Can Post‑Training Close the Gap to Mythos‑Level AI? Musk Says 9 Months, Tang Says Faster

Mythos model ban and GLM‑5.2 progress

Mythos has been banned, so China must rely on domestic development. GLM‑5.2 was released, narrowing the performance gap of the base model.

Importance of post‑training

OpenAI’s jump from GPT‑4 to o1 and Anthropic’s Constitutional AI show that post‑training, not just larger pre‑training, provides the core performance boost. The improvement from GLM‑5.1 to 5.2 is itself attributed to effective post‑training.

Mind Lab’s post‑training results

Machine Heart reported that Mind Lab (under Mindverse) is the only external team that has completed post‑training for the GLM‑5.1/5.2 series. Their model Macaron‑V1‑Preview, fine‑tuned from GLM‑5.1, achieves:

PinchBench: 76.6 → 92.5 (+15.9 points, +20.8 % relative)

Terminal‑Bench 2.0: 63.5 → 67.4 (+3.9 points)

These gains indicate substantial untapped potential in the GLM base models.

Rapid adaptation to GLM‑5.2

Mind Lab quickly added support for GLM‑5.2’s new IndexCache architecture and open‑sourced the adaptation. They also released solutions for Dynamic Sparse Attention (DSA) and Multi‑Token Prediction (MTP), which are required for models above 700 B parameters.

Iteration speed advantage

Post‑training teams iterate on the order of weeks, whereas base‑model training takes months. Consequently, once a new base model is released, post‑training can deliver capability improvements faster.

Barriers to entry

Three essential capabilities limit the number of post‑training teams:

Deep understanding of the base architecture. GLM’s MTP, DSA, and IndexCache are specialized features for >700 B models and are not usable with generic open‑source frameworks.

Construction of high‑quality post‑training data. The data differs fundamentally from pre‑training data; quality and structure matter more than scale.

Robust engineering infrastructure. Post‑training requires precise hyper‑parameter management and large compute. Mind Lab open‑sourced a Megatron‑based training framework that fully supports GLM‑5.1 and 5.2.

Implications for reaching Mythos‑level AI

Given the demonstrated post‑training gains and the short iteration cycles, Mind Lab is positioned as a critical external contributor for China to approach Mythos‑level intelligence within a realistic timeframe.