Can you run Mixtral 8X7B locally?
Mixtral family · Dec 2023 · 46.7B parameters (12.9B activated per token) · Hugging Face model card
Mixtral 8X7B is a mixture-of-experts model with 12.9B active parameters per token and 46.7B total open-weight model with a 32,768-token context window, usable locally with roughly 32 GB of memory at Q4-class quantization (calculated; measured speeds vary by hardware).
Minimum: 32 GB+ memory (Q4_K_M, calculated) · Recommended: 48 GB+ memory for full context (Q4_K_M, calculated)
How much VRAM does Mixtral 8X7B need at each quantization?
Mixtral 8X7B needs 30.8 GB of VRAM at Q4_K_M. The table below lists weights-only size and total VRAM including overhead for each common quantization level with 4k and 32k token contexts.
| Quantization | Bits / weight | Weights only | Total + KV @4k ctx | Total + KV @32k ctx |
|---|---|---|---|---|
| Q4_K_M | 4.8 | 28.0 GB | 30.8 GB | 30.8 GB |
| Q5_K_M | 5.7 | 33.3 GB | 36.6 GB | 36.6 GB |
| Q6_K | 6.6 | 38.5 GB | 42.4 GB | 42.4 GB |
| Q8_0 | 8.5 | 49.6 GB | 54.6 GB | 54.6 GB |
| FP16 | 16 | 93.4 GB | 102.7 GB | 102.7 GB |
Method: weights = parameters × bits-per-weight (Q4_K_M ≈ 4.8, Q5_K_M ≈ 5.7, Q6_K ≈ 6.6, Q8_0 ≈ 8.5, FP16 = 16), plus 10% loading overhead, plus KV cache from the verified architecture config (32 layers, 8 KV heads, head dim). Source: HF-verified 2026-09-12 via api (params=46.7B ctx=32768 license=apache-2.0); VRAM figures are documented calculations, not measurements
Which GPUs can run Mixtral 8X7B locally?
At Q4_K_M with a 4k context, Mixtral 8X7B needs 30.8 GB of VRAM. The lists below are computed live from our GPU database and grouped by how much headroom the card has. Disclosure: CompareAIHardware.com participates in the Amazon Associates program and earns from qualifying purchases through links on this page. Affiliate relationships do not influence our recommendations.
Runs Mixtral 8X7B comfortably (25%+ VRAM headroom)
| GPU | VRAM | Bandwidth | Type | |
|---|---|---|---|---|
| NVIDIA A100 40GB SXMEOL | 40 GB | 1555 GB/s | Data Center GPU | |
| AMD Radeon PRO W7900 Dual Slot | 48 GB | 864 GB/s | Pro GPU | |
| AMD Radeon Pro W7900 | 48 GB | 864 GB/s | Pro GPU | Check price |
| NVIDIA RTX PRO 5000 Blackwell | 48 GB | 1344 GB/s | Pro GPU | |
| RTX 6000 Ada | 48 GB | 960 GB/s | Pro GPU | Check price |
| RTX A6000 | 48 GB | 768 GB/s | Pro GPU | Check price |
| H100 SXM | 80 GB | 3350 GB/s | Data Center GPU | |
| NVIDIA A100 80GB SXM | 80 GB | 2039 GB/s | Data Center GPU | |
| NVIDIA H100 PCIe 80GB | 80 GB | 2039 GB/s | Data Center GPU | |
| NVIDIA RTX PRO 6000 Blackwell | 96 GB | 1792 GB/s | Pro GPU | Check price |
| NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition | 96 GB | — | Pro GPU | |
| NVIDIA RTX PRO 6000 Blackwell Server Edition | 96 GB | — | Pro GPU | |
| H200 SXM | 141 GB | 4800 GB/s | Data Center GPU | |
| AMD Instinct MI300X | 192 GB | 5300 GB/s | Data Center GPU | |
| NVIDIA B200 | 192 GB | 8000 GB/s | Data Center GPU | |
| AMD Instinct MI325X | 256 GB | 6000 GB/s | Data Center GPU | |
| AMD Instinct MI350X | 288 GB | 8000 GB/s | Data Center GPU | |
| AMD Instinct MI355X | 288 GB | 8000 GB/s | Data Center GPU | |
| NVIDIA B300 (Blackwell Ultra) | 288 GB | 8000 GB/s | Data Center GPU | |
| AMD Instinct MI430X | 432 GB | 23300 GB/s | Data Center GPU | |
| AMD Instinct MI455X | 432 GB | 23300 GB/s | Data Center GPU |
Minimum GPUs that fit Mixtral 8X7B at Q4_K_M
These GPUs hold the model but leave little headroom — keep contexts short.
| GPU | VRAM | Bandwidth | Type | |
|---|---|---|---|---|
| AMD Radeon PRO W6800 | 32 GB | 512 GB/s | Pro GPU | |
| AMD Radeon Pro W7800 | 32 GB | 576 GB/s | Pro GPU | Check price |
| GeForce RTX 5090 | 32 GB | 1792 GB/s | Consumer GPU | Check price |
| Intel Arc Pro B65 | 32 GB | 608 GB/s | Pro GPU | |
| Intel Arc Pro B70 | 32 GB | 608 GB/s | Pro GPU | |
| NVIDIA RTX 5000 Ada | 32 GB | 576 GB/s | Pro GPU | Check price |
| NVIDIA RTX PRO 4500 Blackwell | 32 GB | 896 GB/s | Pro GPU | Check price |
Needs 2+ GPUs to run Mixtral 8X7B
One of these cards is too small on its own, but a pair (tensor or pipeline parallel, ~90% efficiency) covers the 30.8 GB requirement. See our multi-GPU guide for setup.
| GPU | VRAM | Bandwidth | Type | |
|---|---|---|---|---|
| Radeon RX 7900 XT | 20 GB ×2 | 800 GB/s | Consumer GPU | Check price |
| GeForce RTX 3090EOL | 24 GB ×2 | 936 GB/s | Consumer GPU | Check price |
| GeForce RTX 3090 TiEOL | 24 GB ×2 | 1008 GB/s | Consumer GPU | Check price |
| GeForce RTX 4090 | 24 GB ×2 | 1008 GB/s | Consumer GPU | Check price |
| Intel Arc Pro B60 | 24 GB ×2 | 456 GB/s | Pro GPU | |
| NVIDIA RTX PRO 4000 Blackwell | 24 GB ×2 | 672 GB/s | Pro GPU | Check price |
| Radeon RX 7900 XTX | 24 GB ×2 | 960 GB/s | Consumer GPU | Check price |
Can a Mac run Mixtral 8X7B?
Yes — these Apple Silicon machines fit Mixtral 8X7B at Q4_K_M, since macOS lets the GPU use about 75% of unified memory. Generation speed is bound by memory bandwidth, so the GB/s column matters as much as capacity.
| Apple Silicon | Unified memory | Usable by GPU (~75%) | Bandwidth |
|---|---|---|---|
| Apple M4 Pro | 64 GB | 48 GB | 273 GB/s |
| Apple M5 Pro | 64 GB | 48 GB | 307 GB/s |
| M5 Pro (Mac mini) | 64 GB | 48 GB | 307 GB/s |
| Apple M3 Max | 128 GB | 96 GB | 400 GB/s |
| Apple M5 Max | 128 GB | 96 GB | 614 GB/s |
| M4 Max (MacBook Pro) | 128 GB | 96 GB | 546 GB/s |
| M5 Max (Mac Studio) | 128 GB | 96 GB | — |
| M5 Ultra (Mac Studio) | 512 GB | 384 GB | 1200 GB/s |
Can Mixtral 8X7B run on mini PCs, Jetson, or NPU devices?
These edge and NPU devices from our database have enough memory for Mixtral 8X7B at Q4_K_M. Their memory bandwidth is far below discrete GPUs, so expect a fraction of desktop generation speed.
| Device | Memory | Bandwidth | Type |
|---|---|---|---|
| Intel Core Ultra 9 288V (Lunar Lake) | 32 GB | 136 GB/s | NPU Chip |
| Jetson AGX Orin 32GB | 32 GB | 204 GB/s | Edge Compute Device |
| Jetson AGX Orin 64GB | 64 GB | 204 GB/s | Edge Compute Device |
| Snapdragon X Elite (X1E-84-100) | 64 GB | 135 GB/s | NPU Chip |
| AMD Ryzen AI 9 HX 370 (Strix Point) | 96 GB | 120 GB/s | NPU Chip |
| NVIDIA Jetson AGX Thor Developer Kit | 128 GB | — | Edge Compute Device |
| NVIDIA RTX Spark (superchip) | 128 GB | — | NPU Chip |
| NVIDIA RTX Spark N1X (desktop superchip) | 128 GB | — | NPU Chip |
Which pre-built systems can run Mixtral 8X7B?
These mini PCs and workstations from our database fit Mixtral 8X7B at Q4_K_M. Usable-memory figures are conservative: Windows shares about half of system RAM with the GPU by default (Linux can expose more), macOS lets Apple Silicon GPUs use about 75% of unified memory, and Linux unified-memory systems such as GB10 expose roughly 90%. Generation speed is bound by memory bandwidth, so compare the GB/s column before buying.