What happened: GLM-4.7-Flash-Coder

GLM-4.7-Flash-Coder, a 30B mixture-of-experts model, improved agentic coding performance from 33.15% to 41.65% on SWE-rebench-V2 with 14% lower inference cost.

Why it matters: GLM-4.7-Flash-Coder

Engineers building code-generation agents or evaluating smaller models against larger competitors should assess this model's cost-performance tradeoff for their specific workloads.

Watch out: GLM-4.7-Flash-Coder

The model was trained on successful trajectories from a teacher model using rejection sampling; performance on novel or out-of-distribution tasks remains unclear.

In the news

GLM-4.7-Flash-Coder

White Circle · Published September 21, 2026 · 3 min read

In 30 seconds

What happened: GLM-4.7-Flash-Coder, a 30B mixture-of-experts model, improved agentic coding performance from 33.15% to 41.65% on SWE-rebench-V2 with 14% lower inference cost.
Why it matters: Engineers building code-generation agents or evaluating smaller models against larger competitors should assess this model's cost-performance tradeoff for their specific workloads.
Watch out: The model was trained on successful trajectories from a teacher model using rejection sampling; performance on novel or out-of-distribution tasks remains unclear.

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