DeepSeek-V3.2 (Non-thinking) vs DeepSeek-V3 Comparison

Comparing DeepSeek-V3.2 (Non-thinking) and DeepSeek-V3 across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V3.2 (Non-thinking) and DeepSeek-V3 don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

DeepSeek-V3.2 (Non-thinking) costs less

For input processing, DeepSeek-V3.2 (Non-thinking) ($0.28/1M tokens) is 1.0x more expensive than DeepSeek-V3 ($0.27/1M tokens).

For output processing, DeepSeek-V3.2 (Non-thinking) ($0.42/1M tokens) is 2.6x cheaper than DeepSeek-V3 ($1.10/1M tokens).

In conclusion, DeepSeek-V3 is more expensive than DeepSeek-V3.2 (Non-thinking).*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers

Sat Mar 14 2026 • llm-stats.com

DeepSeek-V3.2 (Non-thinking)

Input tokens$0.28

Output tokens$0.42

Best providerDeepSeek

DeepSeek-V3

Input tokens$0.27

Output tokens$1.10

Best providerDeepSeek

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Model Size

Parameter count comparison

14.0B diff

DeepSeek-V3.2 (Non-thinking) has 14.0B more parameters than DeepSeek-V3, making it 2.1% larger.

DeepSeek-V3.2 (Non-thinking)

685.0Bparameters

DeepSeek-V3

671.0Bparameters

685.0B

DeepSeek-V3.2 (Non-thinking)

671.0B

DeepSeek-V3

Context Window

Maximum input and output token capacity

Both models have the same input context window of 131,072 tokens. DeepSeek-V3 can generate longer responses up to 131,072 tokens, while DeepSeek-V3.2 (Non-thinking) is limited to 8,192 tokens.

DeepSeek-V3.2 (Non-thinking)

Input131,072 tokens

Output8,192 tokens

DeepSeek-V3

Input131,072 tokens

Output131,072 tokens

Sat Mar 14 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3.2 (Non-thinking) is licensed under MIT, while DeepSeek-V3 uses MIT + Model License (Commercial use allowed).

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek-V3.2 (Non-thinking)

MIT

Open weights

DeepSeek-V3

MIT + Model License (Commercial use allowed)

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2 (Non-thinking) was released on 2025-12-01, while DeepSeek-V3 was released on 2024-12-25.

DeepSeek-V3.2 (Non-thinking) is 11 months newer than DeepSeek-V3.

DeepSeek-V3.2 (Non-thinking)

Dec 1, 2025

3 months ago

11mo newer

DeepSeek-V3

Dec 25, 2024

1.2 years ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

DeepSeek-V3.2 (Non-thinking) is available from DeepSeek. DeepSeek-V3 is available from DeepSeek. The availability of providers can affect quality of the model and reliability.