MODEL ARCHITECTURE SPEC โข META AI109B MoE
Meta Llama 4 Scout (109B-A17B MoE) VRAM & inference speed
109B Total Params17B Active (MoE)48 Layers โข 8 KV Heads64K Default Ctx (Max 977K)Ollama: llama4:scout
Accurate memory requirements, KV cache footprint, and tokens/sec generation benchmarks for running Meta Llama 4 Scout (109B-A17B MoE) across local GPUs, Apple Silicon Macs, and cloud instances.
โ
Runs 100% in GPU VRAM (Optimal Headroom)71.66 GB (65%)~13 t/s
Meta Llama 4 Scout (109B-A17B MoE) on AMD Strix Halo Mini-PC (Ryzen AI Max+ 395 128GB)
โ Fits Comfortably in VRAM
โ FITS IN VRAM
Required VRAM
71.66 GB
65% of hardware capacity (110 GB)Est. Decode Speed
~13 tok/s
17B active params @ 256 GB/sAvailable Headroom
+38.34 GB
Safe for OS display & full contextMemory Allocation & Headroom
71.66 GB allocated of 110 GB capacity
65% utilized
Weights: 65.4 GB
KV: (32K): 3.22 GB
Overhead: 3.04 GB
Free Headroom: +38.34 GB
โก Architecture & Throughput Transparency: Single-user decode speed (~13 tok/s) is memory-bandwidth bound at batch size = 1 on AMD Strix Halo Mini-PC (Ryzen AI Max+ 395 128GB) (256 GB/s). Prompt prefill / TTFT (~189 tok/s) is compute-bound and utilizes GPU Tensor cores. Actual latency varies with FlashAttention-2 and runtime engine (Ollama/vLLM/llama.cpp).
OLLAMA_FLASH_ATTENTION=1 OLLAMA_KV_CACHE_TYPE=q8_0 ollama run llama4:scoutCloud Instance Options for Meta Llama 4 Scout (109B-A17B MoE)
On-DemandDeploy this model on an on-demand cloud GPU without local hardware constraints or power usage:
RunPod Cloud GPUsBest 1-Click Ollama & vLLM
$0.34/hr (RTX 4070 Ti) โ $2.39/hr (H100)Vast.ai GPU MarketplaceCheapest Dual RTX 3090 / 4090
$0.18/hr (RTX 3060) โ $0.55/hr (RTX 4090)Lambda GPU CloudEnterprise 8x H100 Clusters
$1.99/hr (GH200 / H100)Quantization Precision Matrix
32K ctx โข KV: Q8_0| Quantization | Weights | KV Cache | Total VRAM | Est. Speed | Fit Status |
|---|---|---|---|---|---|
| FP1616 bpw | 218 GB | 3.22 GB | 229.6 GB (209%) | 0 t/s | OOM |
| Q8_08.5 bpw | 115.54 GB | 3.22 GB | 123.55 GB (112%) | ~2 t/s | PARTIAL |
| Q6_K6.56 bpw | 89.38 GB | 3.22 GB | 96.48 GB (88%) | ~10 t/s | FITS |
| Q5_K_M5.68 bpw | 77.39 GB | 3.22 GB | 84.07 GB (76%) | ~11 t/s | FITS |
| Q4_K_M4.8 bpw | 65.4 GB | 3.22 GB | 71.66 GB (65%) | ~13 t/s | FITS |
| FP44.25 bpw | 57.77 GB | 3.22 GB | 63.76 GB (58%) | ~15 t/s | FITS |
| IQ3_XS3.3 bpw | 44.69 GB | 3.22 GB | 50.22 GB (46%) | ~18 t/s | FITS |
Export Full Architecture & Infrastructure Spec
Get an executive-ready PDF report with exact memory math, hardware benchmarks, and cost comparisons.
Hardware Compatibility Matrix for Meta Llama 4 Scout (109B-A17B MoE)
Standard Q4_K_M precision with 32K context window and Q8_0 KV cache
| Hardware System | VRAM Envelope | Required VRAM | Headroom | Est. Decode Speed | Compatibility | Test Fit |
|---|---|---|---|---|---|---|
| NVIDIA GeForce RTX 5090 (32GB GDDR7) Consumer GPU โข 1792 GB/s | 32 GB | 71.66 GB | -39.66 GB | 0 (OOM) | โ OOM | Test Fit โ |
| NVIDIA GeForce RTX 4090 (24GB GDDR6X) Consumer GPU โข 1008 GB/s | 24 GB | 71.66 GB | -47.66 GB | 0 (OOM) | โ OOM | Test Fit โ |
| 2x NVIDIA RTX 3090 Dual Rig (48GB Total VRAM) Multi-GPU Rig โข 936 GB/s | 48 GB | 71.66 GB | -23.66 GB | 0 (OOM) | โ OOM | Test Fit โ |
| NVIDIA GeForce RTX 5080 (16GB GDDR7) Consumer GPU โข 960 GB/s | 16 GB | 71.66 GB | -55.66 GB | 0 (OOM) | โ OOM | Test Fit โ |
| NVIDIA RTX 4070 Ti Super (16GB) Consumer GPU โข 672 GB/s | 16 GB | 71.66 GB | -55.66 GB | 0 (OOM) | โ OOM | Test Fit โ |
| NVIDIA GeForce RTX 3060 (12GB) Consumer GPU โข 360 GB/s | 12 GB | 71.66 GB | -59.66 GB | 0 (OOM) | โ OOM | Test Fit โ |
| Apple Mac Mini M4 Pro (64GB Unified Memory) Apple Silicon โข 273 GB/s | 54 GB | 71.66 GB | -17.66 GB | ~3 tok/s | โก PARTIAL | Test Fit โ |
| Apple Mac Studio M4 Max (128GB Unified Memory) Apple Silicon โข 546 GB/s | 112 GB | 71.66 GB | +40.34 GB | ~32 tok/s | โ FITS | Test Fit โ |
| Apple Mac Studio M5 Ultra (256GB Unified Memory) Apple Silicon โข 890 GB/s | 236 GB | 71.66 GB | +164.34 GB | ~52 tok/s | โ FITS | Test Fit โ |
| AMD Strix Halo Mini-PC (Ryzen AI Max+ 395 128GB) Unified APU / Mini-PC โข 256 GB/s | 110 GB | 71.66 GB | +38.34 GB | ~13 tok/s | โ FITS | Test Fit โ |
| NVIDIA DGX Spark (128GB Grace-Blackwell Unified) AI Appliance โข 273 GB/s | 118 GB | 71.66 GB | +46.34 GB | ~17 tok/s | โ FITS | Test Fit โ |
| NVIDIA H100 SXM (80GB HBM3 Cloud GPU) Datacenter Cloud GPU โข 3350 GB/s | 80 GB | 71.66 GB | +8.34 GB | ~219 tok/s | โก TIGHT FIT | Test Fit โ |