Will It Run AI

DeepSeekDeepSeek

DeepSeek V4 Pro

Frontera
huggingfaceHuggingFace
5.9MDescargas4.5KMe gustaApr 2026Publicado1.0M tokensContextoMITLicencia100 ExcepcionalCalidad

DeepSeek V4 Pro (1600B parameters) requires approximately 865.4 GB of VRAM with NVFP4 quantization. As a Mixture of Experts model with 49B 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 996 GB of VRAM.

Comenzar

— copia y pega para ejecutar en local

Copy-paste commands to run DeepSeek V4 Pro on your machine.

Run

docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \ --hf-repo "deepseek-ai/DeepSeek-V4-Pro" \ --hf-file "DeepSeek-V4-Pro-NVFP4.gguf" \ -c 4096 -ngl 99

Quick specs

Parameters1600B (49B active)
Architecturemoe (MoE)
Context1.0M tokens
Modalitytext
Min RAM624 GB
Rec. RAM896 GB (NVFP4)
LicenseMIT
FamilyDeepSeek
✓ Code✓ Reasoning

About this model

DeepSeek V4 Pro is a 1.6T-parameter sparse MoE (49B active, 384 routed + 1 shared expert) built for million-token agentic reasoning. Experts ship natively in FP4, so the real on-disk footprint is roughly 862 GB (FP4 experts + FP8 attention) rather than the trillion-scale FP16 size — but it is still a server/workstation deployment: realistic local use targets 8x 80GB GPUs or 1 TB+ unified memory, and at long Think Max contexts the KV cache dominates.

  • •1.6T total / 49B active sparse MoE — 384 routed + 1 shared expert
  • •Native FP4 experts: ~862 GB on disk, not trillion-scale FP16
  • •1M-token context for million-token agent workflows
  • •Server/workstation class — use distills or the Flash variant for local

Modelos relacionados

Tu hardware

Detectando...

Opciones de cuantización

Estimaciones de VRAM por nivel de cuantización

No hardware detected — fit column shows raw VRAM estimates

QuantBitsVRAMQualityFit
Q2_K
2
624.0 GB
Low—
Q3_K_S
3
784.0 GB
Low—
NVFP4
4
896.0 GB
Medium—
Q4_K_M
4
976.0 GB
Medium—
Q5_K_M
5
1152.0 GB
High—
Q6_K
6
1312.0 GB
High—
Q8_0
8
1712.0 GB
Very High—
F16
16
3280.0 GB
Maximum—

Quality benchmarks

DeepSeek V4 Pro benchmark scores

Benchmark verified

Coding

SWE-bench Verified80.6%
HumanEval+—
Aider Polyglot—
LiveCodeBench93.5%

Reasoning

MMLU-Pro87.5%
GPQA Diamond—
MATH-500—
ARC Challenge—

Source: vendor-reported · 2026-04-24

Compatibilidad de hardware

Estimaciones de encaje en todo el hardware

Abrir calculadora

Computing compatibility...

Desglose de memoria

Reference: RTX 2060 6GB

Weights862.0 GB
KV Cache1.9 GB
Runtime0.9 GB
Headroom0.6 GB

Preguntas frecuentes

FAQ — DeepSeek V4 Pro

Ver también

Guía de cuantizaciónMetodología de puntuaciónAbrir calculadora