Model Comparison

Gemini Diffusion vs GPT-5.2 Codex

Comparing Gemini Diffusion and GPT-5.2 Codex across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Gemini Diffusion and GPT-5.2 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

Cost data unavailable.

Lowest available price from all providers
Thu Apr 16 2026 • llm-stats.com
Google
Gemini Diffusion
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
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

Only GPT-5.2 Codex specifies input context (400,000 tokens). Only GPT-5.2 Codex specifies output context (128,000 tokens).

Google
Gemini Diffusion
Input- tokens
Output- tokens
OpenAI
GPT-5.2 Codex
Input400,000 tokens
Output128,000 tokens
Thu Apr 16 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

GPT-5.2 Codex supports multimodal inputs, whereas Gemini Diffusion does not.

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

Gemini Diffusion

Text
Images
Audio
Video

GPT-5.2 Codex

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under proprietary licenses.

Both models have usage restrictions defined by their respective organizations.

Gemini Diffusion

Proprietary

Closed source

GPT-5.2 Codex

Proprietary

Closed source

Release Timeline

When each model was launched

Gemini Diffusion was released on 2025-05-20, while GPT-5.2 Codex was released on 2026-01-14.

GPT-5.2 Codex is 8 months newer than Gemini Diffusion.

Gemini Diffusion

May 20, 2025

11 months ago

GPT-5.2 Codex

Jan 14, 2026

3 months ago

7mo 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

Outputs Comparison

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Key Takeaways

Google
OpenAI
Larger context window (400,000 tokens)
Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemini Diffusion
OpenAI
GPT-5.2 Codex

FAQ

Common questions about Gemini Diffusion vs GPT-5.2 Codex

Gemini Diffusion (Google) and GPT-5.2 Codex (OpenAI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
Gemini Diffusion scores HumanEval: 89.6%, MBPP: 76.0%, Global-MMLU-Lite: 69.1%, LBPP (v2): 56.8%, BigCodeBench: 45.4%. GPT-5.2 Codex scores Terminal-Bench 2.0: 64.0%, SWE-Bench Pro: 56.4%.
Gemini Diffusion supports an unknown number of 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 multimodal support (no vs yes). See the full comparison above for benchmark-by-benchmark results.
Gemini Diffusion is developed by Google and GPT-5.2 Codex is developed by OpenAI.