Llama · Llama 4 · 109B parameters · 17B active

Llama 4 Scout 109B-A17B VRAM requirements

Llama 4 Scout 109B-A17B has 48 layers and uses grouped-query attention (8 KV heads). At Q4_K_M the weights come to 61.7 GB.

Model

Hardware

Quantisation

Context 8K

KV cache precision

Runtime

Batch

GPUs

Monitor plugged into this GPU

Won't fit

64.0 GB of 21.8 GB · 294%

067 GB

Weights 61.7 GB

KV cache 1.5 GB

Runtime overhead 0.8 GB

Over the limit 42.3 GB

Short by 42.3 GB. You can run it with 15 of 48 layers on the RTX 4090 and the rest in system RAM, at roughly 5.18 tok/s — usable for batch work, painful for chat. A smaller quantisation or a shorter context is usually the better trade.

Generation5.18tok/s

Prompt processing2038tok/s

Max context0tokens

KV per 1K tokens0GB

Every quantisation of Llama 4 Scout 109B-A17B on a RTX 4090

Highlighted row is the highest quality that still fits at 8K context.

Quantisation	bpw	Weights	Total	Verdict	Max ctx	tok/s
FP16 / BF16	16.00	203.0 GB	205.4 GB	Won't fit	—	1.28
INT8 / W8A8	8.50	107.4 GB	109.7 GB	Won't fit	—	2.58
Q8_0 (GGUF)	8.50	107.4 GB	109.7 GB	Won't fit	—	2.58
FP8 (E4M3)	8.00	101.5 GB	103.9 GB	Won't fit	—	2.79
Q6_K	6.56	83.2 GB	85.6 GB	Won't fit	—	3.53
Q5_K_M	5.67	71.9 GB	74.3 GB	Won't fit	—	4.15
Q5_K_S	5.52	70.0 GB	72.4 GB	Won't fit	—	4.37
Q4_K_M	4.85	61.7 GB	64.0 GB	Won't fit	—	5.18
Q4_K_S	4.58	58.3 GB	60.7 GB	Won't fit	—	5.45
Q4_0	4.55	58.0 GB	60.3 GB	Won't fit	—	5.64
AWQ 4-bit	4.25	56.8 GB	59.1 GB	Won't fit	—	5.75
GPTQ 4-bit	4.25	56.8 GB	59.1 GB	Won't fit	—	5.75
MXFP4	4.25	56.8 GB	59.1 GB	Won't fit	—	5.75
IQ4_XS	4.25	54.2 GB	56.6 GB	Won't fit	—	6.17
Q3_K_M	3.91	50.0 GB	52.3 GB	Won't fit	—	6.84
IQ3_M	3.70	47.4 GB	49.7 GB	Won't fit	—	7.40
IQ3_XXS	3.06	39.4 GB	41.8 GB	Won't fit	—	9.93
Q2_K	2.63	34.1 GB	36.4 GB	Won't fit	—	13.1
IQ2_XXS	2.06	27.0 GB	29.3 GB	Won't fit	—	22.2
IQ1_M	1.75	23.1 GB	25.4 GB	Won't fit	—	37.8

Llama 4 Scout 109B-A17B on each GPU

Q4_K_M weights at 8K context, single card, monitor attached.

GPU	VRAM	GB/s	Verdict	Max ctx	tok/s
H100 SXM 80GB	80	3350	Runs comfortably	63K	177
A100 80GB	80	2039	Runs comfortably	63K	100
Mac Studio M3 Ultra 256GB	256	819	Runs comfortably	692K	38.5
Mac Studio M4 Max 128GB	128	546	Runs comfortably	180K	28.7
NVIDIA DGX Spark (GB10)	128	273	Runs comfortably	180K	14.8
Ryzen AI Max+ 395 128GB	128	256	Runs comfortably	180K	11.1
RTX A6000	48	768	Won't fit	—	9.64
L40S	48	864	Won't fit	—	9.40
RTX 5090	32	1792	Won't fit	—	6.75
Mac Mini M4 Pro 48GB	48	273	Won't fit	—	6.52
RTX 3090	24	936	Won't fit	—	5.39
RTX 4090	24	1008	Won't fit	—	5.18
Radeon RX 7900 XTX	24	960	Won't fit	—	4.91
RTX 5080	16	960	Won't fit	—	4.91
RTX 5070 Ti	16	896	Won't fit	—	4.90
RTX 5060 Ti 16GB	16	448	Won't fit	—	4.81
RTX 5070	12	672	Won't fit	—	4.57
RTX 4080 Super	16	736	Won't fit	—	4.43
RTX 4070 Ti Super	16	672	Won't fit	—	4.42
RTX 4060 Ti 16GB	16	288	Won't fit	—	4.28
RTX 3060 12GB	12	360	Won't fit	—	4.27
RTX 3080 10GB	10	760	Won't fit	—	4.16
RTX 4070 Super	12	504	Won't fit	—	4.12
RTX 4070	12	504	Won't fit	—	4.12
Arc B580	12	456	Won't fit	—	3.48

Architecture

Parameters	109B
Active per token	17B of 16 experts, top-1
Layers	48
Hidden size	5120
Attention heads / KV heads	40 / 8
Head dimension	128
Vocabulary	202,048
Trained context	10240K
KV cache per 1K tokens	0 GB
Hugging Face	meta-llama/Llama-4-Scout-17B-16E-Instruct

The Llama family

Meta's open-weight series, and the default target for most local tooling. Every Llama 3.x model uses grouped-query attention with 8 KV heads, so the cache stays modest even at 70B. Llama 4 moved to mixture-of-experts: Scout and Maverick occupy 109B and 400B of memory but read only 17B per token.

huggingface.co/meta-llama · llama.com · all 7 Llama models

Llama 4 Maverick 400B-A17B
400B · 17B active · 48 layers Llama 3.1 8B
8.0B · 32 layers Llama 3.1 70B
70.5B · 80 layers Llama 3.1 405B
405.9B · 126 layers Llama 3.2 1B
1.2B · 16 layers Llama 3.2 3B
3.2B · 28 layers

Direct answers

Llama 4 Scout 109B-A17B on RTX 5090
See the verdict Llama 4 Scout 109B-A17B on RTX 4090
See the verdict Llama 4 Scout 109B-A17B on RTX 3090
See the verdict Llama 4 Scout 109B-A17B on RTX 5080
See the verdict Llama 4 Scout 109B-A17B on RTX 5070 Ti
See the verdict Llama 4 Scout 109B-A17B on RTX 5070
See the verdict Llama 4 Scout 109B-A17B on RTX 4070 Ti Super
See the verdict Llama 4 Scout 109B-A17B on RTX 4070 Super
See the verdict Llama 4 Scout 109B-A17B on RTX 4070
See the verdict