DeepSeek
Language model

DeepSeek V3.2

Open-weight efficiency with sparse attention and rock-bottom pricing.

4.5

At a glance

Provider
DeepSeek
Type
Language model
Context window
163,840 tokens
Released
December 2025
Model ID
deepseek/deepseek-v3.2

Overview

DeepSeek V3.2 is the open-weight model that reset price expectations for the whole industry. Released December 2025, it's a 671B-parameter mixture-of-experts model (37B active per token) with a 128K context window, and its headline innovation is DeepSeek Sparse Attention (DSA) — an efficient attention mechanism that roughly halved long-context API cost overnight while preserving quality.

Beyond efficiency, V3.2 is the first DeepSeek model designed around reasoning with tools and agents rather than treating tool use as an afterthought. It posts strong scores — ~67.8% SWE-bench Verified, ~89.3% AIME 2025, ~85% MMLU-Pro — at a fraction of frontier pricing (often under $0.30 per million tokens), making it the default value pick for cost-sensitive production workloads. It ships under a permissive licence with open weights on Hugging Face.

What it can do

  • DeepSeek Sparse Attention halves long-context cost
  • First DeepSeek built for reasoning-in-tool-use
  • 671B MoE with 37B active parameters
  • Open weights and permissive licence

Pricing: Industry-low — often under $0.30 per million tokens.

Benchmarks

SWE-bench Verified
~67.8%
AIME 2025
~89.3%
Price
From ~$0.14 / 1M tokens

Pros and cons

What works

  • Unbeatable price-per-quality
  • Open weights, self-hostable
  • Strong agentic and reasoning performance

Trade-offs

  • Trails the absolute frontier on the hardest tasks
  • Named in 2026 distillation allegations and facing scrutiny

The verdict

DeepSeek V3.2 is the value champion of 2026 — frontier-adjacent quality at prices nothing else matches, with open weights for self-hosting. If your spend is dominated by a single expensive model and you haven't benchmarked V3.2, you're almost certainly overpaying.

Best for: Cost-sensitive production workloads and self-hosting.

Compare it

Questions

Why is DeepSeek V3.2 so cheap?

Its mixture-of-experts design activates only 37B of 671B parameters per token, and DeepSeek Sparse Attention cuts long-context compute roughly in half — together driving API prices well below frontier models.

Can I self-host DeepSeek V3.2?

Yes. It ships with open weights on Hugging Face under a permissive licence, so you can run it on your own infrastructure.

Further reading

Put DeepSeek V3.2 at the table.

Ask DeepSeek V3.2 and other models the same question side by side, then keep the best answer.