LLM Roofline
Llama 3 · Llama-3.1 · HF: meta-llama/Llama-3.1-405B-Instruct

Llama 3.1 405B Instruct — VRAM, KV Cache & Hardware Matrix

Serverless API Rate
$0.80 in / $1.20 out per 1M
Parameters
405.9B Dense
Attention
GQA (8 KV / 128 Q)
Layers × Hidden
126 × 16384
Max Native Context
128k tokens
MoE Experts
N/A (Dense)

Quantization Memory Footprint

Quantization BPW Weights Only Total @ 8k Ctx Total @ 32k Ctx Quality
FP16 16.00 771.17 GiB 777.91 GiB 789.72 GiB Lossless Reference
Q8_0 8.50 409.68 GiB 416.42 GiB 428.23 GiB Near-Lossless
Q6_K 6.57 316.66 GiB 323.40 GiB 335.21 GiB High Precision
Q5_K_M 5.69 274.25 GiB 280.98 GiB 292.80 GiB Balanced High
Q4_K_M 4.85 233.76 GiB 240.50 GiB 252.31 GiB Recommended 4-bit
MLX_4BIT 4.50 216.89 GiB 223.63 GiB 235.44 GiB Apple Silicon Optimized
IQ4_XS 4.25 204.84 GiB 211.58 GiB 223.39 GiB Compact 4-bit
Q3_K_M 3.91 188.45 GiB 195.19 GiB 207.00 GiB Aggressive Compression

Hardware Compatibility & Speed Leaderboard (Q4_K_M @ 32k Context)

Hardware Status Total / Limit Decode TTFT (4k) Max Safe Ctx Inspect
Apple Mac Studio M3 Ultra (512 GB) COMFORTABLE 252.3 / 399.4 GiB 2.4 tok/s 100.94s 128k Simulate →
Cloud NVIDIA H200 SXM (141 GB) OOM 252.5 / 140.4 GiB OOM — OOM Simulate →
Cloud NVIDIA H100 SXM (80 GB) OOM 252.5 / 79.4 GiB OOM — OOM Simulate →
Cloud NVIDIA A100 SXM (80 GB) OOM 252.5 / 79.4 GiB OOM — OOM Simulate →
NVIDIA RTX PRO 6000 Blackwell (96 GB) OOM 252.5 / 95.0 GiB OOM — OOM Simulate →
NVIDIA RTX 5090 (32 GB) OOM 252.5 / 31.0 GiB OOM — OOM Simulate →
NVIDIA RTX 4090 (24 GB) OOM 252.5 / 23.0 GiB OOM — OOM Simulate →
NVIDIA RTX 5080 (16 GB) OOM 252.5 / 15.0 GiB OOM — OOM Simulate →
NVIDIA RTX 3090 (24 GB Used) OOM 252.5 / 23.0 GiB OOM — OOM Simulate →
NVIDIA RTX 5070 Ti (16 GB) OOM 252.5 / 15.0 GiB OOM — OOM Simulate →
AMD Radeon RX 7900 XTX (24 GB) OOM 252.5 / 23.0 GiB OOM — OOM Simulate →
Cloud NVIDIA L40S (48 GB) OOM 252.5 / 47.4 GiB OOM — OOM Simulate →
Apple Mac Studio M3 Ultra (256 GB) OOM 252.3 / 199.7 GiB OOM — OOM Simulate →
2x NVIDIA RTX 3090 Rig (48 GB) OOM 252.5 / 46.6 GiB OOM — OOM Simulate →
Apple Mac Studio M2 Ultra (192 GB) OOM 252.3 / 149.8 GiB OOM — OOM Simulate →
Apple Mac Studio M4 Max (64 GB) OOM 252.3 / 49.9 GiB OOM — OOM Simulate →
Apple Mac Studio M4 Max (128 GB) OOM 252.3 / 99.8 GiB OOM — OOM Simulate →
NVIDIA RTX 5060 Ti (16 GB) OOM 252.5 / 15.0 GiB OOM — OOM Simulate →
Apple MacBook Pro M3 Max (64 GB) OOM 252.3 / 49.9 GiB OOM — OOM Simulate →
Apple MacBook Pro M3 Max (128 GB) OOM 252.3 / 99.8 GiB OOM — OOM Simulate →
NVIDIA RTX 3060 (12 GB) OOM 252.5 / 11.0 GiB OOM — OOM Simulate →
Apple Mac Mini M4 Pro (48 GB) OOM 252.3 / 37.4 GiB OOM — OOM Simulate →
Apple Mac Mini M4 Pro (64 GB) OOM 252.3 / 49.9 GiB OOM — OOM Simulate →
Ryzen AI Max+ 395 Strix Halo (128 GB) OOM 252.3 / 96.0 GiB OOM — OOM Simulate →
Ryzen AI Max+ 395 Strix Halo (64 GB) OOM 252.3 / 48.0 GiB OOM — OOM Simulate →
Apple Mac Mini M4 (16 GB) OOM 252.3 / 10.0 GiB OOM — OOM Simulate →
Apple Mac Mini M4 (24 GB) OOM 252.3 / 18.0 GiB OOM — OOM Simulate →
Ryzen AI 9 HX 370 Mini-PC (64 GB) OOM 252.3 / 48.0 GiB OOM — OOM Simulate →

Interactive Llama 3.1 405B Instruct Simulator

405.9B Dense · GQA
819 GB/s · 58 TFLOPS
3. Weight Quantization 4.85 bpw
4. KV Cache
32,768 tok
Compute Roofline
COMFORTABLE FIT Memory-Bandwidth Bound
Max Safe Ctx: 128k
Memory Allocation Footprint 252.31 / 399.36 GiB usable
Weights: 233.76 GiB KV Cache: 15.75 GiB Overhead: 2.80 GiB Headroom: 147.05 GiB
Decode Speed
2.4
tok/s (batch=1)
Prefill Speed
41
prompt tok/s
TTFT Latency
100.94s
for 4,096 tok
Active Params
405.9B
of 405.9B total
llama.cpp Server Command
llama-server -hf meta-llama/Llama-3.1-405B-Instruct:Q4_K_M -ngl 99 -fa on -c 32768 --port 8080
Context KV Cache Total VRAM Decode Status
4k 1.97 GiB 237.40 GiB 2.5 tok/s COMFORTABLE
8k 3.94 GiB 240.50 GiB 2.5 tok/s COMFORTABLE
16k 7.88 GiB 244.44 GiB 2.5 tok/s COMFORTABLE
32k 15.75 GiB 252.31 GiB 2.4 tok/s COMFORTABLE
64k 31.50 GiB 268.06 GiB 2.2 tok/s COMFORTABLE
128k 63.00 GiB 299.56 GiB 2.0 tok/s COMFORTABLE

Buy-vs-Cloud-vs-API Monthly TCO Break-Even

USE SERVERLESS API
Own Hardware/mo
$203.05
2092.9h active + power
Cloud GPU/mo
$8399.76
@$3.49/hr spot/pod
Serverless API/mo
$58.00
Payback: 233.3 mo

Engineering FAQ — Llama 3.1 405B Instruct

How much VRAM does Llama 3.1 405B Instruct require in Q4_K_M?

Llama 3.1 405B Instruct weights occupy 233.76 GiB in Q4_K_M. Including 32k FP16 KV cache and runtime buffers, total memory is 252.31 GiB.

What is the cheapest local hardware that runs Llama 3.1 405B Instruct?

Apple Mac Studio M3 Ultra (512 GB) (512 GB) runs Llama 3.1 405B Instruct Q4_K_M at ~2.4 tok/s decode and 100.94s TTFT.

How does Llama 3.1 405B Instruct scale KV cache at long context?

Llama 3.1 405B Instruct uses GQA with 8 KV heads across 126 layers (128 head_dim).