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  1. Home
  2. Models
  3. Redhatai Llama 3.2 90B Vision Instruct FP8 Dynamic
  4. Requirements
  5. Q3_K_S
Q3_K_S33GB VRAM minimum

Redhatai Llama 3.2 90B Vision Instruct FP8 Dynamic Q3_K_S VRAM Requirements

This page answers Redhatai Llama 3.2 90B Vision Instruct FP8 Dynamic q3_k_s quantization queries with explicit calculations from our model requirement dataset and compatibility speed table.

Short answer
Direct requirement summary for Redhatai Llama 3.2 90B Vision Instruct FP8 Dynamic Q3_K_S

Short answer: Redhatai Llama 3.2 90B Vision Instruct FP8 Dynamic typically needs around 33GB VRAM at Q3_K_S, and 40GB is safer for smoother usage.

Minimum VRAM
33GB
Recommended VRAM
40GB
Target quantization
Q3_K_S
Requirement Snapshot
Current quantization-specific requirement breakdown
Selected quantizationQ3_K_S
Minimum VRAM33GB
Q4 baseline45GB
Q8 baseline90GB
FP16 baseline180GB
Methodology
No hand-wavy numbers

Estimated from Q4 using a 28% memory reduction assumption for Q3_K_S.

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 Redhatai Llama 3.2 90B Vision Instruct FP8 Dynamic? →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 Redhatai Llama 3.2 90B Vision Instruct FP8 Dynamic? →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 Redhatai Llama 3.2 90B Vision Instruct FP8 Dynamic? →Buy options for NVIDIA H100 SXM5 80GB →
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Compare other quantization tiers for Redhatai Llama 3.2 90B Vision Instruct FP8 Dynamic

Q4 requirementsQ4_K_M requirementsQ5_K_M requirementsQ8 requirementsFP16 requirements

Best GPUs for Redhatai Llama 3.2 90B Vision Instruct FP8 Dynamic (Q3_K_S)

GPUVRAMQuantizationSpeedCompatibilityBuy
AMD Instinct MI300X192GBQ4153 tok/sView full compatibilityBuy options
NVIDIA H200 SXM 141GB141GBQ4138 tok/sView full compatibilityBuy options
NVIDIA H100 SXM5 80GB80GBQ499 tok/sView full compatibilityBuy options
AMD Instinct MI250X128GBQ496 tok/sView full compatibilityBuy options
NVIDIA H100 PCIe 80GB80GBQ463 tok/sView full compatibilityBuy options
RTX 509032GBQ460 tok/sView full compatibilityBuy options
NVIDIA A100 80GB SXM480GBQ458 tok/sView full compatibilityBuy options
AMD Instinct MI21064GBQ448 tok/sView full compatibilityBuy options
NVIDIA A100 40GB PCIe40GBQ445 tok/sView full compatibilityBuy options
RTX 409024GBQ436 tok/sView full compatibilityBuy options
NVIDIA RTX 6000 Ada48GBQ436 tok/sView full compatibilityBuy options
NVIDIA L4048GBQ433 tok/sView full compatibilityBuy options
Back to Redhatai Llama 3.2 90B Vision Instruct FP8 Dynamic model pageFull hardware requirementsBest GPU guidesPrebuilt systemsLocal AI build guides

VRAM requirements FAQ

How much VRAM does Redhatai Llama 3.2 90B Vision Instruct FP8 Dynamic need at Q3_K_S?

Redhatai Llama 3.2 90B Vision Instruct FP8 Dynamic at Q3_K_S is estimated to require about 33GB VRAM minimum, with 40GB recommended for smoother operation.

Which GPUs can run Redhatai Llama 3.2 90B Vision Instruct FP8 Dynamic Q3_K_S?

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 Q3_K_S or a different quantization for Redhatai Llama 3.2 90B Vision Instruct FP8 Dynamic?

Q3_K_S is a balance point between memory usage and quality. If your GPU is below 33GB, consider lower-bit quantization; if you have extra VRAM, compare Q8/FP16 options for quality-sensitive workloads.