L
localai.computer
ModelsGPUsSystemsBuildsOpenClawMethodology

Resources

  • Methodology
  • Submit Benchmark
  • About

Browse

  • AI Models
  • GPUs
  • PC Builds
  • AI News

Guides

  • OpenClaw Guide
  • How-To Guides

Legal

  • Privacy
  • Terms
  • Contact

© 2026 localai.computer. Hardware recommendations for running AI models locally.

ℹ️We earn from qualifying purchases through affiliate links at no extra cost to you. This supports our free content and research.

  1. Home
  2. Models
  3. Xiaomimimo Mimo V2 Flash
  4. Requirements
  5. Q5_K_M
Q5_K_M2GB VRAM minimum

Xiaomimimo Mimo V2 Flash Q5_K_M VRAM Requirements

This page answers Xiaomimimo Mimo V2 Flash q5_k_m quantization queries with explicit calculations from our model requirement dataset and compatibility speed table.

Short answer
Direct requirement summary for Xiaomimimo Mimo V2 Flash Q5_K_M

Short answer: Xiaomimimo Mimo V2 Flash typically needs around 2GB VRAM at Q5_K_M, and 3GB is safer for smoother usage.

Minimum VRAM
2GB
Recommended VRAM
3GB
Target quantization
Q5_K_M
Requirement Snapshot
Current quantization-specific requirement breakdown
Selected quantizationQ5_K_M
Minimum VRAM2GB
Q4 baseline1GB
Q8 baseline2GB
FP16 baseline4GB
Methodology
No hand-wavy numbers

Estimated from Q4 and Q8 requirement bounds using midpoint interpolation.

Throughput data below uses available compatibility measurements/estimates and is sorted by tokens per second for this model.

Need general guidance? Review full methodology.

Next steps for this requirement

AMD Instinct MI300X
Check full compatibility details and speed context for this model.
Can AMD Instinct MI300X run Xiaomimimo Mimo V2 Flash? →Buy options for AMD Instinct MI300X →
NVIDIA H200 SXM 141GB
Check full compatibility details and speed context for this model.
Can NVIDIA H200 SXM 141GB run Xiaomimimo Mimo V2 Flash? →Buy options for NVIDIA H200 SXM 141GB →
NVIDIA H100 SXM5 80GB
Check full compatibility details and speed context for this model.
Can NVIDIA H100 SXM5 80GB run Xiaomimimo Mimo V2 Flash? →Buy options for NVIDIA H100 SXM5 80GB →
Need GPU recommendations?
Compare curated best GPU guides by budget and workload.
Browse best GPU guides →
Need a complete build?
Use proven local AI build recipes if you are planning a fresh hardware setup.
Browse local AI builds →
Prefer prebuilt systems?
Compare ready-to-buy systems if you want faster deployment.
Compare prebuilt systems →

Compare other quantization tiers for Xiaomimimo Mimo V2 Flash

Q4 requirementsQ4_K_M requirementsQ8 requirementsFP16 requirements

Best GPUs for Xiaomimimo Mimo V2 Flash (Q5_K_M)

GPUVRAMQuantizationSpeedCompatibilityBuy
AMD Instinct MI300X192GBQ4916 tok/sView full compatibilityBuy options
NVIDIA H200 SXM 141GB141GBQ4827 tok/sView full compatibilityBuy options
NVIDIA H100 SXM5 80GB80GBQ4594 tok/sView full compatibilityBuy options
AMD Instinct MI250X128GBQ4573 tok/sView full compatibilityBuy options
NVIDIA H100 PCIe 80GB80GBQ4377 tok/sView full compatibilityBuy options
RTX 509032GBQ4360 tok/sView full compatibilityBuy options
NVIDIA A100 80GB SXM480GBQ4350 tok/sView full compatibilityBuy options
AMD Instinct MI21064GBQ4285 tok/sView full compatibilityBuy options
NVIDIA A100 40GB PCIe40GBQ4273 tok/sView full compatibilityBuy options
RTX 409024GBQ4216 tok/sView full compatibilityBuy options
NVIDIA RTX 6000 Ada48GBQ4214 tok/sView full compatibilityBuy options
NVIDIA L4048GBQ4199 tok/sView full compatibilityBuy options
Back to Xiaomimimo Mimo V2 Flash model pageFull hardware requirementsBest GPU guidesPrebuilt systemsLocal AI build guides

VRAM requirements FAQ

How much VRAM does Xiaomimimo Mimo V2 Flash need at Q5_K_M?

Xiaomimimo Mimo V2 Flash at Q5_K_M is estimated to require about 2GB VRAM minimum, with 3GB recommended for smoother operation.

Which GPUs can run Xiaomimimo Mimo V2 Flash Q5_K_M?

Start with AMD Instinct MI300X, NVIDIA H200 SXM 141GB, NVIDIA H100 SXM5 80GB and review each compatibility page for full speed and fit details.

Should I use Q5_K_M or a different quantization for Xiaomimimo Mimo V2 Flash?

Q5_K_M is a balance point between memory usage and quality. If your GPU is below 2GB, consider lower-bit quantization; if you have extra VRAM, compare Q8/FP16 options for quality-sensitive workloads.