{"slug": "glm-5-2-is-the-leading-open-weights-model-on-the-intelligence-index-v4-1", "title": "GLM-5.2 is the leading open weights model on the Intelligence Index v4.1", "summary": "Z ai's GLM-5.2, a 744B-parameter open weights model with 40B active parameters, achieved a score of 51 on the Artificial Analysis Intelligence Index v4.1, surpassing competitors MiniMax-M3 and DeepSeek V4 Pro. It also leads on the GDPval-AA v2 agentic benchmark with a score of 1524, matching proprietary models like GPT-5.5, and is available under an MIT license with a 1M-token context window.", "body_md": "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\n\n[@Zai_org](/Zai_org)’s 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](/DeepInfra),[@novita_labs](/novita_labs),[@nebiusai](/nebiusai),[@parasailnetwork](/parasailnetwork),[@SiliconFlowAI](/SiliconFlowAI),[@gmi_cloud](/gmi_cloud),[@Baseten](/Baseten)and[@FireworksAI_HQ](/FireworksAI_HQ)Jun 17, 2026 · 6:41 AM UTC\n\n19\n\n68\n\n489\n\n45,739\n\nGLM-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\n\n1\n\n5\n\n49\n\n2,551\n\nGLM-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%\n\n1\n\n1\n\n26\n\n2,020\n\nGLM-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\n\n1\n\n22\n\n1,532\n\nBreakdown of the individual evaluations in the Artificial Analysis Intelligence Index v4.1\n\n1\n\n2\n\n25\n\n2,624\n\nCompare GLM-5.2 with other leading models at:\n\n[artificialanalysis.ai/models…](https://artificialanalysis.ai/models/glm-5-2) 18\n\n2,259", "url": "https://wpnews.pro/news/glm-5-2-is-the-leading-open-weights-model-on-the-intelligence-index-v4-1", "canonical_source": "https://xcancel.com/ArtificialAnlys/status/2067135640249209175", "published_at": "2026-06-17 08:12:30+00:00", "updated_at": "2026-06-17 08:22:52.331384+00:00", "lang": "en", "topics": ["large-language-models", "artificial-intelligence", "ai-research", "ai-products", "ai-agents"], "entities": ["Z ai", "GLM-5.2", "MiniMax-M3", "DeepSeek V4 Pro", "Kimi K2.6", "GPT-5.5", "Artificial Analysis", "DeepInfra"], "alternates": {"html": "https://wpnews.pro/news/glm-5-2-is-the-leading-open-weights-model-on-the-intelligence-index-v4-1", "markdown": "https://wpnews.pro/news/glm-5-2-is-the-leading-open-weights-model-on-the-intelligence-index-v4-1.md", "text": "https://wpnews.pro/news/glm-5-2-is-the-leading-open-weights-model-on-the-intelligence-index-v4-1.txt", "jsonld": "https://wpnews.pro/news/glm-5-2-is-the-leading-open-weights-model-on-the-intelligence-index-v4-1.jsonld"}}