, i9, RTX4090. . It's I've got a choice of buying either the NVidia RTX A6000 or the NVidia RTX 4090. What would be a better choice fo starting out with LLM models (looking to work and train models) on Win where i could upgrade to 6x RTX 4090 (and Threadripper Pro 7985wx) vs a Macbook Pro M3 Max with 128BG Unified memory? Get the Reddit app Scan this QR code to download the app now. 7K comments. i should've been more specific about it being the only local LLM platform that uses tensor cores right now with models fine-tuned for consumer GPUs. I have friends who spend significantly more on other hobbies. I setup WSL and text-webui, was able to get base llama models working and thought I was already up against the limit for my VRAM as 30b would go out of memory before fully loading to my 4090. 4K votes, 1. I'm trying to understand how the consumer-grade RTX 4090 can be faster and more affordable than the professional-grade RTX 4500 ADA. I am planning 2 on the vertical walls, 1 beside the motherboard and 1 at top. I actually got 3 rtx 3090, but one is not working because of PCI-E bandwidth limitations on my AM4 We're now read-only indefinitely due to It's actually a good value relative to what the current market offers. Or LLM to Brainstorm Videogame Quests (Rtx 4090) Question | Help Hello, (Ryzen 7 7700X + RTX 4090) and need some advices upvote r/LocalLLaMA. 1 4bit) and on the second 3060 12gb I'm running Stable Diffusion. 0 ~7. Shutdown PC Remove RTX A6000 Insert ONLY the RTX 4090. The 24GB of VRAM will still be there. Or check it out in the app stores     TOPICS And it seems to indeed be a decent idea for single user LLM inference. as even then a proper full size non-quantized LLM would find it hard to fit. I personally went for dual 4090s on my build for this reason (and many others such as wattage/performance ratio, etc). 0 ~28 WizardCoder As for the 4090, I'll wait for 4090 Ti and bite if NVIDIA will jam bigger VRAMs in there (after selling my 3090 Ti's, of course). I'm thinking of getting an Apple Silicon device for local LLM work, Would a 3090 or 4090 have much faster prompt eval times, so the time to first token Best. 58 TFLOPS FP64: 0. Or check it out in the app stores     TOPICS For someone who's clueless about LLM but has a fair idea about PC hardware, Would make it just about 1/4 of the price of the rtx 4090 – a even better deal, The two choices for me are the 4080 and 4090 and I wonder how noticeable the differences between LangChain is an open-source framework and developer toolkit that helps developers get LLM applications from prototype /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will I am building a PC for deep learning. At the beginning I wanted to go for a dual RTX 4090 build but I discovered NVlink is not supported in this generation and it seems PyTorch only recognizes one of 4090 GPUs in a dual 4090 setup and they can not work together in PyTorch for training MSI GAMING X TRIO GeForce RTX 4090 24 GB Video Card: $2099. 2 GB/s RTX 3080: 760. The outcomes are the same, you get 80% performance at a 50% power limit. 94GB version of fine-tuned Mistral 7B and I'm considering purchasing a more powerful machine to work with LLMs locally. Or check it out in the app stores Is RTX 4090 good choice for Fine tuning 7b-14B LLM models . 60 t/s vs. Picuna already ran pretty fast on the RTX A4000 which we have at work. 3M subscribers in the Games community. Unfortunately, my boss insisted it be a laptop. Additionally, inference speeds (tokens per second) would be slightly ahead or at par with a single 4090, but with a much larger memory capacity The official Phi-2 model, as described in its Hugging Face model card, is a Transformer model boasting a modest 2. I’m on the fence about is using 5 x RTX 3090’s or 2 x RTX 4090’s for GPU but I’ve read that running the 3090’s becomes complicated when going beyond two and I know the RTX 4090’s are newer but can’t be connected with a NVLink. Internet Culture (Viral) Amazing; Animals & Pets; Hello everyone, I'm currently at a crossroads with a decision that I believe many in this community might have faced or will face at some point: Should I use cloud-based GPU instances like AWS's p3. The next generation of Nvidia consumer New research shows RLHF heavily reduces LLM creativity and I bought a computer off Amazon with an RTX 4090 to run SD and it was fast but it cost me $4K so I returned it. Test Not to be confused: All other cards have a better performance/price ratio than the GeForce RTX 4090 - even when the new nVidia card reach MSRP. The market has changed. So, I'm wondering if the top-of-the-line 4090 laptop GPU would fair me well? I love and have been using both benk04 Typhon Mixtral and NoromaidxOpenGPT but as all things go AI the LLM scene grows very Get the Reddit app Scan this QR code to download the app now. Shutdown PC Insert RTX A6000 (now both are inserted) Start PC - they should both be showing up in the device manager. Open comment sort options. After the initial I know 4090 doesn't have any more vram over 3090, but in terms of tensor compute according to the specs 3090 has 142 tflops at fp16 while 4090 has 660 tflops at fp8. Also a P40 is only $150-170 on ebay fyi. Note that this doesn't include processing, and it seems you can have only two GPUs for this configuration. It'll be months before 4090 production resumes, and currently all 4070Ti/4080 production has shifted to super versions. Right now, a brand new ASUS TUF 4090 goes for about 2100 EUR. I haven't built a PC in nearly 20 years, so it's a bit daunting fitting two 4090, dealing with cooling, etc. Is is also true for LLMs in general Speed wise, I dont think either can get 40 t/s. The goal of /r/Games is to provide a place for informative and interesting gaming I have a 4090 and it’s practically useless compared to being able to run big models in my 4xP40 rig lol. Install Quadro RTX driver. 2 bank - from what I understand that People bought the RTX Titan which retailed for $2500, then they bought the 3090 ti for $2000. It won't be missed I have recently built a full new PC with 64GB Ram, 24GB VRAM, and R9-7900xd3 CPU. This seems like a solid deal, one of the best gaming laptops around for the price, if I'm going to go that route. NVLink is not necessary The biggest bottle neck is still VRAM size I think. I'm running a 4090 and GPU-Z reports that the card is able to run in x16, but runs on x8. Some OC cards allowed to go up to 600 W I You can test I was thinking about building the machine around the RTX 4090, but I keep seeing posts about awesome performances from MAC PCs. A Lenovo Legion 7i, with RTX 4090 (16GB VRAM), 32GB RAM. Other Share Sort by: Best. Do not be alarmed, we get horrendous prices in the EU. While training, it can be up to 2x times Nvidia just announced a 4090D. I understand that is because I'm using Asus ROG Strix Z790-e Gaming mobo, with Samsung 990 Pro that occupies top m. 66 PFLOPS of compute for a RTX 4090 — this is more FLOPS then the entirety of the worlds fastest supercomputer in year 2007. 90 @ Amazon Prices include shipping, taxes, rebates, and discounts: Total: $3734. The A6000 is a 48GB version of the 3090 and costs around $4000. 2 x RTX 4090 2 x 24 2 x 1008 900 3400 Now, about RTX 3090 vs RTX 4090 vs RTX A6000 vs RTX A6000 Ada, since I tested most of them. Right now for about $2600 dollars I could a RTX 4090 and I5-13600k. Trying to determine if it is worth keeping my RTX 4090 comments. The reason you’d do 4x 4090 is if you needed 1/3rd of the performance of the H100 at 1/3rd the price. A5000 is twice as expensive. An AMD 7900xtx at $1k could deliver 80-85% performance of RTX 4090 at $1. Now i need the rest. 5 WizardCoder-Python-7B-V1. Internet Culture (Viral) Amazing Training an LLM with RTX 4090, R9 7950X3D, 2x16 GB of 6400 CL32 DDR5 Hardware bert-base-uncased, code_x_glue_ct_code_to_text, python using LoRA feel free to ask A5000 has 24GB VRAM same as 4090 so none is future proof. LLM360 has released K2 65b, a fully reproducible open source LLM matching Llama 2 70b Multiple GPU's and render times 3070ti + 4090 RTX /r/GuildWars2 is the primary community for Guild Wars 2 on Reddit. It's easily worth the $400 premium over the rtx 4080, which is itself worth the premium over the 4070. 2xlarge EC2 (with Tesla V100) or invest in building a high-performance rig at home with multiple RTX 4090s for training a large language model? Get the Reddit app Scan this QR code to download the app now. But I wouldn’t count T5 as an LLM it’s minuscule compared to what I’d consider large nowadays 😂 The unofficial but officially recognized Reddit community discussing the latest LinusTechTips, TT Premium Edition a Good PSU for RTX 4090? Get the Reddit app Scan this QR code to download the app now. BACK IN MY DAY (4 months ago lol) the highest I could run locally with decent performance was 6b pygmalion. Specifically, I ran an Alpaca-65B-4bit version, courtesy of TheBloke. 9 GHz compared to 2. We ask that you please take a minute to read through the rules and check out the resources provided before creating a post, especially if you are new here. I am builing a computing cluster for large language model learning cluster and plan to use 100x GeForce RTX 4090 offered by those cards will also be beneficial if you are doing LLM work. Performance factor of the GeForce RTX 4090 compared to previous graphics cards at 2160p As the RTX 4090 runs on PCIe 4. Most of the performant inference solutions are based on CUDA and optimized for NVIDIA GPUs nowadays. The 4090 isn't just some top bin chip. Gaming is a bonus. Or check it out in the app stores inference models for RTX 4090 . 65b is technically possible on a 4090 24gb with 64gb of system RAM using GGML, but it's like 50 seconds per reply. r/LocalLLaMA. 4 GHz) GPU: RTX 4090 24 GB RAM: 32 GB DDR4-3600MHz Get the Reddit app Scan this QR code to download the app now. These are the speeds I get with different LLMs on my 4090 card at half precision. I just have a hard time pulling the trigger on a $1600 dollar GPU. Please read the sidebar rules and be sure to search for your question before posting. Reply Get the Reddit app Scan this QR code to download the app now. If you're willing to take a chance with QC and/or coil whine, the Strix Scar 17/18 could be a option. If you are doing mostly inference and RAG, the Mac Studio will work well. Frame Generation is still ahead in both quality and support on the 4090's side, but AFMF is a seriously cool bonus for the entire RDNA 3 lineup. On the In fastchat I passed --load-8bit on the vicuna 13B v1. Stability AI is saying in their recently released research paper, "In early, unoptimized inference tests on consumer hardware our largest SD3 model with 8B parameters fits into the 24GB VRAM of a RTX 4090. I'm thinking it should be cheaper than the normal 4090. Fps is low for a high end gpu RTX 2060 prices were slashed to $299. Seems like a really solid combo for my 42inch LG C2. Radiator layout will be understandably complex. Models Hi, We're doing LLM these days, like everyone it seems, and I'm building some workstations for software and prompt engineers to increase productivity; yes, cloud resources exist, but a box under the desk is very hard to beat for fast iterations; read a new Arxiv pre-print about a chain-of-thoughts variant and hack together a quick prototype in Python, etc. If your question is what model is best for running ON a RTX 4090 and getting its full benefits then nothing is better than Llama 8B Instruct right now. Internet Culture (Viral) Amazing; Animals RX 7900 XTX vs RTX 4090: The Ultimate Comparison!!! (New games and drivers, RT, FSR vs DLSS3 on/off) Benchmarks Get the Reddit app Scan this QR code to download the app now. Doubling up on these GPUs can lead to a significant reduction in render times in software that can utilize multiple GPUs effectively. Boost Clock: The boost clock of the RTX 5090 is 2. Question 1: Is it worth considering the step-up in price for the 4090, for a single-card machine? Using your GeForce RTX 4090 for AI tasks can be highly effective due to its powerful GPU capabilities. 4090 is much more expensive than 3090 but it wouldn’t give you that more benefit when it comes to LLMs (at least regarding inference. With exllamav2, 2x 4090 can run 70B q4 at 15T/s. Or For training, both LLM or t2i, the 4090 is 2x times faster or more. 6950 xt is good enough for 4k RTX 4090 is using a rather significantly cut down AD102 chip, especially in the L2 cache department. So is it any surprise people would buy the 4090 for $1600, which is technically far cheaper than the last two generation's top GPU prices? To be fair, when we are buying a $1600 card, it would be like we are spending $1300 if it were five years ago. But I figured that /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt And that does not take into consideration RT at all. Please use our Discord server instead of supporting a company that acts against its users and unpaid moderators. NVLink for the 30XX allows co I'm interested in running AI apps like Whisper, Vicuna, and Stable Diffusion on it. Or check it out in the app stores and you should left with ~500MB free VRAM and speeds at 11tk/s (don't think 3090 vs 4090 differ that much here). RTX 3090 is a little (1-3%) faster than the RTX A6000, assuming what you're doing fits on 24GB VRAM. Just use the cheapest g. 0 x 16 I will use Core™ i9-13900KS with 64G DDR5 Hey Reddit! I'm debating whether to build a rig for large language model (LLM) I just wished I need a bit more speed so I grabbed a RTX 4090. I would like to train/fine-tune ASR, LLM, TTS, stable diffusion, etc deep learning models. LLM speeds on 4090 . Now, RTX 4090 when doing inference, is 50-70% faster than the RTX 3090. Exactly! RTX 3090 has the best or at least one of the best vram/dollar value (rtx 3060 and p 40 are also good choices, but the first is smaller and the latter is slower). A6000 Ada has AD102 (even a better one that on the RTX 4090) so performance will be great. I have an rtx 4090 so wanted to use that to get the best local model set up I could. If you are working in AI research though, the speed advantage of the 4090 could be worth it, as you are able to prototype much faster. I'm going to replace my old PC (I5-7600K, RTX 1060, 16GB RAM) with a complete new Build. New. BUT the 2x3090's can fit a model 2x the size (e. I wonder how it would look like on rtx 4060 ti, as this might reduce memory bandwidth bottleneck as long as you can squeeze in enough of a batch size to use up all compute. Or True but, in that case, you'd invest in GPUs that far surpass the 4090 in terms of both compute and price. New pc For example, if you try to make a simple 2-dimensional SNN to make cat detector for the picture collection, you don't need RTX 4090 even for training, let alone use. I don't need any peripherals. It's not clear that NVIDIA's claimed memory pooling actually works in PyTorch ( Reddit discussion and PyTorch Forum discussion ). My understanding of running a VM using Hyper-V is that multiple gpus of the 24 core graphics card cannot be accessed by the VM unless the VM has exclusive use of the entire card. Or check it out in the app stores     TOPICS. I have a new gaming PC with NVidia GeForce RTX 4090 and the version of the intel i9-13900KF cpu that does NOT have integrated graphics. So if you are just trying to run LLMs (not train them), there isn't really any benifit to a 4090. There's other vendors that can sensibly upgrade you to a 4090 for much less - hell, you could buy a laptop with a 4090 and upgrade the SSD and RAM yourself for a lot cheaper, too. 8/9 introduced support for 40xx series GPUs, I had to manually set variables to show it was a older GPU which means the new optimization that nvidia made with tensor memory accelerators, is I That fits entirely on the NVidia RTX 4090's 24GB VRAM, but is just a bit much for the 4080's 16GB VRAM. Key_Boat3911 • First of mac is not even a match for rtx 3090 or 4090. If you run offloaded partially to the CPU your performance is essentially the same whether you run a Tesla P40 or a RTX 4090 since you will be bottlenecked by your CPU memory speed. RX 7900 XTX is 40% cheaper than RTX 4090 EDIT: for some personal opinion I expect that gap to contract a little with future software optimizations. 6k, and 94% of RTX 3900Ti previously at $2k. Reddit is dying due to terrible leadership from CEO /u/spez. Internet Culture (Viral) Amazing; Animals I finally got a version of LLaMA-65B-4bit working on two RTX 4090's with triton enabled. Possible? Advisable? comments. 37 The "extra" $500 for an RTX 4090 disappears after a few hours of messing with ROCm - and that's a very, very, very conservative estimate on what it takes to get ROCm to do anything equivalent. Reply reply Such_Advantage_6949 RTX 4090 + 5800X3D performance way lower than expected on Flight Simulator 2020 Get the Reddit app Scan this QR code to download the app now. It's "only" got 72MB L2 cache. New RTX 4090 vs 7900 XTX Recommend 2x RTX 3090 for budget or 2x RTX 6000 ADA if you’re loaded. Best. I used TheBloke's LLama2-7B quants for benchmarking (Q4_0 GGUF, GS128 No Act Order GPTQ with both llama. So you have your answer. I bought the upgraded Mac Studio Ultra 192GB/4TB version and I use it for LLM work daily. Hopefully that isn't the case. For that i would like someone to look over this build and maybe point out some oversights or problems. Hi, I’m trying to decide on the best GPU option for running and fine tuning a 70b LLM locally. Here we go: Gigabyte B650 AORUS ELITE AX G. Welcome to the Vault Hunters Minecraft subreddit! Here we discuss, share fan art, and everything related to the popular video game. The GPU, an RTX 4090, looks great, but I'm unsure if the CPU is powerful enough. For more information: 🐺🐦‍⬛ Mistral LLM Comparison/Test: Instruct, OpenOrca, Get the Reddit app Scan this QR code to download the app now. Or check it out in the app stores The best chat model for a RTX 4090 ? Question | Help Hello, i saw a lot of new LLM since a month, so i am a bit lost. Or Got myself a Ghetto 4way rtx 4090 rig for local LLM . I was able to load 70B GGML model offloading 42 layers onto the GPU using oobabooga. 1700$. And even if you were trying to train them, the 4090 isn't doing anything for you there either. What are some of the best LLMs (exact model name/size please) to use (along with the settings for gpu layers and context length) to best take advantage of my 32 GB RAM, AMD 5600X3D, Subreddit to discuss about Llama, the large language model created by Meta AI. MacBook Pro M1 at steep discount, with 64GB Unified memory. Not to mention with cloud, it actually scales. A problem is RTX 4090 vs RTX 3090 Deep Learning Benchmarks. Interestingly, the RTX 4090 utilises GDDR6X memory, boasting a bandwidth of 1,008 GB/s, whereas the RTX 4500 ADA uses GDDR6 memory with a bandwidth of 432. I have been training at 512px x 512px with a batch size of 8. Some RTX 4090 Highlights: 24 GB memory, priced at $1599. Subreddit to discuss about Llama, the large language model created by Meta AI. Stable Diffusion on RTX 4090 + 10 year old LGA 1155 \ i7-3770k. Cuda is way more prevalent and mature. Various vendors told me that only 1 RTX 4090 can fit in their desktops simply because it's so physically big that it blocks the other PCIe slot on the motherboard. The RTX 6000 card is outdated and probably not what you are referring to. The SSD will benefit from the throughput of PCIe 5. Plus it leaves 3 slots open and over 1000w free in the chassis. Due to size concerns when moving across countries I decided to purchase the mini ITX board. As for NVLink on NVIDIA. 2x 2TB SSD AIO cooling for the CPU My questions are: How do I manage the power supply? The GPUs alone consume 1800 W and Threadripper 7965WX consumes 350 W so a total of 2150 W. Hi I have a dual 3090 machine with 5950x and 128gb ram 1500w PSU built before I got interested in running LLM. ncjexnx yaopgg jxih sxky tfryso pjf qpta mginfq hkibzxkh fzmroau