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[ARTICLE · art-52726] src=tokenstead.ai ↗ pub= topic=large-language-models verified=true sentiment=· neutral

DeepSeek V3.2 Exp

DeepSeek released V3.2 Exp, a 685B-parameter mixture-of-experts model with 37B active parameters per token, featuring DeepSeek Sparse Attention (DSA) for fine-grained sparse attention. The model, built on V3.1-Terminus and released under MIT license, was later superseded by V4 within about seven months.

read1 min views1 publishedJul 9, 2026
DeepSeek V3.2 Exp
Image: Tokenstead (auto-discovered)

MoE workstation685B total, ~37B active per token (MoE, 256 routed experts) - shares the V3 backbone. Adds DeepSeek Sparse Attention (DSA): a lightning indexer (FP8, Hadamard dot-product) selects top-2048 tokens per query, then MLA runs only over those - the first fine-grained sparse attention from DeepSeek and the precursor to V4's CSA. Built on V3.1-Terminus. Experimental; superseded by V4 within ~7 months. Open weights under MIT.

coding reasoning

  • 685.0B
  • 128k
  • mit
  • Sep 2025

Scores #

Coding

80

Reasoning

86

General

83

PRICE HISTORY

Inference cost over time #

Data accumulates from the first daily sync - longer ranges populate over time. Prices come from OpenRouter snapshots, not a historical API.

price history...

source & further reading
tokenstead.ai — original article Qwen3.6 35B A3B DeepSeek V4 Flash DeepSeek V3.1 Terminus
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