Q82GB VRAM minimum

Deepseek AI Deepseek Coder V2 Lite Instruct Q8 VRAM Requirements

This page answers Deepseek AI Deepseek Coder V2 Lite Instruct q8 quantization queries with explicit calculations from our model requirement dataset and compatibility speed table.

Short answer

Direct requirement summary for Deepseek AI Deepseek Coder V2 Lite Instruct Q8

Short answer: Deepseek AI Deepseek Coder V2 Lite Instruct typically needs around 2GB VRAM at Q8, and 3GB is safer for smoother usage.

Minimum VRAM

2GB

Recommended VRAM

3GB

Target quantization

Requirement Snapshot

Current quantization-specific requirement breakdown

Selected quantizationQ8

Minimum VRAM2GB

Q4 baseline1GB

Q8 baseline2GB

FP16 baseline4GB

Methodology

No hand-wavy numbers

Exact Q8 requirement from model requirement data.

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 Deepseek AI Deepseek Coder V2 Lite Instruct? →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 Deepseek AI Deepseek Coder V2 Lite Instruct? →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 Deepseek AI Deepseek Coder V2 Lite Instruct? →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 Deepseek AI Deepseek Coder V2 Lite Instruct

Q4 requirements Q4_K_M requirements Q5_K_M requirements FP16 requirements

High-demand speed checks for Deepseek AI Deepseek Coder V2 Lite Instruct

deepseek ai deepseek coder v2 lite instruct speed on rtx 4070 ti super1,079 impressions tracked

deepseek ai deepseek coder v2 lite instruct speed on amd instinct mi250x140 impressions tracked

Best GPUs for Deepseek AI Deepseek Coder V2 Lite Instruct (Q8)

GPU	VRAM	Quantization	Speed	Compatibility	Buy
AMD Instinct MI300X	192GB	Q8	801 tok/s	View full compatibility	Buy options
NVIDIA H200 SXM 141GB	141GB	Q8	724 tok/s	View full compatibility	Buy options
NVIDIA H100 SXM5 80GB	80GB	Q8	520 tok/s	View full compatibility	Buy options
AMD Instinct MI250X	128GB	Q8	501 tok/s	View full compatibility	Buy options
NVIDIA H100 PCIe 80GB	80GB	Q8	330 tok/s	View full compatibility	Buy options
RTX 5090	32GB	Q8	315 tok/s	View full compatibility	Buy options
NVIDIA A100 80GB SXM4	80GB	Q8	307 tok/s	View full compatibility	Buy options
AMD Instinct MI210	64GB	Q8	250 tok/s	View full compatibility	Buy options
NVIDIA A100 40GB PCIe	40GB	Q8	239 tok/s	View full compatibility	Buy options
RTX 4090	24GB	Q8	189 tok/s	View full compatibility	Buy options
NVIDIA RTX 6000 Ada	48GB	Q8	187 tok/s	View full compatibility	Buy options
NVIDIA L40	48GB	Q8	174 tok/s	View full compatibility	Buy options

Back to Deepseek AI Deepseek Coder V2 Lite Instruct model page Full hardware requirements Best GPU guides Prebuilt systems Local AI build guides

VRAM requirements FAQ

How much VRAM does Deepseek AI Deepseek Coder V2 Lite Instruct need at Q8?

Deepseek AI Deepseek Coder V2 Lite Instruct at Q8 is estimated to require about 2GB VRAM minimum, with 3GB recommended for smoother operation.

Which GPUs can run Deepseek AI Deepseek Coder V2 Lite Instruct Q8?

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 Q8 or a different quantization for Deepseek AI Deepseek Coder V2 Lite Instruct?

Q8 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.

Q82GB VRAM minimum

Deepseek AI Deepseek Coder V2 Lite Instruct Q8 VRAM Requirements

This page answers Deepseek AI Deepseek Coder V2 Lite Instruct q8 quantization queries with explicit calculations from our model requirement dataset and compatibility speed table.

Short answer

Direct requirement summary for Deepseek AI Deepseek Coder V2 Lite Instruct Q8

Short answer: Deepseek AI Deepseek Coder V2 Lite Instruct typically needs around 2GB VRAM at Q8, and 3GB is safer for smoother usage.

Minimum VRAM

2GB

Recommended VRAM

3GB

Target quantization

Requirement Snapshot

Current quantization-specific requirement breakdown

Selected quantizationQ8

Minimum VRAM2GB

Q4 baseline1GB

Q8 baseline2GB

FP16 baseline4GB

Methodology

No hand-wavy numbers

Exact Q8 requirement from model requirement data.

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 Deepseek AI Deepseek Coder V2 Lite Instruct? →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 Deepseek AI Deepseek Coder V2 Lite Instruct? →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 Deepseek AI Deepseek Coder V2 Lite Instruct? →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 Deepseek AI Deepseek Coder V2 Lite Instruct

Q4 requirements Q4_K_M requirements Q5_K_M requirements FP16 requirements

High-demand speed checks for Deepseek AI Deepseek Coder V2 Lite Instruct

deepseek ai deepseek coder v2 lite instruct speed on rtx 4070 ti super1,079 impressions tracked

deepseek ai deepseek coder v2 lite instruct speed on amd instinct mi250x140 impressions tracked

Best GPUs for Deepseek AI Deepseek Coder V2 Lite Instruct (Q8)

GPU	VRAM	Quantization	Speed	Compatibility	Buy
AMD Instinct MI300X	192GB	Q8	801 tok/s	View full compatibility	Buy options
NVIDIA H200 SXM 141GB	141GB	Q8	724 tok/s	View full compatibility	Buy options
NVIDIA H100 SXM5 80GB	80GB	Q8	520 tok/s	View full compatibility	Buy options
AMD Instinct MI250X	128GB	Q8	501 tok/s	View full compatibility	Buy options
NVIDIA H100 PCIe 80GB	80GB	Q8	330 tok/s	View full compatibility	Buy options
RTX 5090	32GB	Q8	315 tok/s	View full compatibility	Buy options
NVIDIA A100 80GB SXM4	80GB	Q8	307 tok/s	View full compatibility	Buy options
AMD Instinct MI210	64GB	Q8	250 tok/s	View full compatibility	Buy options
NVIDIA A100 40GB PCIe	40GB	Q8	239 tok/s	View full compatibility	Buy options
RTX 4090	24GB	Q8	189 tok/s	View full compatibility	Buy options
NVIDIA RTX 6000 Ada	48GB	Q8	187 tok/s	View full compatibility	Buy options
NVIDIA L40	48GB	Q8	174 tok/s	View full compatibility	Buy options

Back to Deepseek AI Deepseek Coder V2 Lite Instruct model page Full hardware requirements Best GPU guides Prebuilt systems Local AI build guides

VRAM requirements FAQ

How much VRAM does Deepseek AI Deepseek Coder V2 Lite Instruct need at Q8?

Deepseek AI Deepseek Coder V2 Lite Instruct at Q8 is estimated to require about 2GB VRAM minimum, with 3GB recommended for smoother operation.

Which GPUs can run Deepseek AI Deepseek Coder V2 Lite Instruct Q8?

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 Q8 or a different quantization for Deepseek AI Deepseek Coder V2 Lite Instruct?

Q8 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.