Compare GPT-5.2 Chat by OpenAI against Kimi K2 by Moonshot AI, tested across 53 shared challenges. Updated April 2026.
GPT-5.2 Chat and Kimi K2 are both competitive models. GPT-5.2 Chat costs $1.75/M input tokens vs $0.57/M for Kimi K2. Compare their real outputs side by side below.
GPT-5.2 Chat is made by openai while Kimi K2 is from moonshotai. On pricing, GPT-5.2 Chat costs $1.75/M input tokens vs $0.57/M for Kimi K2.
No community votes yet. On paper, these are closely matched - try both with your actual task to see which fits your workflow.
Kimi K2 is 6.1x cheaper per token — worth considering if cost matters.
GPT-5.2 Chat uses 4.6x more transitions
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 GPT-5.2 Chat by OpenAI against Kimi K2 by Moonshot AI, tested across 53 shared challenges. Updated April 2026.
GPT-5.2 Chat and Kimi K2 are both competitive models. GPT-5.2 Chat costs $1.75/M input tokens vs $0.57/M for Kimi K2. Compare their real outputs side by side below.
GPT-5.2 Chat is made by openai while Kimi K2 is from moonshotai. On pricing, GPT-5.2 Chat costs $1.75/M input tokens vs $0.57/M for Kimi K2.
No community votes yet. On paper, these are closely matched - try both with your actual task to see which fits your workflow.
Kimi K2 is 6.1x cheaper per token — worth considering if cost matters.
GPT-5.2 Chat uses 4.6x more transitions
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.
