Model Comparison

DeepSeek-V3.2 (Non-thinking) vs GPT-5.3 Codex

Comparing DeepSeek-V3.2 (Non-thinking) and GPT-5.3 Codex 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 GPT-5.3 Codex 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 6.2x cheaper than GPT-5.3 Codex ($1.75/1M tokens).

For output processing, DeepSeek-V3.2 (Non-thinking) ($0.42/1M tokens) is 33.3x cheaper than GPT-5.3 Codex ($14.00/1M tokens).

In conclusion, GPT-5.3 Codex 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
Thu Apr 16 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2 (Non-thinking)
Input tokens$0.28
Output tokens$0.42
Best providerDeepSeek
OpenAI
GPT-5.3 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-5.3 Codex accepts 400,000 input tokens compared to DeepSeek-V3.2 (Non-thinking)'s 131,072 tokens. GPT-5.3 Codex can generate longer responses up to 128,000 tokens, while DeepSeek-V3.2 (Non-thinking) is limited to 8,192 tokens.

DeepSeek
DeepSeek-V3.2 (Non-thinking)
Input131,072 tokens
Output8,192 tokens
OpenAI
GPT-5.3 Codex
Input400,000 tokens
Output128,000 tokens
Thu Apr 16 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

GPT-5.3 Codex supports multimodal inputs, whereas DeepSeek-V3.2 (Non-thinking) does not.

GPT-5.3 Codex can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V3.2 (Non-thinking)

Text
Images
Audio
Video

GPT-5.3 Codex

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3.2 (Non-thinking) is licensed under MIT, while GPT-5.3 Codex uses a proprietary license.

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

DeepSeek-V3.2 (Non-thinking)

MIT

Open weights

GPT-5.3 Codex

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V3.2 (Non-thinking) was released on 2025-12-01, while GPT-5.3 Codex was released on 2026-02-05.

GPT-5.3 Codex is 2 months newer than DeepSeek-V3.2 (Non-thinking).

DeepSeek-V3.2 (Non-thinking)

Dec 1, 2025

4 months ago

GPT-5.3 Codex

Feb 5, 2026

2 months ago

2mo 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 (Non-thinking) is available from DeepSeek. GPT-5.3 Codex is available from OpenAI.

DeepSeek-V3.2 (Non-thinking)

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

GPT-5.3 Codex

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

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Less expensive input tokens
Less expensive output tokens
Has open weights
OpenAI
Larger context window (400,000 tokens)
Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.2 (Non-thinking)
OpenAI
GPT-5.3 Codex

FAQ

Common questions about DeepSeek-V3.2 (Non-thinking) vs GPT-5.3 Codex

DeepSeek-V3.2 (Non-thinking) (DeepSeek) and GPT-5.3 Codex (OpenAI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
GPT-5.3 Codex scores SWE-Lancer (IC-Diamond subset): 81.4%, Cybersecurity CTFs: 77.6%, Terminal-Bench 2.0: 77.3%, OSWorld-Verified: 64.7%, SWE-Bench Pro: 56.8%.
DeepSeek-V3.2 (Non-thinking) is 6.2x cheaper for input tokens. DeepSeek-V3.2 (Non-thinking) costs $0.28/M input and $0.42/M output via deepseek. GPT-5.3 Codex costs $1.75/M input and $14.00/M output via openai.
DeepSeek-V3.2 (Non-thinking) supports 131K tokens and GPT-5.3 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 (Non-thinking) is developed by DeepSeek and GPT-5.3 Codex is developed by OpenAI.