👁 Mistral
Mistral
Mixtral 8x22B
Current
50.3KDownloads753LikesApr 2024Released66K tokensContextApache 2.0License34 BasicQuality
Mixtral 8x22B (141B parameters) requires approximately 90.9 GB of VRAM with Q4_K_M quantization. As a Mixture of Experts model with 39B active parameters, it uses less memory than its total parameter count suggests. For the best balance of quality and speed, we recommend hardware with at least 105 GB of VRAM.
Get started
— copy & paste to run locallyCopy-paste commands to run Mixtral 8x22B on your machine.
Run
ollama run mixtral:8x22bQuick specs
Parameters141B (39B active)
Architecturemoe (MoE)
Context66K tokens
Modalitytext
Min RAM55 GB
Rec. RAM86 GB (Q4_K_M)
LicenseApache 2.0
FamilyMixtral
✓ Chat✓ Reasoning
About this model
- •[AVAILABLE_TOOLS]
- •[/AVAILABLE_TOOLS]
Related models
Your hardware
Detecting...
Quick picks
Best budgetB
Mac Studio M3 Ultra 256GB~$6,999 — 14 tok/s
Best overallA
NVIDIA H200 141GB~$30,000 — 97 tok/sBest hardware
Top picks for Mixtral 8x22B
Run this model
Quantization options
VRAM estimates by quant level
No hardware detected — fit column shows raw VRAM estimates
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 55.0 GB | Low | — |
Q3_K_S | 3 | 69.1 GB | Low | — |
NVFP4 | 4 | 79.0 GB | Medium | — |
Q4_K_M | 4 | 86.0 GB | Medium | — |
Q5_K_M | 5 | 101.5 GB | High | — |
Q6_K | 6 | 115.6 GB | High | — |
Q8_0 | 8 | 150.9 GB | Very High | — |
F16 | 16 | 289.0 GB | Maximum | — |
Quality benchmarks
Mixtral 8x22B benchmark scores
Coding
SWE-bench Verified—
HumanEval+78.6%
Aider Polyglot—
LiveCodeBench—
Reasoning
MMLU-Pro38.7%
GPQA Diamond16.4%
MATH-50018.7%
ARC Challenge—
General
Chatbot Arena—
IFEval71.8%
Source: official · 2024-04-16
Hardware compatibility
Fit estimates across all hardware
Computing compatibility...
Memory breakdown
Reference: RTX 2060 6GB
Weights86.0 GB
KV Cache3.4 GB
Runtime0.9 GB
Headroom0.6 GB
Frequently asked questions
FAQ — Mixtral 8x22B
See also