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GLM-5.2 (max)

Z AIGLMओपन वेटMIT · व्यावसायिक उपयोग

विवरण

GLM-5.2 is Z.AI's flagship foundation model built for long-horizon tasks, delivering a solid 1M-token context that stably sustains long, messy coding-agent trajectories. It improves substantially over GLM-5.1, becoming the strongest open-source model on standard coding benchmarks (81.0 on Terminal-Bench 2.1 and 62.1 on SWE-bench Pro) and the highest-ranked open-source model across long-horizon coding benchmarks (FrontierSWE, PostTrainBench, SWE-Marathon). It introduces flexible thinking effort levels (High and Max) to balance capability against latency and compute. Architecturally, GLM-5.2 proposes IndexShare, which reuses one lightweight indexer across every four sparse-attention (DSA) layers to cut per-token FLOPs by 2.9x at 1M context, and an improved MTP layer for speculative decoding that raises acceptance length by up to 20%. Released under a pure MIT open-source license with weights available on HuggingFace and ModelScope, it supports transformers, vLLM, SGLang, xLLM, and ktransformers, with 1M input context, 128K max output, thinking mode, function calling, structured output, context caching, and MCP integration.

रिलीज़ तिथि
2026-06-16
पैरामीटर
753.0B
संदर्भ लंबाई
1.0M
मोडैलिटीज़
text

क्षमता रडार

35
general
66
coding
90
reasoning
66
science
70
agents
0
multimodal

रैंकिंग

बेंचमार्क स्कोर (LLM Stats)

(LLM Stats (zeroeval))

Agents

Program Bench63.7%स्वयं
Toolathlon48.2%स्वयं
PostTrainBench34.3%स्वयं

Code

FrontierSWE74.0%
NL2Repo48.9%स्वयं
DeepSWE46.2%स्वयं
DeepSWE 1.144.0%
SWE-Marathon13.0%स्वयं

Math

AIME 202699.2%स्वयं
HMMT 202594.4%स्वयं
HMMT Feb 2692.5%स्वयं
IMO-AnswerBench91.0%स्वयं

Reasoning

GPQANYU + Cohere + Anthropic (2023)91.2%स्वयं
Terminal-Bench 2.182.7%स्वयं
MCP Atlas76.8%स्वयं
SWE-Bench ProPrinceton NLP (2024)62.1%स्वयं
Humanity's Last Exam54.7%स्वयं
FrontierCode 1.124.5%
CritPT16.7%स्वयं

AA मूल्यांकन सूचकांक

(Artificial Analysis)
Tau2(Sierra + U Toronto + Vector Institute (2025))
99.1
Gpqa(NYU + Cohere + Anthropic (2023))
89.5
Lcr(Artificial Analysis)
78.3
Terminalbench V2 1
77.9
Ifbench(Google Research (2023))
73.3
Coding Index(Artificial Analysis)
68.8
Scicode(UIUC + Argonne National Lab (2024))
51.2
Terminalbench Hard(Stanford × Laude Institute (2026))
50.8
Hle(Center for AI Safety + Scale AI (2025))
41.1
Tau Banking
34.6
Intelligence Index(Artificial Analysis)
33.7

LLM Stats श्रेणी स्कोर

(LLM Stats (zeroeval))
Physics
90
Biology
90
Chemistry
90
Math
70
Tool Calling
70
Reasoning
60
General
60
Agents
50
Code
50
Vision
50
Systems
30

मूल्य निर्धारण

इनपुट मूल्य$1.4 / 1M टोकन
आउटपुट मूल्य$4.4 / 1M टोकन
मिश्रित मूल्य (3:1)$2.15 / 1M टोकन
कैश पठन मूल्य$0.26 / 1M टोकन
कैश लेखन मूल्यमुफ्त

गति

टोकन/सेकंड0.0
पहले टोकन में देरी0.00s
पहले उत्तर में देरी0.00s

प्रदाता मूल्य रैंकिंग

प्रदाता मूल्य रैंकिंग

9 प्रदाता

सबसे सस्ता: DeepInfraसबसे महंगा: EmpirioLabs AI
प्रदाताइनपुटआउटपुट
1DeepInfraसबसे सस्ता
$0
$0
2FriendliAI
$0
$0
3Fireworks
$0
$0
4Novita
$0
$0
5Together
$0
$0
6ZAI
$0
$0
7Z AIप्राथमिक
$1.4
$4.4
8Neon
$1.4
$4.4
9EmpirioLabs AI
$1.4
$4.4

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