nowfound

Life & fun · December 26, 2023

IM

I made a GPU VRAM calculator for transformer-based models

I made a GPU VRAM calculator for transformer-based models launched on December 26, 2023 with 135 votes, #366 of 3,780 launches that month and more than 95% of that year's launches. The site was still online in September 2026, 2 years on.

Visit vram.asmirnov.xyz ↗Alternativestop 10% of December 2023

In plain words

This tool calculates GPU VRAM requirements for transformer-based models. Users input model parameters and batch size to determine memory needs across different GPUs. It's designed for machine learning engineers and researchers who need to plan hardware requirements before training or deploying large language models and similar architectures.

written from the facts on this page · September 2026

From the sources

VRAM Calculator

Model Parameters could be taken from config.json on HuggingFace or directly from model via model.config Expanding dimensionality within MLP block. Usually it is 4 × hidden size. Number of Parameters (1.418 billion) × number of bytes per parameter (6; parameters are stored in both full precision and half precision) Sum of sizes of all intermediate tensors during forward pass across all 24 layers. Activations size have quadratic dependence on Sequence Length. Gradient is stored for each parameter in full precision, so it is Number of Parameters (1.418 billion) × number of bytes per parameter (4) Optimizer stores moving average of gradients for each parameter in full precision, so it is Number…from vram.asmirnov.xyz

Does a similar job

all alternatives →
  • I made a VRAM Calculator in Hugging Face2025 · chromewebstore.google.com · ▲9

    It's a chrome extension that automatically loads the specs from the Hugging Face model card into the calculation. > To test it, install the extension (no registration/key needed) and navigate to a HF model page. Then click the "VRAM" icon on the top right to open the sidepanel. You can specify quantization, batch size, sequence length, etc. Works for inference & fine-tuning. If it does not fit on the specified GPUs, it gives you an advise on how to still run it (e.g. lowering precision). It is inspired at my work, where we were constantly exporting metrics from HF to estimate required…

  • Llama 3.1 70B on a single RTX 3090 via NVMe-to-GPU bypassing the CPUFeb 2026 · github.com · ▲395

    Hi everyone, I'm kinda involved in some retrogaming and with some experiments I ran into the following question: "It would be possible to run transformer models bypassing the cpu/ram, connecting the gpu to the nvme?" This is the result of that question itself and some weekend vibecoding (it has the linked library repository in the readme as well), it seems to work, even on consumer gpus, it should work better on professional ones tho

  • Open-source calculator for "will my GPU run this LLM?"Aug 2026 · jaeseok614.github.io · ▲5

    LLM·RAG·VLM·아바타 워크로드를 GPU·CPU·RAM·스토리지·네트워크 구성과 경제형·권장형·확장형 견적 3안으로 변환하는 오픈소스 AI 인프라 산정 도구

  • Can your GPU run this LLM?2023 · github.com · ▲15

    Calculate token/s & GPU memory requirement for any LLM. Supports llama.cpp/ggml/bnb/QLoRA quantization - RahulSChand/gpu_poor

  • LI
    LLM Inference Calculator – Estimate VRAM, Latency, and ThroughputAug 2026 · llm-inference-calculator-delta.vercel.app · ▲6

    LLM Inference Calculator — Estimate throughput, latency, TTFT, TPOT, and GPU memory usage for large language model inference. LLM 推理计算器 — 估算大模型推理吞吐量 (throughput)、延迟 (latency)、TTFT、TPOT 与 GPU 显存占用。

  • PO
    PlaidML, open source deep learning for any GPU2017 · ▲52

    Our company Vertex.AI has been working on this for a while but this is the first public release. We're starting with using PlaidML to bring OpenCL support to Keras and more frameworks, platforms, etc are coming. Yes, this means you can use use your AMD GPU for deep learning dev. Sorry, no Mac or Windows support yet although the brave can try building from source (it should work). http://vertex.ai/blog/announcing-plaidml https://github.com/plaidml/plaidml

More life & fun this month

the category →

Source: Show HN post ↗

Launched alongside, December 2023

the whole month →
  • Hi HN! I’m proud to share that we have built a real 3rd party iMessage client for Android. We did it by reverse engineering the iMessage protocol and encryption system. It's available to download today (no waitlist): https://play.google.com/store/apps/details?id=com.beeper.ima and there's a technical writeup here: https://blog.beeper.com/p/how-beeper-mini-works. Unlike every other attempt to build an iMessage app for Android (including our first gen app), Beeper Mini does not use a Mac server relay in the cloud. The app connects directly to Apple…

    Work · 2023 · beeper.com

  • Hey! I made Heynote entirely for my own use case. For many years, I always had an Emacs instance running with the scratch buffer open, even long after I had abandoned Emacs as my programming editor in favor of more recent IDE:s. The simplicity of having just one big scratch buffer appeals to me, but I still want to separate the different things I jot down somehow (without using tabs or similar). Previously, my solution was to insert a bunch of blank lines between the notes, but hitting C-A would still select the entire buffer. That's why I came up with the concept of "blocks", which turned…

    Work · 2023 · heynote.com

  • LogoFast▲988

    Make beautiful logos with AI, fast & free

    AI · 2023 · logofa.st

  • FuseBase▲939

    Client collaboration platform for professional services

    Dev tools · 2023 · thefusebase.com

  • Beep! 2.0▲871

    Fastest tool to assign and share visual tasks with your team

    Work · 2023 · justbeepit.com

  • Clean Up Your Inbox In Minutes Newsletter management, AI automation, and email analytics. Inbox Zero is the open-source email app that puts you back in control of your inbox.

    AI · 2023 · getinboxzero.com