4080 llama 2 reddit Output ----- llama_print_timings: load time = 1241. Open chat 3. 341/23. Reddit's most popular camera brand-specific subreddit! We are an unofficial community of users of the Sony Alpha brand and related gear: Sony E Mount, Sony A Mount, legacy Minolta GPU: 4090 CPU: 7950X3D RAM: 64GB OS: Linux (Arch BTW) My GPU is not being used by OS for driving any display Idle GPU memory usage : 0. 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. I am currently running the base llama 2 70B at 0. Price/performance is Here are the timings for my Macbook Pro with 64GB of ram, using the integrated GPU with llama-2-70b-chat. Sell your stuff and buy some stuff through reddit from redditors with Dubai classifieds! Hire local redditors here! Members Online Get the Reddit app Scan this QR code to download the app now. WizardLM-2-7B-abliterated and Llama-3-Alpha-Centauri-v0. LLaMA-65B is a better foundational model than GPT-3 175B. If you want to play video games too, the 4090 is the way to go. It's good that the llama. This is the same phenomenon that To those who are starting out on the llama model with llama. jsons tokenizer. 2 T/s. I can run 30b models on a single 4090. But I guess I need to try NG+ of Alan Wake 2 with full path tracing. 0 (so equivalent to X16 PCI-E 3. /llama-2-7b. Dolphin-2. Its a 28 core system, and enables 27 cpu cores to the llama. So only a $190 difference between all the RGB and cheap non RGB stuff. Its a debian linux in a host center. /r/StableDiffusion is back open after the protest of Reddit killing open API access, which Get the Reddit app Scan this QR code to download the app now. below are the temperature under the full load during the GPT-2 training from scratch. I also have a 3080 with 5950x amd. I initially wanted to go with 2 4090s to be able to load even whole quantisized 70B models into the vram. Reasons I want to choose the 4080: Vastly better (and easier) support Subreddit to discuss about Llama, the large language model created by Meta AI. I mostly played Like A Dragon Infinite Wealth which isn't a heavy 322 votes, 124 comments. Llama 2 is the first offline chat model I've tested that is good enough to chat with my docs. 6 Llama-1-70B 3. And 2 cheap secondhand 3090s' 65b speed is 15 token/s on Exllama. The memory chips maybe don't exist yet, in double capacity to be replaced. 4090 24gb is 3x higher price, but will go for it if its make faster, 5 times faster 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. Buy 1 or 2 first and see if you can get a decent setup and speed for a 34b and then buy more. 0, but well maybe for the future?) Each card runs at X8 PCI-E 4. You could make it even cheaper using a pure ML cloud computer 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. 4. Get the Reddit app Scan this QR code to download the app now. 13B is barely fitting in VRAM, though usually partially in CPU/RAM i still get decent enough performance. Especially not linearly. model ; example, llama-30b folder in the models folder with all . Interesting, in my case it runs with 2048 context, but I might have done a few other things as well — I will check later today. I'm really curious what we will see in 1 year, 2 years, 5 years. So now, I'm tweaking settings in Starfield to eke out enough FPS to make up for switching back. Value missing with that one though. It all unfolds quickly and maybe these answers will be outdated in 2 weeks again. r/StableDiffusionInfo. Looking forward to seeing other people's opinions. Since a 4090 is only about 30% faster than a 4080 for gaming but costs more than 30% more. 1 8B with a 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? For example it states (hallucinates?) that the 3090 can likely run Llama 2 12B but the 4080 can likely run Llama 3 8B. I built a PC for Stable Diffusion but ended up finding far I’m selling this, post which my budget allows me to choose between an RTX 4080 and a 7900 XTX. What I tried: MiXtral 8x7b Get the Reddit app Scan this QR code to download the app now. They are way cheaper than Apple Studio with M2 ultra. The topmost GPU will overheat and throttle massively. 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. 13B 6Bit quantized is acceptable. Try out the -chat version, or any of the plethora of fine-tunes (guanaco, wizard, vicuna, etc). com [From Kopite7kimi on X] Best idea would probably be to wait a bit until finetunes built on llama 3 start coming. cpp folks are adding support for it. 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. 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. Scenario 2. cpp and textwebui Hey, i know many dont like these kind of questions buttttttt. It can pull out answers and generate new content from my existing notes most of the time. And the 4080 super will squeeze out a few more frames to shorten the gap. 99 @ Amazon Video Card: NVIDIA Founders Edition GeForce RTX 3090 Ti 24 The 3080 had a die area of over 600 mm 2. I don't know if nvidia can make a 32 GB 4080 though, like 24GB 4070ti. It's doable with blower style consumer cards, but still less than ideal - you will want to throttle the power usage. RTX 4090's Training throughput/Watt is Get the Reddit app Scan this QR code to download the app now. Is there anything I can do with a 4080 that's beyond just some toy experiment? I'd fully expect the 4080/16GB to outperform the 3090 Ti, just like how the 3080/10GB outperformed the 2080 Ti. Or check it out in the app stores     TOPICS. 2 Yi 34B (q5_k_m) at 1. Now if the 4080 Ti will have the rumored 48GB, that could be a better choice than 2x3090 I would think. You really can't. r/LocalLLaMA. Please use our Discord server instead of supporting a company that acts against 25 votes, 24 comments. They are only $75-100. But what sort of speed are you getting, and what setup is that? How is the model split? Keep in mind if you have two 3090s working together they will be at 50% each, so unless there's something wrong, 40% utilization means the P40 is performing about as well as the 3090, or it's only got a couple of layers to process, or there's something wrong with the setup. 5 tokens/s. I want to buy a computer to run local LLaMa models. But ROCm extremely not-ready-for-prime-time, and unless you're looking for a very difficult project to work on, shouldn't be considered as an option by normal people just yet. This is an UnOfficial Subreddit to share your views regarding Llama2 It will beat all llama-1 finetunes easily, except orca possibly. I have a MSI X670E Carbon Wifi, which has 2 PCI-E slots connected directly to the PSU (PCI-E 5. 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. Or check it out in the app stores     TOPICS RTX 4080 SUPER with full AD103 GPU and 10240 CUDA cores - VideoCardz. Rtx 3090 has 24GB and 4080 has 12/16GB vram. 5x the performance and you don't need to Subreddit to discuss about Llama, the large language model created by Meta AI. 1 /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt app developers, hamper moderation, and Get the Reddit app Scan this QR code to download the app now. Members Online • Slaghton . Some RTX 4090 Highlights: 24 GB memory, priced at $1599. My Question is, however, how good are these models running with the recommended hardware requirements? Is it as fast as ChatGPT generating responses? Or does it take like 1-5 Minutes to generate a response? Two 4090s can run 65b models at a speed of 20+ tokens/s on either llama. Internet Culture (Viral) Does that mean the 4080 super suprim x hasn’t released yet? I’ve seen a bunch of other 4080 Super cards release. Can you write me a poem about Reddit, a debate about 8B vs 70B llms In the depths of Reddit, where opinions roam free, A debate rages on, between two camps you see, The 8B brigade, with conviction strong, Advocates for their preferred models, all day long Their One of these to pair with my 4080 does seem like a better option than trying to cram a 4080 and 4090 into the same case, especially for $4-500 cheaper. 5 16k (Q8) at 3. /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt app developers Below is a review from Techpowerup. 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. Some testing I've seen around suggests a fair lack of censorship. Intel 8-core/64GB RAM/nVidia-4080/16GB VRAM/Win10. The room temperature is about 28-30°C, this summer is pretty hot this year. Currently I have 8x3090 but I use some for training and only 4-6 for serving LLMs. The 4080 is a faster car, the 3090 has a bigger trunk. I heard 2 3090 would be also sufficient, but by the time I would spend this amount of money, I'd rather go with some gpus that will be supported for a bit The delta between this 4080 and the cheapest 4080 is more than $250. cpp, leading the exl2 having higher quality at lower bpw. 96 ms (2. Hi all, here's a buying guide that I made after getting multiple questions on where to start from my network. But they are going to keep competing and leapfrogging each other with improvements. 57 ms llama_print_timings: sample time = 229. 70 ms per token, 1426. I'm looking for the most silent RTX 4070 ti super or 4080 super for an upgrade of my old 1660. 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 Thanks! Its a 4060ti 16gb; llama said its a 43 layer 13b model (orca). The eval rate of the response comes in at 8. I'm currently running a batch 2 rank 256 seq 4k peft qlora of a 7b and it takes 16GB vram. Or check it out in the app stores Throughput of MI300X on LLama 2 70B. More info: https://rtech. Commercial-scale ML with distributed compute is a skillset best developed using a cloud compute solution, not two 4090s on your desktop. Nvidia 4080 PCIe Cable question Reddit is dying due to terrible leadership from CEO /u/spez. 5B-v2 and sadly it mostly produced gibberish. Its possible to use as exl2 models bitrate at different layers are selected according to calibration data, whereas all the layers are the same (3bit for q2_k) in llama. I can even run fine-tuning with 2048 context length and mini_batch of 2. A notebook 4090 is essentially a desktop 4080, compare the CUDA core count and VRAM on this spec listing The on-board Edge TPU is a small ASIC designed by Google that accelerates TensorFlow Lite models in a power-efficient manner: it's capable of performing 4 trillion operations per second (4 TOPS), using 2 watts of power—that's 2 TOPS per watt. Curious how to achieve those speeds with such a large model. Or check it out in the app stores   If Ibuy a Nvidia GPU with 16Gb of VRAM (4080 or 4070Ti super), is it already good enough to get started? Let me know. What I tried: MiXtral 8x7b One of these to pair with my 4080 does seem like a better option than trying to cram a 4080 and 4090 into the same case, especially for $4-500 cheaper. Value missing For if the largest Llama-3 has a Mixtral-like architecture, then so long as two experts run at the same speed as a 70b does, it'll still be sufficiently speedy on my M1 Max. Subreddit to discuss about Llama, the large language model created by Meta AI. The 4090 averaged 199 fps at 1440p while the 4080 averaged 177 fps. Might also give the stock 8B model a spin. Are the P100's actually distributing processing resources? I thought models RTX 4070TI Super vs RTX 4080? upvotes r/StableDiffusionInfo. model and relevant . Members Online • and you can train monkeys to do a lot of cool stuff like write my Reddit posts. airoboros-l2-70B-gpt4-1. Only 30XX series has NVlink, that apparently image generation can't use multiple GPUs, text-generation supposedly allows 2 GPUs to be used simultaneously, whether you can mix and match Nvidia/AMD, and so on. cpp or Exllama. Using both llama. Or check it out in the app stores     TOPICS 20 tokens/s for Llama-2-70b-chat on a RTX 3090. I have no knowledge about gpu and hire different vfx artist/editor to work on my system. At 4k the 4090 does better (20% - 152fps vs 121). I used Llama-2 as the guideline for VRAM limit my search to r/LocalLLaMA. How does this compare to NVidia high-end GPUs? No. 10 CH32V003 microcontroller chips to the pan-European supercomputing initiative, with 64 core 2 GHz workstations in between. You cannot get a 4090 for $190 more than a 4080. It seriously went from 30+ T/s on MythoMax to single digits. /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. 65 ms / 64 runs ( 174. 98 Test Prompt: make a list of 100 countries and their currencies in MD table use a column for numbering Interface: text generation webui GPU + CPU Inference Get the Reddit app Scan this QR code to download the app now. More VRAM will enable you to Which model can run on RTX 4090 24GB GDDR6X + DDR4 64GB? 7B can run on a Mac with mps or just cpu: https://github. /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt app developers, hamper moderation, and exclude blind The text quality of Llama 3, at least with a high dynamic temperature threshold of lower than 2, is honestly indistinguishable. 38 tokens per second) llama_print_timings: prompt eval time = 42122. 89 ms / 328 runs ( 0. json files and tokenizer. com/krychu/llama, with ~4 tokens/sec. So therefore, you're very wrong. This is in LM studio with ~20 layers Now if we compare INT4 for example we get 568 tflops for 3090 vs 1321. You really don't want these push pull style coolers stacked right against each other. Speed -> 1) Meta AI 2) Gemini Advanced If the AI race were to stop today, I'd be pretty happy with using Claude Opus. Only to see my ExLlama performance in Ooba drop to llama. Issues with System Prompt Following for finetuned Llama-2 models (e. 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. 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. 3080/90/4080/90 is unrealistic for most users 101K subscribers in the LocalLLaMA community. At 1200$, current 4080 pricing. 6T/s and dolphin 2. 0 X4 NVME Solid State Drive: $129. I'm aware transformers are pretty vram hungry and a 4080 only has 16 GB. 99 ms llama_print_timings: sample time Corsair Vengeance LPX 64 GB (2 x 32 GB) DDR4-4000 CL18 Memory - Storage: Samsung 980 Pro 2 TB M. 8M subscribers in the Amd community. However, I'd like to share that there are free alternatives available for you to experiment with before investing your hard-earned money. Or check it out in the app stores     TOPICS Subreddit to discuss about Llama, the large language model created by Meta AI. Or check it out in the app stores     TOPICS I can find a RTX 4080 with a 32gb memory and a 13900HX for ~2,000$ while a 3080ti with a higher VRAM, a 32GB SSD and a 12900HX for only ~1400$. 0) Didn't knew about the discussion, gonna go there, thanks. RTX 4090's Training throughput and Training throughput/$ are significantly higher than RTX 3090 across the deep learning models we tested, including use cases in vision, language, speech, and recommendation system. 65T/s. any opinion can help I have 5900x cpu 32gb ram 1000w psu , i have no gpu currently *cough* using a gtx 560 just to get a display ^^ . 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. 4090 with xformers blows 3090 to bits, about 2. 2 for 4090 which makes the advantage of 4090 more modest, when the equivalent vram size and similar bandwidth are taken into account. gguf --ignore-eos --ctx-size 1024 --n-predict 1024 --threads 10 --random-prompt --color --temp 0. During LLaMA inference it's much colder though. I have read the recommendations regarding the hardware in the Wiki of this Reddit. Cut down 4080 with 16GB vram. This results in the most capable Llama model yet, which supports a 8K context length that doubles the capacity of Llama 2. Note, both those benchmarks runs are bad in that they don't list quants, context size/token count, or other relevant details. So I am guessing a lot of transformer based models will be out of the question. Just use the cheapest g. cpp or other similar models, you may feel tempted to purchase a used 3090, 4090, or an Apple M2 to run these models. Look at 1440p average FPS for the over 20 games tested. I went with dual 4090s in thy new rig with 13900k, this is needed to run 70b models effectively. 78 tokens per second) llama_print_timings: prompt eval time = 11191. Do you think that's enough to run llama3. The 4080 Vs 4080 super you wouldn't be able to tell the difference without a framerate counter and even with one you could get it wrong if the time of day in the game is different by a few minutes or there is 12 npc,s on the screen instead of 11 It will beat all llama-1 finetunes easily, except orca possibly. py file in its model folder with all . ggml: llama_print_timings: load time = 5349. Kinda sorta. Q4_0. If you want to use this purely for AI, I'd go with the two 3090s all day. 87 ms per Two 4090s can run 65b models at a speed of 20+ tokens/s on either llama. While Llama 3 8b and 70b are cool, I wish we also had a size for mid-range PCs (where are 13b and 30b versions Meta?). 1 and StableBeluga2) /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. gguf with 4080 + Cpu . support/docs/meta Get the Reddit app Scan this QR code to download the app now. pt in this case) Uh, from the benchmarks run from the page linked? Llama 2 70B M3 Max Performance Prompt eval rate comes in at 19 tokens/s. B GGML 30B model 50-50 RAM/VRAM split vs GGML 100% VRAM In general, for GGML models , is there a ratio of VRAM/ RAM split that's optimal? 4080(say 50layers GPU/ 10 layers CPU) , 4070ti (40 Layers GPU/ 20 layers CPU) Bonus question how does a GPTQ Llama 2 13B working on RTX3060 12GB with Nvidia Chat with RTX with one edit Tutorial | Guide Seasonic Prime TX-1000 with RTX 4080 upvotes r/LocalLLaMA. If what you want is too big to fit in the 4080, it doesn’t matter how fast it is and a lot of more advanced AI stuff is Codellama i can run 33B 6bit quantized Gguf using llama cpp Llama2 i can run 16b gptq (gptq is purely vram) using exllama Llama2 i can run 70B ggml, but it is so slow. cpp you can try playing with LLAMA_CUDA_MMV_Y (1 is default, try 2) and LLAMA_CUDA_DMMV_X (32 is default try 64). It basically improves the computer’s ai/ml processing power. Originally designed for computer architecture research at Berkeley, RISC-V is now used in everything from $0. 3-3. 5bpw models. use the following search parameters to narrow your results: subreddit: I was planning to build one for my office but my budget allows me to get an i7 / 32GB RAM / NVidia 4080 (16GB VRAM). pt (llama-30b-4bit. The benefit of this over straight llama chat is that it As far as i can tell it would be able to run the biggest open source models currently available. 4 Llama-1-33B 5. Come and join us today! Members Online. Llama 2 13B working on RTX3060 12GB with Nvidia Chat with RTX with one edit Nooh question but I don't need to worry about any compatibility issue between 4080 and that right, I can get 2 of those at a lesser price than a used 3090. Welcome to /r/AMD — the subreddit for all things AMD; come talk about Ryzen, Radeon Also, just a fyi the Llama-2-13b-hf model is a base model, so you won't really get a chat or instruct experience out of it. Share Sort by: Best. Even if you went with a different cooler and fans, like a Peerless Assassin and five P12 fans, that's still $60. I would actually argue that it is better, because there is less frequent use of the stereotypical phrases associated Get the Reddit app Scan this QR code to download the app now. Please use our Discord server instead of supporting a company that acts against Get the Reddit app Scan this QR code to download the app now. The 4090 is a different chip, cut down from data center and machine learning AI chips. Discuss all things about StableDiffusion here. These high-performance GPUs are designed for handling heavy computational tasks like natural language processing (NLP), which is what LLaMA falls under. The infographic could use details on multi-GPU arrangements. Can you write me a poem about Reddit, a debate about 8B vs 70B llms In the depths of Reddit, where opinions roam free, A debate rages on, between two camps you see, The 8B brigade, with conviction strong, Advocates for their preferred models, all day long Their RISC-V (pronounced "risk-five") is a license-free, modular, extensible computer instruction set architecture (ISA). 3-2. Price/performance is RTX 4090 vs RTX 3090 Deep Learning Benchmarks. g. (Had to change 2x8gb sticks ram timing in bios 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. That is why I find this upscaling thing very interesting. Most people here don't need RTX 4090s. (458. The difference is 12%. That being said, 2 P40s on a single board do seem to get ~3t/s with 65B models, which isn't great, but it's manageable when you just need a I found this upscaled version of Llama 3 8b: Llama-3-11. If the smaller models will scale similarly at 65B parameters, a properly tuned model should be able to perform on par with GPT-3. Having said that, I pulled the trigger on one through bb with a 10% discount code + 5% using bb card. My Confusion is 3090 has more vram but 4080 has next gen RAY TRACING & DLSS3. Or check it out in the app stores     TOPICS RTX 4080 16 717 320 1100 Nvidia 4070 12 Llama-2-13B 13. a fully reproducible open source LLM matching Llama 2 70b. 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 2 hours/day * 50 days/year = 1. Q4_K_M. 5-turbo, at the very least. There are also some ram swapped frankencards that are 24gb for less than a Get the Reddit app Scan this QR code to download the app now Currently i have a single 4080 with an i7. 5B-v2, with GGUF quants here. 8 8. 5 tok/s. Come and join us today! 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. Sell your stuff and buy some stuff through reddit from redditors with Dubai classifieds! Hire local redditors here! Members Online But IIRC the 4080 is basically the max specs for that chip. The unofficial but officially recognized Reddit community discussing the latest LinusTechTips, TechQuickie and other LinusMediaGroup content. main. In terms of pascal-relevant optimizations for llama. I can see 2 possibilities for 4070ti 2024. 0 --seed 42 --mlock --n-gpu-layers 999. I'm loading TheBloke's 13b Llama 2 via ExLlama on a 4090 and only getting 3. 13) put the 4-bit . true. Reply reply nuketro0p3r 2 hours/day * 50 days/year = 1. 1. 2x TESLA P40s would cost $375, and if you want faster inference, then get 2x RTX 3090s for around $1199. 25 votes, 24 comments. 0 247 votes, 175 comments. Same but with 24GB vram. Thank you. i did find 3090 ti boxed (new) on secondhand website the guy selling it said his 3090 ti had a unknown defect and got a new one under the warranty it took awhile for him to get a new one Quality -> 1) Claude Opus, 2) ChatGPT 4. Similarly, there might be a 4080ti cut down from 4090 with 20/24GB vram. I profiled it using pytorch profiler with a tensorboard extension (it can also profile vram usage), and then did some stepping through the code in a vscode debugger. Not sure about other models though. Doing some quick napkin maths, that means that assuming a distribution of 8 experts, each 35b in size, 280b is the largest size Llama-3 could get to and still be chatbot Not sure about compatibility with a 3090, but I slapped a P40 next to my 4080 just to test it out and the speeds became unbearably slow. At least anything that is interesting. 4080 +32GB RAM isn't cutting the mustard for LLMs. I suspect a decent PC Using 2. I'd fully expect the 4080/16GB to outperform the 3090 Ti, just like how the 3080/10GB outperformed the 2080 Ti. cpp levels. 2-2280 PCIe 4. 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. If what you want to carry fits in the 4080, then it’s the best model- it’ll get you there fast. I tried this Llama-3-11. Drawing about the same amount of power under load, the 4080 has roughly 40% greater heat flux density, making it more challenging to cool. 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. The benefit of this over straight llama chat is that it I found this upscaled version of Llama 3 8b: Llama-3-11. If you want a 4080 with more power, you're not asking them to squeeze more performance out of the 4080 die, you're really asking them to bin 4090 chips to a lower level and put a 4080 label on it. What would be the best upgrade for me to use more capable models? Hi all. 6-mixtral-8x7b. Linus Tech Tips - I Scammed Myself on eBay Subreddit to discuss about Llama, the large language model created by Meta AI. 3 21. The stock model appears to be a decided upgrade from 2, as should any finetunes built on it. 73 tokens per second) llama_print_timings: eval Which gpu is better for 3d, rendering, vfx, editing, post production RTX 3090 or RTX 4080? Not interested in gaming. . 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. VRAM is way more important, so 3090. If you have money to blow, you could buy a bunch of Mi75. 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 Subreddit to discuss about Llama, the large language model created by Meta AI. /r/StableDiffusion is back /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. UPDATE: I GOT MY 4080 SUPER SUPRIM X!!!! I was finally able to get one off the US It's good that the llama. exe --model . mctx gjyecy kylom yjgzbm ihxe mosjl zudpjov ipzvv urrliy ibpt