GLM-5.2 is the new leading open weights model on Artificial Analysis

# GLM-5.2 is the new leading open weights model on the Artificial Analysis Intelligence Index Source: [https://artificialanalysis.ai/articles/glm-5-2-is-the-new-leading-open-weights-model-on-the-artificial-analysis-intelligence-index](https://artificialanalysis.ai/articles/glm-5-2-is-the-new-leading-open-weights-model-on-the-artificial-analysis-intelligence-index) **Z ai’s GLM\-5\.2 is the new leading open weights model on the Artificial Analysis Intelligence Index scoring 51 and it sits on the Pareto frontier of Intelligence vs Cost per Task** GLM\-5\.2 is the same size as GLM\-5\.1 \(744B total / 40B active parameters\) but scores 11 points higher on the Intelligence Index v4\.1, placing ahead of MiniMax\-M3 \(44\) and DeepSeek V4 Pro \(max, 44\)\. On the first\-party API it is priced in line with GLM\-5\.1 at $1\.4/$4\.4/$0\.26 per 1M input/output/cache hit tokens **Key results:** ➤**GLM\-5\.2 is the leading open weights model on the Intelligence Index v4\.1\.**At 51, it leads MiniMax\-M3 \(44\), DeepSeek V4 Pro \(max, 44\) and Kimi K2\.6 \(43\) ➤**Improvements across most evaluations, particularly scientific reasoning:**GLM\-5\.2 gains over GLM\-5\.1 on most evaluations, led by scientific reasoning on CritPt \(\+16 points to 21%\) and HLE \(\+12 points to 40%\), alongside AA\-LCR \(\+9 points to 71%\), tau3 banking \(\+15 points to 27%\) and SciCode \(\+7 points to 50%\)\. TerminalBench v2\.1 also improves \(\+16 points to 78%\) and GPQA Diamond gains 3 points to 89% **➤ Leading open weights model on GDPval\-AA v2 and competitive with proprietary models:**GLM\-5\.2 scores 1524 on GDPval\-AA v2, ahead of MiniMax\-M3 \(1418\) and DeepSeek V4 Pro \(max, 1328\)\. This impressive result places GLM\-5\.2 in\-line with proprietary models including GPT\-5\.5 \(xhigh reasoning\)\. GDPval\-AA v2 builds on the original GDPval\-AA by baselining Elo to human performance at 1000, introducing a rotating panel of frontier\-model judges, and raising the turn limit from 100 to 250 for longer\-horizon agent trajectories ➤**GLM\-5\.2 uses more output tokens per task than other leading open weights models:**the model uses 43k output tokens per Intelligence Index task, up from GLM\-5\.1 \(26k\) and above MiniMax\-M3 \(24k\), Kimi K2\.6 \(35k\) and DeepSeek V4 Pro \(max, 37k\) ➤**On the Intelligence vs\. Cost per Task Pareto Frontier:**GLM\-5\.2 is on the Pareto frontier of the Intelligence vs Cost per Task chart, with the lowest cost per task among models at its intelligence level\. GLM\-5\.2 costs ~$0\.46 per task, compared to GLM\-5\.1 \($0\.25\), Kimi K2\.6 \($0\.31\), MiniMax\-M3 \($0\.18\) and DeepSeek V4 Pro \(max, $0\.05\) **Additional Model Details:** ➤**License:**MIT ➤**Size:**744B total parameters, 40B active parameters, equivalent to GLM\-5\.1 ➤**Context window:**1M tokens, up from 200K on GLM\-5\.1 ➤**Pricing:**$1\.4/$0\.26/$4\.4 per 1M input/cache hit/output tokens ➤**Availability:**Alongside Z ai's first\-party API, GLM\-5\.2 is available across third\-party providers including DeepInfra, Novita, Nebius, Parasail, Siliconflow, GMI Cloud, Baseten, and Fireworks  GLM\-5\.2 leads all open weights models on GDPval\-AA v2, our primary metric for real\-world agentic performance\. At 1524 it places ahead of MiniMax\-M3 \(1418\) and DeepSeek V4 Pro \(max, 1328\), and is effectively level with GPT\-5\.5 \(xhigh, 1514\)\. We visually inspected GLM\-5\.2's outputs across a range of GDPval\-AA tasks\. We have attached a selection below\.  GLM\-5\.2 scores 4 on the AA\-Omniscience Index, up from GLM\-5\.1 \(2\)\. The gain comes from both higher accuracy \(25\.1% vs 24\.2%\) and a lower hallucination rate \(28\.1% vs 29\.4%\), with attempt rate flat at 47%\.  GLM\-5\.2 uses 43k output tokens per Intelligence Index task, of which 37k is reasoning\. This is up from GLM\-5\.1 \(26k\) and higher than open weights peers MiniMax\-M3 \(24k\) and Kimi K2\.6 \(35k\), placing it among the less token\-efficient open weights models at its intelligence level\. GLM\-5\.2 sits off the most attractive quadrant on the Intelligence vs Output Tokens chart\.  Breakdown of the individual evaluations in the Artificial Analysis Intelligence Index v4\.1\.  Compare GLM\-5\.2 with other leading models at:[https://artificialanalysis\.ai/models/glm\-5\-2](https://artificialanalysis.ai/models/glm-5-2)