Meta/Dense

LLaMA 1 65B

Name: LLaMA 1 65B
Author: Meta

LLaMA 1 65B — largest original LLaMA. Impressive for its time.

chat

65.2B

Parameters

Context length

Benchmarks

Quantizations

80K

HF downloads

Architecture

Dense

Released

2023-02-24

Layers

KV Heads

Head Dim

128

Family

llama

Quantization Options

Quant	Bits	VRAM	Quality
IQ2_M	2.93	24.4 GB	low
Q2_K	3.16	26.2 GB	low
IQ3_XXS	3.25	27.0 GB	low
IQ3_XS	3.5	29.0 GB	low
Q3_K_S	3.64	30.2 GB	low
IQ3_M	3.76	31.1 GB	low
Q3_K_M	4	33.1 GB	low
Q3_K_L	4.3	35.5 GB	moderate
IQ4_XS	4.46	36.8 GB	moderate
Q4_K_S	4.67	38.5 GB	moderate
Q4_K_M	4.89	40.3 GB	good
Q5_K_S	5.57	45.9 GB	good
Q5_K_M	5.7	46.9 GB	good
Q6_K	6.56	54.0 GB	excellent
Q8_0	8.5	69.8 GB	lossless
FP16	16	130.9 GB	lossless

Select your GPU above to see speed estimates and compatibility for each quantization.

▸ READY TO RUN THIS?RENT BY THE HOUR

RENT A GPU AND RUN LLAMA 1 65B NOW

Rent on RunPod →Or Vast.ai →

Spin up an A100 / H100 / 4090 in ~60s. Pay by the second. Cancel anytime.

Community Ratings

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Benchmarks (7)

IFEval81.2

BBH54.1

MMLU-PRO48.1

MATH44.1

GPQA24.6

HumanEval23.7

MUSR22.3

Run this model

▸Easiest way to get started·Beginners

DOCS ↗

curl -fsSL https://ollama.com/install.sh | sh

$ollama run llama:65b-q4_K_M

Tag may need adjustment — check ollama.com/library/llama for available tags.

▸ SETUP GUIDE

Auto-setup with fitmyllm CLI

Detects your GPU, recommends the best model, downloads it, and starts chatting — zero config. Benchmarks your speed and contributes anonymous data to improve predictions.

pip install fitmyllmthen run fitmyllmLearn more

Auto-detect GPULive tok/s in chatSpeed benchmarks9 inference engines

HuggingFace GGUF Downloads Build Hardware