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GLM-5.2 (max)

Z AIGLMОткрытые весаMIT · Коммерческое использование

Описание

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.

Дата выхода
2026-06-16
Параметры
753.0B
Длина контекста
1.0M
Модальности
text

Радар способностей

36
general
66
coding
90
reasoning
66
science
70
agents
0
multimodal

Рейтинги

Домен#МестоОценкаИсточник
Агентные возможности34
51.0
LS
Рейтинг кодинга72
83.0
AA
Общий рейтинг32
78.0
AA
Наука61
80.0
AA

Оценки бенчмарков (LLM Stats)

(LLM Stats (zeroeval))

Agents

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

Code

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

Math

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

Reasoning

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

Индексы оценки AA

(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)
34.0

Оценки категорий LLM Stats

(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

Цены

Цена ввода$1.4 / 1M токенов
Цена вывода$4.4 / 1M токенов
Смешанная цена (3:1)$2.15 / 1M токенов
Цена чтения кэша$0.26 / 1M токенов
Цена записи кэшаБесплатно

Скорость

Токенов/сек77.3
Задержка первого токена6.97s
Время до первого ответа32.85s

Рейтинг цен провайдеров

Рейтинг цен провайдеров

9 провайдеров

Самый дешевый: DeepInfraСамый дорогой: EmpirioLabs AI
ПровайдерВводВывод
1DeepInfraСамый дешевый
$0
$0
2ZAI
$0
$0
3Fireworks
$0
$0
4FriendliAI
$0
$0
5Together
$0
$0
6Novita
$0
$0
7Z AIОсновной
$1.4
$4.4
8Neon
$1.4
$4.4
9EmpirioLabs AI
$1.4
$4.4

Сравнение цен разных API-провайдеров для этой модели.

Внешние ссылки