GLM 5.2.

specs at a glance

how good is GLM 5.2 at coding?

GLM 5.2 sits at #9 of 21 ranked models, posting 82.8% on SWE-bench Verified — 14.2 points behind #1 Claude Opus 5.

Score provenance: Independent (vals.ai, Jul 22 2026, mini-swe-agent bash-only harness): SWE-bench Verified 82.8% ±1.69, 9th of 75 systems. Added Jul 27, 2026 after a routine sweep found vals.ai had scored it and we were not carrying it. Z.ai published no SWE-bench Verified figure of its own, so the independent number is the ranked score with no vendor claim to disclose against it. This is now the highest-scoring genuinely downloadable model on the board: Kimi K3 scores higher at 93.4% but its weights remain unpublished, so K3 is listed as closed. Weights went up on Hugging Face and ModelScope under an unrestricted MIT license on Jun 16, 2026. Priced $1.40/$4.40 per 1M, cached input $0.26. vals.ai measured $0.71 per SWE-bench task, cheaper per solved task than every closed model ranked above it except GPT-5.6 Luna. Context 1M, max output 131k.

what does GLM 5.2 cost?

$1.40 per 1M input tokens and $4.40 per 1M output — #8 cheapest of the 20 models we track. Coding workloads are output-heavy, so weight the output rate when budgeting. Run your own volume through the AI API cost calculator for a monthly estimate.

where can you use it?

Available via API · Z.ai · OpenRouter and other hosts; MIT weights on Hugging Face and ModelScope. Because it ships open weights, you can also self-host it on your own hardware or any inference provider — with the version pinned so the model can't change under you.

Full storyZhipu's GLM-5.2 Tops the Open-Weight Model Rankings

Ranked on our AI Coding Leaderboard — scores confirmed against primary sources only, updated 2026-07-27.