Model Comparison

DeepSeek-V3.2 (Thinking) vs DeepSeek-V3 0324

DeepSeek-V3.2 (Thinking) significantly outperforms across most benchmarks. DeepSeek-V3.2 (Thinking) is 1.6x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

DeepSeek-V3.2 (Thinking) outperforms in 3 benchmarks (GPQA, LiveCodeBench, MMLU-Pro), while DeepSeek-V3 0324 is better at 0 benchmarks.

DeepSeek-V3.2 (Thinking) significantly outperforms across most benchmarks.

Sun May 24 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

DeepSeek-V3.2 (Thinking) costs less

For input processing, DeepSeek-V3.2 (Thinking) ($0.28/1M tokens) costs the same as DeepSeek-V3 0324 ($0.28/1M tokens).

For output processing, DeepSeek-V3.2 (Thinking) ($0.42/1M tokens) is 2.7x cheaper than DeepSeek-V3 0324 ($1.14/1M tokens).

In conclusion, DeepSeek-V3 0324 is more expensive than DeepSeek-V3.2 (Thinking).*

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

Lowest available price from all providers
Sun May 24 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2 (Thinking)
Input tokens$0.28
Output tokens$0.42
Best providerDeepSeek
DeepSeek
DeepSeek-V3 0324
Input tokens$0.28
Output tokens$1.14
Best providerNovita
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

14.0B diff

DeepSeek-V3.2 (Thinking) has 14.0B more parameters than DeepSeek-V3 0324, making it 2.1% larger.

DeepSeek
DeepSeek-V3.2 (Thinking)
685.0Bparameters
DeepSeek
DeepSeek-V3 0324
671.0Bparameters
685.0B
DeepSeek-V3.2 (Thinking)
671.0B
DeepSeek-V3 0324

Context Window

Maximum input and output token capacity

DeepSeek-V3 0324 accepts 163,840 input tokens compared to DeepSeek-V3.2 (Thinking)'s 131,072 tokens. DeepSeek-V3 0324 can generate longer responses up to 163,840 tokens, while DeepSeek-V3.2 (Thinking) is limited to 65,536 tokens.

DeepSeek
DeepSeek-V3.2 (Thinking)
Input131,072 tokens
Output65,536 tokens
DeepSeek
DeepSeek-V3 0324
Input163,840 tokens
Output163,840 tokens
Sun May 24 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3.2 (Thinking) is licensed under MIT, while DeepSeek-V3 0324 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 (Thinking)

MIT

Open weights

DeepSeek-V3 0324

MIT + Model License (Commercial use allowed)

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2 (Thinking) was released on 2025-12-01, while DeepSeek-V3 0324 was released on 2025-03-25.

DeepSeek-V3.2 (Thinking) is 8 months newer than DeepSeek-V3 0324.

DeepSeek-V3.2 (Thinking)

Dec 1, 2025

5 months ago

8mo newer
DeepSeek-V3 0324

Mar 25, 2025

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 (Thinking) is available from DeepSeek. DeepSeek-V3 0324 is available from Novita.

DeepSeek-V3.2 (Thinking)

deepseek logo
DeepSeek
Input Price:Input: $0.28/1MOutput Price:Output: $0.42/1M

DeepSeek-V3 0324

novita logo
Novita
Input Price:Input: $0.28/1MOutput Price:Output: $1.14/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

DeepSeek
Less expensive output tokens
Higher GPQA score (82.4% vs 68.4%)
Higher LiveCodeBench score (83.3% vs 49.2%)
Higher MMLU-Pro score (85.0% vs 81.2%)
DeepSeek
Larger context window (163,840 tokens)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.2 (Thinking)
DeepSeek
DeepSeek-V3 0324

FAQ

Common questions about DeepSeek-V3.2 (Thinking) vs DeepSeek-V3 0324.

Which is better, DeepSeek-V3.2 (Thinking) or DeepSeek-V3 0324?

DeepSeek-V3.2 (Thinking) significantly outperforms across most benchmarks. DeepSeek-V3.2 (Thinking) is made by DeepSeek and DeepSeek-V3 0324 is made by DeepSeek. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek-V3.2 (Thinking) compare to DeepSeek-V3 0324 in benchmarks?

DeepSeek-V3.2 (Thinking) scores AIME 2025: 93.1%, HMMT 2025: 90.2%, MMLU-Pro: 85.0%, LiveCodeBench: 83.3%, GPQA: 82.4%. DeepSeek-V3 0324 scores MATH-500: 94.0%, MMLU-Pro: 81.2%, GPQA: 68.4%, AIME 2024: 59.4%, LiveCodeBench: 49.2%.

Is DeepSeek-V3.2 (Thinking) cheaper than DeepSeek-V3 0324?

Both models cost $0.28 per million input tokens.

What are the context window sizes for DeepSeek-V3.2 (Thinking) and DeepSeek-V3 0324?

DeepSeek-V3.2 (Thinking) supports 131K tokens and DeepSeek-V3 0324 supports 164K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V3.2 (Thinking) and DeepSeek-V3 0324?

Key differences include context window (131K vs 164K), licensing (MIT vs MIT + Model License (Commercial use allowed)). See the full comparison above for benchmark-by-benchmark results.