4080 llama 2 reddit gguf with 4080 + Cpu . Q4_K_M. You could make it even cheaper using a pure ML cloud computer Currently I have 8x3090 but I use some for training and only 4-6 for serving LLMs. I am currently running the base llama 2 70B at 0. Q4_0. I understand that the 4090 is potentially 2-3 times faster based on benchmarks, but does this actually translate to improved Llama speeds? Would it even be viable to go for double 4060ti's instead? 7800X3D vs 13/14700k and 4070Ti vs 4080 Help me decide 247 votes, 175 comments. I wish the 4080 offered just a bit more performance, like 25%-30% instead of it being 18-20% over the 3090Ti and maybe $999 for AIB models. /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 Subreddit to discuss about Llama, the large language model created by Meta AI. staviq • Additional comment actions The 3080 had a die area of over 600 mm 2. What would be the best upgrade for me to use more capable models? Hi all. Best idea would probably be to wait a bit until finetunes built on llama 3 start coming. So now, I'm tweaking settings in Starfield to eke out enough FPS to make up for switching back. 2 T/s. The stock model appears to be a decided upgrade from 2, as should any finetunes built on it. com/krychu/llama, with ~4 tokens/sec. 0 The text quality of Llama 3, at least with a high dynamic temperature threshold of lower than 2, is honestly indistinguishable. It can pull out answers and generate new content from my existing notes most of the time. 0 (so equivalent to X16 PCI-E 3. Get 24GB /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt app developers, hamper moderation, and exclude blind Corsair Vengeance LPX 64 GB (2 x 32 GB) DDR4-4000 CL18 Memory - Storage: Samsung 980 Pro 2 TB M. 99 ms llama_print_timings: sample time Get the Reddit app Scan this QR code to download the app now. Can you write your specs CPU Ram and token/s ? comment sorted by Best Top New Controversial Q&A Add a Comment. Reasons I want to choose the 4080: Vastly better (and easier) support Post your hardware setup and what model you managed to run on it. These high-performance GPUs are designed for handling heavy computational tasks like natural language processing (NLP), which is what LLaMA falls under. Originally designed for computer architecture research at Berkeley, RISC-V is now used in everything from $0. 6-mixtral-8x7b. I use two servers, an old Xeon x99 motherboard for training, but I serve LLMs from a BTC mining motherboard and that has 6x PCIe 1x, 32GB of RAM and a i5-11600K CPU, as speed of the bus and CPU has no effect on inference. It also shows the tok/s metric at the bottom of the chat dialog. 58 $/year (purchase repaid in 158 years) shadow of a doubt more speed to be had from a single 3090 than any combo of dual 12 or 16GB cards though I'm sure dual 4080 could do well. View community ranking In the Top 5% of largest communities on Reddit. I‘m working on a REST API for llama 2 70b uncensored—maybe you‘ll not need to run it If you want to use this purely for AI, I'd go with the two 3090s all day. /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. I went with dual 4090s in thy new rig with 13900k, this is needed to run 70b models effectively. Members Online • Slaghton . Its a debian linux in a host center. Or check it out in the app stores Get one with a 4080 unless you can get an AMD with better stats. The 4080 has a die area under 400 mm 2. 6 Llama-1-70B 3. 39 seconds (12. . 8 8. Thanks! Its a 4060ti 16gb; llama said its a 43 layer 13b model (orca). Commercial-scale ML with distributed compute is a skillset best developed using a cloud compute solution, not two 4090s on your desktop. com [From Kopite7kimi on X] Quantized Llama models can run very well on 24GB. 500€? I assume, GPU is the most relevant piece of hardware? What would be better: One GeForce RTX 4080 24GB or two GeForce RTX 4060 Ti 16GB? Llama 2 is the first offline chat model I've tested that is good enough to chat with my docs. However, I'd like to share that there are free alternatives available for you to experiment with before investing your hard-earned money. It’s been trained on our two recently announced custom-built 24K GPU clusters on over 15T token of data – a training dataset 7x larger than that used for Llama 2, including 4x more code. Using https://github. 2-2280 PCIe 4. The topmost GPU will overheat and throttle massively. Dolphin-2. Having said that, I pulled the trigger on one through bb with a 10% discount code + 5% using bb card. This results in the most capable Llama model yet, which supports a 8K context length that doubles the capacity of Llama 2. 000 - 1. The benefit of this over straight llama chat is that it To those who are starting out on the llama model with llama. In fact the 4090 is the most popular card for running Llama models main. Output ----- llama_print_timings: load time = 1241. Generation So I recently just bought 2x32gb sticks of ddr4 and made it work with 2 older sticks of 2x8gb for a total of 80gb of ram. This is the same phenomenon that It will beat all llama-1 finetunes easily, except orca possibly. cpp levels. The infographic could use details on multi-GPU arrangements. 0 X4 NVME Solid State Drive: $129. I would actually argue that it is better, because there is less frequent use of the stereotypical phrases associated with GPT training data. 24GB is the most vRAM you'll get on a single consumer GPU, so the P40 matches that, and presumably at a fraction of the cost of a 3090 or 4090, but there are still a number of open source models that won't fit there unless you shrink them considerably. Or check it out in the app stores TOPICS RTX 4080 SUPER with full AD103 GPU and 10240 CUDA cores - VideoCardz. below are the temperature under the full load during the GPT-2 training from scratch. But you can run Llama 2 70B 4-bit GPTQ on 2 x Hi, playing around with local LLaMAs on my Laptop is awfully slow, so I am thinking about buying a new PC. As far as i can tell it would be able to run the biggest open source models currently available. I have used this 5. true. It's doable with blower style consumer cards, but still less than ideal - you will want to throttle the power usage. As far as llama-2 finetunes, very few exist so far, so it’s probably the best for everything, but that will change when more models release. use the following search parameters to narrow your results: subreddit: I saw that the Nvidia P40 arent that bad in price with a good VRAM 24GB and wondering if i could use 1 or 2 to run LLAMA 2 and increase inference times? I saw a lot of LM Studio allows you to pick whether to run the model using CPU and RAM or using GPU and VRAM. 94GB version of fine-tuned Mistral 7B and Which model can run on RTX 4090 24GB GDDR6X + DDR4 64GB? 7B can run on a Mac with mps or just cpu: https://github. For AI: the 3090 and 4090 are both so fast that you won't really feel a huge difference in speed jumping up from the 3090 to 4090 in terms of inference. Value missing with that one though. 32GB RAM, RTX 4080 12GB (mostly ASUS Rog Strix Scar 16 2023) Gaming Laptop with i9 12th, 32GB RAM, RTX 3080 16GB (mostly ASUS Zephyrus M16) Upgrade it later to 4070ti or 4080? upvotes LLM360 has released K2 65b, a fully reproducible open source LLM matching Llama 2 70b The unofficial but officially recognized Reddit community discussing the latest LinusTechTips, TechQuickie and other LinusMediaGroup content. 2x TESLA P40s would cost $375, and if you want faster inference, then get 2x RTX 3090s for around $1199. Get the Reddit app Scan this QR code to download the app now. VRAM is way more important, so 3090. The room temperature is about 28-30°C, this summer is pretty hot this year. This is an UnOfficial Subreddit to share your views regarding Llama2 I have a MSI X670E Carbon Wifi, which has 2 PCI-E slots connected directly to the PSU (PCI-E 5. 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. 2 Yi 34B (q5_k_m) at 1. Its a 28 core system, and enables 27 cpu cores to the llama. Most people here don't need RTX 4090s. Or check it out in the app stores TOPICS RTX 4080 16 717 320 1100 Nvidia 4070 12 Llama-2-13B 13. Come and join us today! Subreddit to discuss about Llama, the large language model created by Meta AI. gguf --ignore-eos --ctx-size 1024 --n-predict 1024 --threads 10 --random-prompt --color --temp 0. You really don't want these push pull style coolers stacked right against each other. If you want to play video games too, the 4090 is the way to go. 4 Llama-1-33B 5. I built a PC for Stable Diffusion but ended up finding far I'm running a simple finetune of llama-2-7b-hf mode with the guanaco dataset. 99 @ Amazon Video Card: NVIDIA Founders Edition GeForce RTX 3090 Ti 24 GB Video Card: $1640. 0, but well maybe for the future?) Each card runs at X8 PCI-E 4. What would be a good setup with a budget of 1. Or check it out in the app stores TOPICS I have a 4080 sitting on my desk Bought that before I got into local AI. Subreddit to discuss about Llama, the large language model created by Meta AI. 5 16k (Q8) at 3. I'm currently running a batch 2 rank 256 seq 4k peft qlora of a 7b and it takes 16GB vram. 4090 24gb is 3x higher price, but will go for it if its make faster, 5 times faster Yeah I read both, for the 4080 and 4090, the best PCBs with regards to the 4080 are the ones in the Asus ROG Strix and MSI Suprim X, op wasn't asking about the Strix but the TUF model. I can run 30b models on a single 4090. 6T/s and dolphin 2. It seriously went from 30+ T/s on MythoMax to single digits. In this case it is 8+3 stages and lower rated 15+3 MOSFETs (50A) compared to the Strix 10+3 stages and 18+3 70A MOSFETs. 4080 +32GB RAM isn't cutting the mustard for LLMs. This is in LM studio with ~20 layers I also have a 3080 with 5950x amd. During LLaMA inference it's much colder though. Might also give the stock 8B model a spin. Yes, a laptop with an RTX 4080 GPU and 32GB of RAM should be powerful enough for running LLaMA-based models and other large language models. /r/StableDiffusion is back 2 hours/day * 50 days/year = 1. A test run with batch size of 2 and max_steps 10 using the hugging face trl library (SFTTrainer) takes a little I’m selling this, post which my budget allows me to choose between an RTX 4080 and a 7900 XTX. exe --model . cpp (without BLAS) for inference and quantization I ran a limit my search to r/LocalLLaMA. 5x the performance and you don't need to Get the Reddit app Scan this QR code to download the app now. Output generated in 2. Now if the 4080 Ti will have the rumored 48GB, that could be a better choice than 2x3090 I would think. 10 CH32V003 microcontroller chips to the pan-European supercomputing initiative, with 64 core 2 GHz workstations in between. Llama 2 q4_k_s (70B) performance without GPU . com/ggerganov/llama. 0 --seed 42 --mlock --n-gpu-layers 999. Or check it out in the app stores TOPICS Subreddit to discuss about Llama, the large language model created by Meta AI. 3 21. Open chat 3. 4090 with xformers blows 3090 to bits, about 2. /llama-2-7b. Only 30XX series has NVlink, that apparently image generation can't use multiple GPUs, text-generation supposedly allows 2 GPUs to be LLaMA (Large Language Model Meta AI), a state-of-the-art foundational large language model designed to help researchers advance their work in this subfield of AI. Only to see my ExLlama performance in Ooba drop to llama. 2 for 4090 which makes the advantage of 4090 more modest, when the equivalent vram size and similar bandwidth are taken into account. 00 @ Amazon Video Card: NVIDIA Founders Edition GeForce RTX 3090 Ti 24 GB Video Card Now if we compare INT4 for example we get 568 tflops for 3090 vs 1321. Kinda sorta. (Had to change 2x8gb sticks ram timing in bios 25 votes, 24 comments. 65T/s. 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. cpp or other similar models, you may feel tempted to purchase a used 3090, 4090, or an Apple M2 to run these models. Drawing about the same amount of power under load, the 4080 has roughly 40% greater heat flux density, making it more challenging to cool. 0) Didn't knew about the discussion, gonna go there, thanks. More VRAM will enable you to The size of Llama 2 70B fp16 is around 130GB so no you can't run Llama 2 70B fp16 with 2 x 24GB. Just use the cheapest g. You need 2 x 80GB GPU or 4 x 48GB GPU or 6 x 24GB GPU to run fp16. 56 tokens/s, 30 RISC-V (pronounced "risk-five") is a license-free, modular, extensible computer instruction set architecture (ISA). I suspect a decent PC For example it states (hallucinates?) that the 3090 can likely run Llama 2 12B but the 4080 can likely run Llama 3 8B. /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt app developers, hamper moderation, and exclude blind Get the Reddit app Scan this QR code to download the app now. Some testing I've seen around suggests a fair lack of censorship. fgscz wonkr pocqe wjgjkh dbja tcxm ompod ecseicve uai lxnui