Model Comparison

GPT-5.2 vs DeepSeek-V3.1

GPT-5.2 significantly outperforms across most benchmarks. DeepSeek-V3.1 is 10.6x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

6 benchmarks

GPT-5.2 outperforms in 6 benchmarks (AIME 2025, BrowseComp, GPQA, HMMT 2025, Humanity's Last Exam, SWE-Bench Verified), while DeepSeek-V3.1 is better at 0 benchmarks.

GPT-5.2 significantly outperforms across most benchmarks.

Wed Apr 15 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

DeepSeek-V3.1 costs less

For input processing, GPT-5.2 ($1.75/1M tokens) is 6.5x more expensive than DeepSeek-V3.1 ($0.27/1M tokens).

For output processing, GPT-5.2 ($14.00/1M tokens) is 14.0x more expensive than DeepSeek-V3.1 ($1.00/1M tokens).

In conclusion, GPT-5.2 is more expensive than DeepSeek-V3.1.*

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

Lowest available price from all providers
Wed Apr 15 2026 • llm-stats.com
OpenAI
GPT-5.2
Input tokens$1.75
Output tokens$14.00
Best providerOpenAI
DeepSeek
DeepSeek-V3.1
Input tokens$0.27
Output tokens$1.00
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

GPT-5.2 accepts 400,000 input tokens compared to DeepSeek-V3.1's 163,840 tokens. DeepSeek-V3.1 can generate longer responses up to 163,840 tokens, while GPT-5.2 is limited to 128,000 tokens.

OpenAI
GPT-5.2
Input400,000 tokens
Output128,000 tokens
DeepSeek
DeepSeek-V3.1
Input163,840 tokens
Output163,840 tokens
Wed Apr 15 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

GPT-5.2 supports multimodal inputs, whereas DeepSeek-V3.1 does not.

GPT-5.2 can handle both text and other forms of data like images, making it suitable for multimodal applications.

GPT-5.2

Text
Images
Audio
Video

DeepSeek-V3.1

Text
Images
Audio
Video

License

Usage and distribution terms

GPT-5.2 is licensed under a proprietary license, while DeepSeek-V3.1 uses MIT.

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

GPT-5.2

Proprietary

Closed source

DeepSeek-V3.1

MIT

Open weights

Release Timeline

When each model was launched

GPT-5.2 was released on 2025-12-11, while DeepSeek-V3.1 was released on 2025-01-10.

GPT-5.2 is 11 months newer than DeepSeek-V3.1.

GPT-5.2

Dec 11, 2025

4 months ago

11mo newer
DeepSeek-V3.1

Jan 10, 2025

1.3 years ago

Knowledge Cutoff

When training data ends

GPT-5.2 has a documented knowledge cutoff of 2025-08-25, while DeepSeek-V3.1's cutoff date is not specified.

We can confirm GPT-5.2's training data extends to 2025-08-25, but cannot make a direct comparison without DeepSeek-V3.1's cutoff date.

GPT-5.2

Aug 2025

DeepSeek-V3.1

—

Provider Availability

GPT-5.2 is available from OpenAI. DeepSeek-V3.1 is available from DeepInfra, Novita.

GPT-5.2

openai logo
OpenAI
Input Price:Input: $1.75/1MOutput Price:Output: $14.00/1M

DeepSeek-V3.1

deepinfra logo
Deepinfra
Input Price:Input: $0.27/1MOutput Price:Output: $1.00/1M
novita logo
Novita
Input Price:Input: $0.27/1MOutput Price:Output: $1.00/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

OpenAI
Larger context window (400,000 tokens)
Supports multimodal inputs
Higher AIME 2025 score (100.0% vs 49.8%)
Higher BrowseComp score (65.8% vs 30.0%)
Higher GPQA score (92.4% vs 74.9%)
Higher HMMT 2025 score (99.4% vs 33.5%)
Higher Humanity's Last Exam score (34.5% vs 15.9%)
Higher SWE-Bench Verified score (80.0% vs 66.0%)
DeepSeek
Less expensive input tokens
Less expensive output tokens
Has open weights

Detailed Comparison

AI Model Comparison Table
Feature
OpenAI
GPT-5.2
DeepSeek
DeepSeek-V3.1

FAQ

Common questions about GPT-5.2 vs DeepSeek-V3.1

GPT-5.2 significantly outperforms across most benchmarks. GPT-5.2 is made by OpenAI and DeepSeek-V3.1 is made by DeepSeek. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
GPT-5.2 scores AIME 2025: 100.0%, HMMT 2025: 99.4%, Tau2 Telecom: 98.7%, Graphwalks BFS <128k: 94.0%, GPQA: 92.4%. DeepSeek-V3.1 scores SimpleQA: 93.4%, MMLU-Redux: 91.8%, MMLU-Pro: 83.7%, GPQA: 74.9%, CodeForces: 69.7%.
DeepSeek-V3.1 is 6.5x cheaper for input tokens. GPT-5.2 costs $1.75/M input and $14.00/M output via openai. DeepSeek-V3.1 costs $0.27/M input and $1.00/M output via deepinfra.
GPT-5.2 supports 400K tokens and DeepSeek-V3.1 supports 164K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (400K vs 164K), input pricing ($1.75 vs $0.27/M), multimodal support (yes vs no), licensing (Proprietary vs MIT). See the full comparison above for benchmark-by-benchmark results.
GPT-5.2 is developed by OpenAI and DeepSeek-V3.1 is developed by DeepSeek.