DeepSeek V2.5 236B

Current

6.0KDownloads734LikesSep 2024Released131K tokensContextDeepSeekLicense80 StrongQuality

DeepSeek V2.5 236B (236B parameters) requires approximately 204.1 GB of VRAM with Q4_K_M quantization. As a Mixture of Experts model with 21B 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 235 GB of VRAM.

Get started

— copy & paste to run locally

Copy-paste commands to run DeepSeek V2.5 236B on your machine.

Run

docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
 --hf-repo "deepseek-ai/DeepSeek-V2.5" \
 --hf-file "DeepSeek-V2.5-Q4_K_M.gguf" \
 -c 4096 -ngl 99

Quick specs

Parameters236B (21B active)

Architecturemoe (MoE)

Context131K tokens

Modalitytext

Min RAM92 GB

Rec. RAM144 GB (Q4_K_M)

LicenseDeepSeek

FamilyDeepSeek

✓ Chat✓ Reasoning

About this model

DeepSeek-V2.5 is an upgraded version that combines DeepSeek-V2-Chat and DeepSeek-Coder-V2-Instruct. The new model integrates the general and coding abilities of the two previous versions. For model details, please visit DeepSeek-V2 page for more information.

Related models

Your hardware

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Quick picks

Best budgetS

AMD Instinct MI350X 288GB~$8,000 — 109 tok/s

Best hardware

Top picks for DeepSeek V2.5 236B

AMD Instinct MI350X 288GBS

288 GB

AMD Instinct MI325X 256GBS

256 GB

👁 NVIDIA

NVIDIA GB200 192GBA

192 GB

👁 NVIDIA

B100 192GBA

192 GB

AMD Instinct MI300X 192GBA

192 GB

Run this model

DeepSeek V2.5 236B on AMD Instinct MI350X 288GB DeepSeek V2.5 236B on AMD Instinct MI325X 256GB DeepSeek V2.5 236B on NVIDIA GB200 192GB

Quantization options

VRAM estimates by quant level

No hardware detected — fit column shows raw VRAM estimates

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	92.0 GB	Low	—
Q3_K_S	3	115.6 GB	Low	—
NVFP4	4	132.2 GB	Medium	—
Q4_K_M	4	144.0 GB	Medium	—
Q5_K_M	5	169.9 GB	High	—
Q6_K	6	193.5 GB	High	—
Q8_0	8	252.5 GB	Very High	—
F16	16	483.8 GB	Maximum	—

Quality benchmarks