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Model Comparison

DeepSeek-V3.2 (Thinking) vs o1-preview

DeepSeek-V3.2 (Thinking) significantly outperforms across most benchmarks. DeepSeek-V3.2 (Thinking) is 83.3x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

DeepSeek-V3.2 (Thinking) outperforms in 2 benchmarks (GPQA, SWE-Bench Verified), while o1-preview is better at 0 benchmarks.

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

Thu Apr 23 2026 • llm-stats.com

Arena Performance

Human preference votes

CallingBox

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One API for outbound and inbound calls.

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$0.05 /min all-in7 lines of code

Pricing Analysis

Price comparison per million tokens

DeepSeek-V3.2 (Thinking) costs less

For input processing, DeepSeek-V3.2 (Thinking) ($0.28/1M tokens) is 53.6x cheaper than o1-preview ($15.00/1M tokens).

For output processing, DeepSeek-V3.2 (Thinking) ($0.42/1M tokens) is 142.9x cheaper than o1-preview ($60.00/1M tokens).

In conclusion, o1-preview is more expensive than DeepSeek-V3.2 (Thinking).*

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

Lowest available price from all providers
Thu Apr 23 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2 (Thinking)
Input tokens$0.28
Output tokens$0.42
Best providerDeepSeek
OpenAI
o1-preview
Input tokens$15.00
Output tokens$60.00
Best providerOpenAI
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

DeepSeek-V3.2 (Thinking) accepts 131,072 input tokens compared to o1-preview's 128,000 tokens. DeepSeek-V3.2 (Thinking) can generate longer responses up to 65,536 tokens, while o1-preview is limited to 32,768 tokens.

DeepSeek
DeepSeek-V3.2 (Thinking)
Input131,072 tokens
Output65,536 tokens
OpenAI
o1-preview
Input128,000 tokens
Output32,768 tokens
Thu Apr 23 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3.2 (Thinking) is licensed under MIT, while o1-preview uses a proprietary license.

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

DeepSeek-V3.2 (Thinking)

MIT

Open weights

o1-preview

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V3.2 (Thinking) was released on 2025-12-01, while o1-preview was released on 2024-09-12.

DeepSeek-V3.2 (Thinking) is 15 months newer than o1-preview.

DeepSeek-V3.2 (Thinking)

Dec 1, 2025

4 months ago

1.2yr newer
o1-preview

Sep 12, 2024

1.6 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. o1-preview is available from OpenAI, Azure.

DeepSeek-V3.2 (Thinking)

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

o1-preview

openai logo
OpenAI
Input Price:Input: $15.00/1MOutput Price:Output: $60.00/1M
azure logo
Azure
Input Price:Input: $16.50/1MOutput Price:Output: $66.00/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

DeepSeek
Larger context window (131,072 tokens)
Less expensive input tokens
Less expensive output tokens
Has open weights
Higher GPQA score (82.4% vs 73.3%)
Higher SWE-Bench Verified score (73.1% vs 41.3%)
OpenAI

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.2 (Thinking)
OpenAI
o1-preview

FAQ

Common questions about DeepSeek-V3.2 (Thinking) vs o1-preview

DeepSeek-V3.2 (Thinking) significantly outperforms across most benchmarks. DeepSeek-V3.2 (Thinking) is made by DeepSeek and o1-preview is made by OpenAI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek-V3.2 (Thinking) scores AIME 2025: 93.1%, HMMT 2025: 90.2%, MMLU-Pro: 85.0%, LiveCodeBench: 83.3%, GPQA: 82.4%. o1-preview scores MGSM: 90.8%, MMLU: 90.8%, MATH: 85.5%, GPQA: 73.3%, LiveBench: 52.3%.
DeepSeek-V3.2 (Thinking) is 53.6x cheaper for input tokens. DeepSeek-V3.2 (Thinking) costs $0.28/M input and $0.42/M output via deepseek. o1-preview costs $15.00/M input and $60.00/M output via openai.
DeepSeek-V3.2 (Thinking) supports 131K tokens and o1-preview supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (131K vs 128K), input pricing ($0.28 vs $15.00/M), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3.2 (Thinking) is developed by DeepSeek and o1-preview is developed by OpenAI.