← Back to the A-Z glossary
Model · DeepSeek · 2026

DeepSeek V3.2

DeepSeek V3.2 is the open-weight model from the Chinese lab DeepSeek, released in early 2026. Its performance is very close to GPT-5 on most benchmarks, but at 30x less on the API. When you have a ton of text to process without blowing your budget, this is my first move.

Model 5 min read Updated 2026-05-25
— What it is

DeepSeek V3.2, in plain words

Plainly: it's a model that's nearly on par with the best, whose weights are published for free, and whose API costs a fraction of what GPT or Claude do.

Open-weight like Llama: the weights are published for free, and anyone can run it. But DeepSeek goes further than Meta on price: on their official API, the cache hit (when you re-query content it has already seen) drops to $0.003 per million tokens. It's wild.

Performance: very close to GPT-5 and Claude Sonnet 4.6 on public benchmarks, slightly behind on the really hard reasoning.

What I use it for

  • High-volume pipelines: generating 10,000 summaries, classifying 100,000 comments — DeepSeek cuts my bill by 30x compared to GPT.
  • Cascading drafts: let DeepSeek write 5 versions, pick the best, then ask Claude to polish it. A "low cost + finishing touch" strategy.
  • Consumer apps: a startup that wants to bake in AI without wrecking its margin — DeepSeek is unbeatable on the quality-to-price ratio.
  • Testing a use case: validating an idea without burning $50 in premium tokens.
  • Repetitive tasks: with the cache hit at $0.003, repeated prompts become nearly free.

How it compares

vs GPT-5.5 / Claude Sonnet 4.6: DeepSeek is 20-30x cheaper, with performance ~5-10% behind on the hard benchmarks and on par for everyday tasks. Pick DeepSeek when price comes first, GPT/Claude when raw quality comes first.

vs Llama 4 Maverick: prices are close, DeepSeek is usually a notch above on benchmarks and offers an unbeatable cache hit. Llama has a more mature ecosystem.

vs Qwen 3: another Chinese open-weight model, with prices in the same range. Qwen is better at multilingual work, DeepSeek at code and math.

What it costs

API pricing as of May 25, 2026 (source: platform.deepseek.com/pricing):

  • Input: $0.14 per million tokens
  • Output: $0.28 per million tokens
  • Cache hit: $0.0028 per million tokens (yes, less than three thousandths of a cent per thousand)
  • Model weights: free on Hugging Face

To give you a sense of scale: running 100,000 classified emails through DeepSeek = ~$5. The same volume through GPT-5.5 = ~$150.

My take

I use it for my high-volume pipelines and my cascading drafts. It's not my go-to for conversation, but it's my first move when I need to process a lot for cheap.

What I love: the price, honestly. And the quality stays really decent. The cache hit changes how I design my prompts (I structure them to max out the cache).

What bugs me: the French is less fluent than Sonnet's, and moderation is stricter on certain sensitive topics (Chinese politics, Tibet, and so on). For professional French use cases, I always double-check the output.

Quick questions

Does DeepSeek send my data to China?

If you use the official DeepSeek API or app, your data goes through servers in China. If you run the open weights yourself (on Hugging Face, Fireworks AI, or your own machine), nothing leaves your setup — that's the whole point of open-weight.

Is DeepSeek really open-source?

Open-weight (free weights) under an MIT license, which is more permissive than Llama.

Is there a consumer app?

Yes, chat.deepseek.com, free with sign-up.

Verified on 2026-05-25 · next review 2026-11-25

Prices and specs verified on the official DeepSeek pricing page. Personal use: automated pipelines 2-3 times a week via Fireworks AI.

Want to keep going in order?

Head back to the full glossary, search a word, then open only the pages that deserve more than a short definition.

Open the AI glossary