LLM Roofline
Mistral · Apache-2.0 · HF: mistralai/Mixtral-8x7B-Instruct-v0.1

Mixtral 8x7B Instruct — VRAM, KV Cache & Hardware Matrix

Serverless API Rate
$0.24 in / $0.24 out per 1M
Parameters
46.7B (12.9B act.)
Attention
GQA (8 KV / 32 Q)
Layers × Hidden
32 × 4096
Max Native Context
32k tokens
MoE Experts
2 / 8

Quantization Memory Footprint

Quantization BPW Weights Only Total @ 8k Ctx Total @ 32k Ctx Quality
FP16 16.00 88.73 GiB 91.04 GiB 94.04 GiB Lossless Reference
Q8_0 8.50 47.14 GiB 49.45 GiB 52.45 GiB Near-Lossless
Q6_K 6.57 36.43 GiB 38.75 GiB 41.75 GiB High Precision
Q5_K_M 5.69 31.55 GiB 33.87 GiB 36.87 GiB Balanced High
Q4_K_M 4.85 26.89 GiB 29.21 GiB 32.21 GiB Recommended 4-bit
MLX_4BIT 4.50 24.95 GiB 27.27 GiB 30.27 GiB Apple Silicon Optimized
IQ4_XS 4.25 23.57 GiB 25.88 GiB 28.88 GiB Compact 4-bit
Q3_K_M 3.91 21.68 GiB 23.99 GiB 26.99 GiB Aggressive Compression

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

Hardware Status Total / Limit Decode TTFT (4k) Max Safe Ctx Inspect
Cloud NVIDIA H200 SXM (141 GB) COMFORTABLE 32.2 / 140.4 GiB 289.1 tok/s 0.19s 32k Simulate →
Cloud NVIDIA H100 SXM (80 GB) COMFORTABLE 32.2 / 79.4 GiB 201.8 tok/s 0.19s 32k Simulate →
Cloud NVIDIA A100 SXM (80 GB) COMFORTABLE 32.2 / 79.4 GiB 119.9 tok/s 0.55s 32k Simulate →
NVIDIA RTX PRO 6000 Blackwell (96 GB) COMFORTABLE 32.2 / 95.0 GiB 107.9 tok/s 0.68s 32k Simulate →
Cloud NVIDIA L40S (48 GB) COMFORTABLE 32.2 / 47.4 GiB 50.8 tok/s 0.50s 32k Simulate →
Apple Mac Studio M3 Ultra (256 GB) COMFORTABLE 32.0 / 199.7 GiB 45.8 tok/s 3.31s 32k Simulate →
Apple Mac Studio M3 Ultra (512 GB) COMFORTABLE 32.0 / 399.4 GiB 45.8 tok/s 3.31s 32k Simulate →
2x NVIDIA RTX 3090 Rig (48 GB) COMFORTABLE 32.2 / 46.6 GiB 45.1 tok/s 3.11s 32k Simulate →
Apple Mac Studio M2 Ultra (192 GB) COMFORTABLE 32.0 / 149.8 GiB 44.8 tok/s 3.65s 32k Simulate →
Apple Mac Studio M4 Max (64 GB) COMFORTABLE 32.0 / 49.9 GiB 30.1 tok/s 5.02s 32k Simulate →
Apple Mac Studio M4 Max (128 GB) COMFORTABLE 32.0 / 99.8 GiB 30.1 tok/s 5.02s 32k Simulate →
Apple MacBook Pro M3 Max (64 GB) COMFORTABLE 32.0 / 49.9 GiB 21.8 tok/s 6.72s 32k Simulate →
Apple MacBook Pro M3 Max (128 GB) COMFORTABLE 32.0 / 99.8 GiB 21.8 tok/s 6.72s 32k Simulate →
Apple Mac Mini M4 Pro (48 GB) COMFORTABLE 32.0 / 37.4 GiB 14.5 tok/s 10.35s 32k Simulate →
Apple Mac Mini M4 Pro (64 GB) COMFORTABLE 32.0 / 49.9 GiB 14.5 tok/s 10.35s 32k Simulate →
Ryzen AI Max+ 395 Strix Halo (128 GB) COMFORTABLE 32.0 / 96.0 GiB 13.6 tok/s 3.74s 32k Simulate →
Ryzen AI Max+ 395 Strix Halo (64 GB) COMFORTABLE 32.0 / 48.0 GiB 13.6 tok/s 3.74s 32k Simulate →
Ryzen AI 9 HX 370 Mini-PC (64 GB) COMFORTABLE 32.0 / 48.0 GiB 6.0 tok/s 10.67s 32k Simulate →
NVIDIA RTX 5090 (32 GB) OOM 32.2 / 31.0 GiB OOM — 22k Simulate →
NVIDIA RTX 4090 (24 GB) OOM 32.2 / 23.0 GiB OOM — OOM Simulate →
NVIDIA RTX 5080 (16 GB) OOM 32.2 / 15.0 GiB OOM — OOM Simulate →
NVIDIA RTX 3090 (24 GB Used) OOM 32.2 / 23.0 GiB OOM — OOM Simulate →
NVIDIA RTX 5070 Ti (16 GB) OOM 32.2 / 15.0 GiB OOM — OOM Simulate →
AMD Radeon RX 7900 XTX (24 GB) OOM 32.2 / 23.0 GiB OOM — OOM Simulate →
NVIDIA RTX 5060 Ti (16 GB) OOM 32.2 / 15.0 GiB OOM — OOM Simulate →
NVIDIA RTX 3060 (12 GB) OOM 32.2 / 11.0 GiB OOM — OOM Simulate →
Apple Mac Mini M4 (16 GB) OOM 32.0 / 10.0 GiB OOM — OOM Simulate →
Apple Mac Mini M4 (24 GB) OOM 32.0 / 18.0 GiB OOM — OOM Simulate →

Interactive Mixtral 8x7B Instruct Simulator

46.7B (12.9B active) · GQA
1792 GB/s · 250 TFLOPS
3. Weight Quantization 4.85 bpw
4. KV Cache
32,768 tok
Compute Roofline
COMFORTABLE FIT Memory-Bandwidth Bound
Max Safe Ctx: 32k
Memory Allocation Footprint 32.21 / 95.00 GiB usable
Weights: 26.89 GiB KV Cache: 4.00 GiB Overhead: 1.31 GiB Headroom: 62.79 GiB
Decode Speed
107.9
tok/s (batch=1)
Prefill Speed
6326
prompt tok/s
TTFT Latency
0.68s
for 4,096 tok
Active Params
12.9B
of 46.7B total
llama.cpp Server Command
llama-server -hf mistralai/Mixtral-8x7B-Instruct-v0.1:Q4_K_M -ngl 99 -fa on -c 32768 --port 8080
Context KV Cache Total VRAM Decode Status
4k 0.50 GiB 28.43 GiB 155.6 tok/s COMFORTABLE
8k 1.00 GiB 29.21 GiB 146.4 tok/s COMFORTABLE
16k 2.00 GiB 30.21 GiB 130.8 tok/s COMFORTABLE
32k 4.00 GiB 32.21 GiB 107.9 tok/s COMFORTABLE

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

USE SERVERLESS API
Own Hardware/mo
$163.44
40.8h active + power
Cloud GPU/mo
$86.80
@$1.85/hr spot/pod
Serverless API/mo
$15.60
Payback: 984.5 mo

Engineering FAQ — Mixtral 8x7B Instruct

How much VRAM does Mixtral 8x7B Instruct require in Q4_K_M?

Mixtral 8x7B Instruct weights occupy 26.89 GiB in Q4_K_M. Including 32k FP16 KV cache and runtime buffers, total memory is 32.21 GiB.

What is the cheapest local hardware that runs Mixtral 8x7B Instruct?

NVIDIA RTX PRO 6000 Blackwell (96 GB) (96 GB) runs Mixtral 8x7B Instruct Q4_K_M at ~107.9 tok/s decode and 0.68s TTFT.

How does Mixtral 8x7B Instruct scale KV cache at long context?

Mixtral 8x7B Instruct uses GQA with 8 KV heads across 32 layers (128 head_dim).