Compare OpenAI Codex Mini by OpenAI against Gemma 3 12B by Google AI, tested across 10 shared challenges. Updated April 2026.
OpenAI Codex Mini and Gemma 3 12B are both competitive models. OpenAI Codex Mini costs $1.5/M input tokens vs $0.03/M for Gemma 3 12B. Compare their real outputs side by side below.
OpenAI Codex Mini is made by openai while Gemma 3 12B is from google. On pricing, OpenAI Codex Mini costs $1.5/M input tokens vs $0.03/M for Gemma 3 12B.
No community votes yet. On paper, these are closely matched - try both with your actual task to see which fits your workflow.
Gemma 3 12B is 200x cheaper per token — worth considering if cost matters.
Ask them anything yourself
Some models write identically. You are paying for the brand.
178 models fingerprinted across 32 writing dimensions. Free research.
185x
price gap between models that write identically
178
models
12
clone pairs
32
dimensions
279 AI models invented the same fake scientist.
We read every word. 250 models. 2.14 million words. This is what we found.

Compare OpenAI Codex Mini by OpenAI against Gemma 3 12B by Google AI, tested across 10 shared challenges. Updated April 2026.
OpenAI Codex Mini and Gemma 3 12B are both competitive models. OpenAI Codex Mini costs $1.5/M input tokens vs $0.03/M for Gemma 3 12B. Compare their real outputs side by side below.
OpenAI Codex Mini is made by openai while Gemma 3 12B is from google. On pricing, OpenAI Codex Mini costs $1.5/M input tokens vs $0.03/M for Gemma 3 12B.
No community votes yet. On paper, these are closely matched - try both with your actual task to see which fits your workflow.
Gemma 3 12B is 200x cheaper per token — worth considering if cost matters.
Ask them anything yourself
Some models write identically. You are paying for the brand.
178 models fingerprinted across 32 writing dimensions. Free research.
185x
price gap between models that write identically
178
models
12
clone pairs
32
dimensions
279 AI models invented the same fake scientist.
We read every word. 250 models. 2.14 million words. This is what we found.

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