DeepSeek V3.2-Exp — Local AI Model by DeepSeek

作者： Jakub Rusinowski · 最后更新： 2026年7月21日

PREVIEW (June 2026, specs unverified). Experimental sparse-attention snapshot of DeepSeek V3.2 (already present in Hugging Face Transformers). ~685B/37B MoE, MIT, 128K context — a research preview of the V3.2 line (which is itself slated for retirement in favour of V4). Confirm the exact served variant against the Hugging Face model card.

Hardware Requirements

DeepSeek V3.2-Exp 685BMin 414 GB VRAM · Q4_K_M · 128,000 ctx ·

Recommended GPU

The cheapest GPU that runs DeepSeek V3.2-Exp locally (min 414 GB VRAM) is the Apple M3 Ultra (512 GB).

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How to Run Locally

Install Ollama then run: ollama run

Minimum VRAM: 414 GB. For best results use Q4_K_M quantization.

DeepSeek V3.2-Exp — Frequently Asked Questions

How much VRAM does DeepSeek V3.2-Exp need?

DeepSeek V3.2-Exp needs about 414 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: DeepSeek V3.2-Exp 685B (414 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.

Can I run DeepSeek V3.2-Exp on an RTX 4090 (24 GB)?

DeepSeek V3.2-Exp's smallest variant needs about 414 GB, which exceeds a single RTX 4090 (24 GB). Use multiple GPUs, a higher-VRAM card, or Apple Silicon with large unified memory.

What quantization should I use for DeepSeek V3.2-Exp?

Q4_K_M is the best balance of quality and VRAM for DeepSeek V3.2-Exp in most cases. Choose Q8_0 for near-lossless quality if you have spare VRAM, or smaller quants (Q3/Q2) only when memory is tight.

How do I run DeepSeek V3.2-Exp with Ollama?

Install Ollama, then run: ollama run . This downloads DeepSeek V3.2-Exp and starts a local, OpenAI-compatible endpoint — no internet connection is needed after the initial download.