MiniMax open-sources M2.7, a 229B-parameter rival to GPT-5.3-Codex
10/04/2026 — 10/04, 17:15·1 sources·1 reports
Story overview
On October 4, 2026, DEV Community reported that MiniMax had released M2.7 on Hugging Face just a few hours earlier. According to the report, the model ships with 229B parameters, with full weights available under an Apache 2.0 license.
The number the report dwells on is 56.22%. That is M2.7's score on SWE-Pro, which the report says matches GPT-5.3-Codex. The framing is straightforward: an open-weight model from a Chinese AI company going toe to toe with OpenAI's coding flagship on an engineering benchmark.
Within minutes of the release, someone on r/LocalLLaMA was already asking how to run it on a consumer GPU, according to the report. The report does not go into architecture, training data, context length, or any follow-up plans, and it does not say who ran the benchmark or when. That is where things stand: the weights are public on Hugging Face, and the discussion around M2.7 centers on its 229B parameters, its Apache 2.0 license, and the 56.22% result on SWE-Pro.
AI-generated from 1 reports · updated 1 hour ago
Latest turnMiniMax has published M2.7 on Hugging Face with full 229B weights under an Apache 2.0 license. The model scores 56.22% on SWE-Pro, matching GPT-5.3-Codex and putting an open-weight model from a Chinese lab level with OpenAI's coding flagship on a production engineering benchmark.
Reports on this story headlines open the original
MiniMax has published M2.7 on Hugging Face with full 229B weights under an Apache 2.0 license. The model scores 56.22% on SWE-Pro, matching GPT-5.3-Codex and putting an open-weight model from a Chinese lab level with OpenAI's coding flagship on a production engineering benchmark.
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