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DeepSeekOpen source DeepSeek · China· 2026

DeepSeek V3.2

Strong general open model with competition-grade results.

Modality

Text

Context

Large context

Pricing (per 1M)

Open / self-host

What DeepSeek V3.2 is for

DeepSeek V3.2 is the general-purpose counterpart to R1 — a conventional model built for breadth rather than deliberation, and priced aggressively enough to have moved the market's expectations of what capability should cost.

Its practical importance is as a price anchor. Capability that was premium-tier eighteen months ago is now available at a fraction of the cost, and that shapes what is worth building.

Where it does well

Cost-to-capability is the headline and it is real. For ordinary production work — drafting, summarising, extraction, code generation, structured output — it delivers quality comparable to models several times the price.

It handles code well for a general model, and the open-weights availability means self-hosting is an option if data residency matters more than convenience.

Where it falls short

On the hardest reasoning it trails the leading flagships, and it is not the model to reach for when a wrong answer is expensive. Ecosystem maturity — integrations, tooling, documented prompt patterns — is behind the US labs.

For organisations with constraints on where models may be hosted or where data may be processed, the governance question needs answering before the capability question.

Should you use it?

A strong default for cost-sensitive production work, and worth benchmarking against your current model on your actual tasks — the price difference is large enough that even a modest quality gap may be acceptable. Escalate to a flagship for the small fraction of work where it is not.

Capabilities

General reasoningCodingOpen weights

Pros

  • Very capable open model
  • MIT license
  • Cost-efficient

Cons

  • Consider data-governance for sensitive use

Best for

Open general assistantCost-efficient production

Try a prompt for DeepSeek V3.2

DeepSeek V3.2
Draft a technical explainer on [TOPIC] for beginners, under 200 words.

Other DeepSeek models

Pricing indicative, per 1M tokens, reviewed July 2026.

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