LLM VRAM Calculator | GPU Memory for Local AI

LLM VRAM calculator: check if a local model fits your GPU or Mac, using real GGUF file sizes and KV cache math matched to llama.cpp. Any context length. Free.

Also known as: llm vram calculator · gpu memory calculator for llm · how much vram do i need for llm · llm vram requirements · kv cache calculator · vram calculator gguf · local llm memory calculator · ollama vram calculator · llm context length memory

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Model and Context

8.0B params

Model

Layers and heads from unsloth/Meta-Llama-3.1-8B-Instruct; file sizes from bartowski/Meta-Llama-3.1-8B-Instruct-GGUF.

Weight format

Q4_K_M is the usual Ollama and LM Studio pick

KV cache type

-ctk / -ctv in llama.cpp

Context length (tokens)

Concurrent conversations

-np in llama-server; each gets the full context

Runtime overhead (GB)

compute buffers and driver context

Weights file size (GB, optional)

overrides the lookup, e.g. for AWQ or MLX

Check against

Total = weights + KV cache + any linear-attention state + overhead. The KV cache grows with every token of context, for every conversation held at once.

Vision encoders (mmproj files) are not included.

Memory Needed

The total VRAM, the split between weights and KV cache, and which GPUs and Macs can hold it will appear here.

About LLM VRAM Calculator

An LLM VRAM calculator tells you whether a local model will fit on your GPU or Mac before you download it. Pick a model, a quantization such as Q4_K_M and a context length, and it adds the real GGUF file size, the KV cache for every token you plan to hold and the runtime overhead, then checks the total against common NVIDIA cards and Apple Silicon machines.

Key Features

Uses actual GGUF file sizes from Hugging Face for 20 popular models wherever that file exists, not parameters times a rounded bit count
KV cache math matched to llama.cpp, including Gemma's sliding-window layers and the linear-attention layers in Qwen3.5 and newer
F16, q8_0, q4_0 and FP8 KV cache types, plus multiple concurrent conversations
Finds the longest context that still fits on the card you pick
Fit check across 8 GB to 141 GB GPUs and 16 GB to 512 GB Macs in one table
Custom mode for any model: enter layers, KV heads and head dimension from its config.json

Use Cases

Decide between an RTX 5090 and a used RTX 3090 before buying a card for local AI
Check whether Qwen3.8 27B or Gemma 4 31B fits on a 24 GB GPU at 32k context
Size a MacBook Pro or Mac Studio order for running 70B models with Ollama or LM Studio
Plan an internal llama-server for a team of four engineers sharing one GPU
See how much memory a q8_0 KV cache saves before changing -ctk and -ctv
Explain an out-of-memory error after raising the context window to 128k

Supported Formats

GGUF Q3_K_M to Q8_0

FP16 / BF16

FP8

llama.cpp

Ollama

LM Studio

vLLM

Related Keywords

llm vram calculator

gpu memory calculator for llm

how much vram do i need for llm

llm vram requirements

kv cache calculator

vram calculator gguf

local llm memory calculator

ollama vram calculator

llm context length memory

How much VRAM do I need to run an LLM?

Add three things. The weights cost about their file size: a Q4_K_M quant runs near 4.9 bits per parameter, so Llama 3.1 8B is a 4.92 GB file. The KV cache costs 2 x layers x KV heads x head dimension x bytes per value for every token of context, which is 128 KB per token for Llama 3.1 8B in F16, or 1.07 GB at 8,192 tokens and 17.18 GB at its full 131,072. Then allow about 1 GB for compute buffers and the driver. So the same 8B model needs about 7 GB for a short chat and over 23 GB at full context. Context length, more than parameter count, decides whether a model fits, and a q8_0 cache roughly halves that part.

Privacy & Security

All processing happens locally in your browser. Your data never leaves your computer, ensuring complete privacy and security.

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Frequently asked questions

What is LLM VRAM Calculator used for?

LLM VRAM calculator: check if a local model fits your GPU or Mac, using real GGUF file sizes and KV cache math matched to llama.cpp. Any context length. Free.

Is LLM VRAM Calculator free to use?

Yes. LLM VRAM Calculator is completely free with no usage limits, and there is no paid tier required to use it.

Do I need an account to use LLM VRAM Calculator?

No. LLM VRAM Calculator works immediately in your browser with no signup, login, or email address required.

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