Can you run Mistral Large 2411 locally?
Mistral family · · 122.6B parameters · Hugging Face model card
Mistral Large 2411 is a 122.6B-parameter model open-weight model with a 131,072-token context window, usable locally with roughly 96 GB of memory at Q4-class quantization (calculated; measured speeds vary by hardware).
Minimum: 96 GB+ memory (Q4_K_M, calculated) · Recommended: 96 GB+ memory for full context (Q4_K_M, calculated)
How much VRAM does Mistral Large 2411 need at each quantization?
Mistral Large 2411 needs 82.4 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 | 73.6 GB | 82.4 GB | 92.7 GB |
| Q5_K_M | 5.7 | 87.4 GB | 97.6 GB | 107.9 GB |
| Q6_K | 6.6 | 101.2 GB | 112.8 GB | 123.1 GB |
| Q8_0 | 8.5 | 130.3 GB | 144.8 GB | 155.1 GB |
| FP16 | 16 | 245.2 GB | 271.2 GB | 281.6 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 (88 layers, 8 KV heads, 128 head dim). Source: HF-verified 2026-09-12 via api (params=122.61B ctx=131072 license=other); VRAM figures are documented calculations, not measurements
Which GPUs can run Mistral Large 2411 locally?
At Q4_K_M with a 4k context, Mistral Large 2411 needs 82.4 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 Mistral Large 2411 comfortably (25%+ VRAM headroom)
| GPU | VRAM | Bandwidth | Type | |
|---|---|---|---|---|
| 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 MI355X | 288 GB | 8000 GB/s | Data Center GPU | |
| NVIDIA B300 (Blackwell Ultra) | 288 GB | 8000 GB/s | Data Center GPU |
Minimum GPUs that fit Mistral Large 2411 at Q4_K_M
These GPUs hold the model but leave little headroom — keep contexts short.
| GPU | VRAM | Bandwidth | Type | |
|---|---|---|---|---|
| NVIDIA RTX PRO 6000 Blackwell | 96 GB | 1792 GB/s | Pro GPU | Check price |
Needs 2+ GPUs to run Mistral Large 2411
One of these cards is too small on its own, but a pair (tensor or pipeline parallel, ~90% efficiency) covers the 82.4 GB requirement. See our multi-GPU guide for setup.
| GPU | VRAM | Bandwidth | Type | |
|---|---|---|---|---|
| AMD Radeon Pro W7900 | 48 GB ×2 | 864 GB/s | Pro GPU | Check price |
| NVIDIA RTX PRO 5000 Blackwell | 48 GB ×2 | 1344 GB/s | Pro GPU | |
| RTX 6000 Ada | 48 GB ×2 | 960 GB/s | Pro GPU | Check price |
| RTX A6000 | 48 GB ×2 | 768 GB/s | Pro GPU | Check price |
| H100 SXM | 80 GB ×2 | 3350 GB/s | Data Center GPU | |
| NVIDIA A100 80GB SXM | 80 GB ×2 | 2039 GB/s | Data Center GPU | |
| NVIDIA H100 PCIe 80GB | 80 GB ×2 | 2039 GB/s | Data Center GPU |
Can a Mac run Mistral Large 2411?
Yes — these Apple Silicon machines fit Mistral Large 2411 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 M3 Max | 128 GB | 96 GB | 400 GB/s |
| M4 Max (MacBook Pro) | 128 GB | 96 GB | 546 GB/s |
| M3 Ultra (Mac Studio) | 512 GB | 384 GB | 819 GB/s |
Can Mistral Large 2411 run on mini PCs, Jetson, or NPU devices?
These edge and NPU devices from our database have enough memory for Mistral Large 2411 at Q4_K_M. Their memory bandwidth is far below discrete GPUs, so expect a fraction of desktop generation speed.
| Device | Memory | Bandwidth | Type |
|---|---|---|---|
| AMD Ryzen AI 9 HX 370 (Strix Point) | 96 GB | 120 GB/s | NPU Chip |
Which pre-built systems can run Mistral Large 2411?
These mini PCs and workstations from our database fit Mistral Large 2411 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.
| System | Type | Memory | Usable for AI | Bandwidth | GPUs |
|---|---|---|---|---|---|
| BOXX APEXX 8R (1x RTX PRO 6000 Blackwell) | Workstation | 96 GB | 96 GB | 1792 GB/s | 1 |
| GEEKOM A9 Mega AI Workstation | Workstation | 128 GB | 96 GB | — | 1 |
| NOVATECH RTX PRO 6000 AI Workstation | Workstation | 96 GB | 96 GB | — | 1 |
| System76 Thelio Major (1x RTX PRO 6000 Blackwell) | Workstation | 96 GB | 96 GB | 1792 GB/s | 1 |
| System76 Thelio Major (2x RTX 6000 Ada) | Workstation | 96 GB | 96 GB | 960 GB/s | 2 |
| Lenovo ThinkStation PGX | Workstation | 128 GB | 115.2 GB | 273 GB/s | 1 |
| NVIDIA DGX Spark | Workstation | 128 GB | 115.2 GB | 273 GB/s | 1 |
| BIZON G3000 G2 (4x RTX 5090) | Workstation | 128 GB | 128 GB | 1792 GB/s | 4 |
| Apple Mac Studio M2 Ultra (192GB) | Workstation | 192 GB | 144 GB | 800 GB/s | 1 |
| HP Z8 Fury G5 (4x RTX 6000 Ada) | Workstation | 192 GB | 192 GB | 960 GB/s | 4 |