Model Comparison

DeepSeek-V3.2 (Thinking) vs GPT-5.2 Codex

GPT-5.2 Codex significantly outperforms across most benchmarks. DeepSeek-V3.2 (Thinking) is 15.3x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

DeepSeek-V3.2 (Thinking) outperforms in 0 benchmarks, while GPT-5.2 Codex is better at 1 benchmark (Terminal-Bench 2.0).

GPT-5.2 Codex significantly outperforms across most benchmarks.

Fri Apr 17 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) is 6.2x cheaper than GPT-5.2 Codex ($1.75/1M tokens).

For output processing, DeepSeek-V3.2 (Thinking) ($0.42/1M tokens) is 33.3x cheaper than GPT-5.2 Codex ($14.00/1M tokens).

In conclusion, GPT-5.2 Codex is more expensive than DeepSeek-V3.2 (Thinking).*

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

Lowest available price from all providers
Fri Apr 17 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2 (Thinking)
Input tokens$0.28
Output tokens$0.42
Best providerDeepSeek
OpenAI
GPT-5.2 Codex
Input tokens$1.75
Output tokens$14.00
Best providerOpenAI
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

GPT-5.2 Codex accepts 400,000 input tokens compared to DeepSeek-V3.2 (Thinking)'s 131,072 tokens. GPT-5.2 Codex can generate longer responses up to 128,000 tokens, while DeepSeek-V3.2 (Thinking) is limited to 65,536 tokens.

DeepSeek
DeepSeek-V3.2 (Thinking)
Input131,072 tokens
Output65,536 tokens
OpenAI
GPT-5.2 Codex
Input400,000 tokens
Output128,000 tokens
Fri Apr 17 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

GPT-5.2 Codex supports multimodal inputs, whereas DeepSeek-V3.2 (Thinking) does not.

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

DeepSeek-V3.2 (Thinking)

Text
Images
Audio
Video

GPT-5.2 Codex

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3.2 (Thinking) is licensed under MIT, while GPT-5.2 Codex 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

GPT-5.2 Codex

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V3.2 (Thinking) was released on 2025-12-01, while GPT-5.2 Codex was released on 2026-01-14.

GPT-5.2 Codex is 1 month newer than DeepSeek-V3.2 (Thinking).

DeepSeek-V3.2 (Thinking)

Dec 1, 2025

4 months ago

GPT-5.2 Codex

Jan 14, 2026

3 months ago

1mo newer

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. GPT-5.2 Codex is available from OpenAI.

DeepSeek-V3.2 (Thinking)

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

GPT-5.2 Codex

openai logo
OpenAI
Input Price:Input: $1.75/1MOutput Price:Output: $14.00/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

DeepSeek
Less expensive input tokens
Less expensive output tokens
Has open weights
OpenAI
Larger context window (400,000 tokens)
Supports multimodal inputs
Higher Terminal-Bench 2.0 score (64.0% vs 46.4%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.2 (Thinking)
OpenAI
GPT-5.2 Codex

FAQ

Common questions about DeepSeek-V3.2 (Thinking) vs GPT-5.2 Codex

GPT-5.2 Codex significantly outperforms across most benchmarks. DeepSeek-V3.2 (Thinking) is made by DeepSeek and GPT-5.2 Codex 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%. GPT-5.2 Codex scores Terminal-Bench 2.0: 64.0%, SWE-Bench Pro: 56.4%.
DeepSeek-V3.2 (Thinking) is 6.2x cheaper for input tokens. DeepSeek-V3.2 (Thinking) costs $0.28/M input and $0.42/M output via deepseek. GPT-5.2 Codex costs $1.75/M input and $14.00/M output via openai.
DeepSeek-V3.2 (Thinking) supports 131K tokens and GPT-5.2 Codex supports 400K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (131K vs 400K), input pricing ($0.28 vs $1.75/M), multimodal support (no vs yes), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3.2 (Thinking) is developed by DeepSeek and GPT-5.2 Codex is developed by OpenAI.