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Hy3

TencentОткрытые весаApache 2.0 · Коммерческое использование

Описание

Hy3 is a 295B-parameter Mixture-of-Experts (MoE) model with 21B active parameters and a 3.8B MTP layer, developed by the Tencent Hy Team. Following the Hy3 Preview launch in late April, the team scaled up post-training with higher-quality data and RL, gathering feedback from 50+ products. Hy3 outperforms similar-size models and rivals flagship open-source models with 2-5x the parameters, with strong gains in reasoning, agentic, and long-context tasks. It uses 80 layers (plus 1 MTP layer), 64 GQA attention heads (8 KV heads, head dim 128), a 4096 hidden size, 192 experts with top-8 activated, a 256K context window, and BF16 precision. Hy3 is a hybrid-thinking model supporting configurable reasoning effort (no_think, low, high), and emphasizes production-grade tool-call and output-format stability, reduced hallucination, and reliable multi-turn intent tracking.

Дата выхода
2026-07-06
Параметры
295.0B
Длина контекста
262K
Модальности
text

Радар способностей

40
general
57
coding
90
reasoning
64
science
70
agents
0
multimodal

Рейтинги

Домен#МестоОценкаИсточник
Агентные возможности51
52.0
LS
Рейтинг кодинга57
80.0
AA
Общий рейтинг128
66.0
AA
Наука61
78.0
AA

Оценки бенчмарков (LLM Stats)

(LLM Stats (zeroeval))

Agents

DeepSearchQA91.0%Сам.
BrowseCompOpenAI (2025)84.2%Сам.
MCP Atlas79.1%Сам.
WideSearch76.4%Сам.
Terminal-Bench 2.171.7%Сам.
Claw-Eval68.5%Сам.
SWE-Bench ProPrinceton NLP (2024)57.9%Сам.
SkillsBench55.3%Сам.
WildClawBench53.6%Сам.
Toolathlon48.5%Сам.
NL2Repo45.6%Сам.
DeepSWE28.0%Сам.
APEX-Agents25.6%Сам.
CL-bench23.8%Сам.
CL-bench (Life)17.0%Сам.

Biology

GPQANYU + Cohere + Anthropic (2023)90.4%Сам.

Chemistry

SuperChem54.9%Сам.

Code

SWE-Bench Verified78.0%Сам.
SWE-bench Multilingual75.8%Сам.

Long Context

AA-LCR73.4%Сам.

Math

USAMO 202630.24 / 42Сам.
IMO-AnswerBench90.0%Сам.
FrontierScience Olympiad74.8%Сам.
Humanity's Last Exam (with tools, text-only)53.2%Сам.
ArXivMath52.2%Сам.
Humanity's Last Exam (no tools, text-only)47.0%Сам.
MathArena Apex38.7%Сам.
HorizonMath7.1%Сам.

Physics

PHYBench77.4%Сам.
CMT-Benchmark37.9%Сам.

Reasoning

FrontierScience Research21.3%Сам.

Индексы оценки AA

(Artificial Analysis)
Coding Index(Artificial Analysis)
58.8
Intelligence Index(Artificial Analysis)
42.2
Gpqa(NYU + Cohere + Anthropic (2023))
0.9
Lcr(Artificial Analysis)
0.7
Terminalbench V2 1
0.6
Scicode(UIUC + Argonne National Lab (2024))
0.5
Hle(Center for AI Safety + Scale AI (2025))
0.3
Tau Banking
0.2

Оценки категорий LLM Stats

(LLM Stats (zeroeval))
Math
6
Reasoning
2
General
2
Physics
90
Biology
90
Search
80
Frontend Development
80
Long Context
70
Chemistry
70
Tool Calling
70
Agents
60
Code
60
Science
50
Knowledge
50
Coding
50

Цены

Цена ввода$0.136 / 1M токенов
Цена вывода$0.557 / 1M токенов
Смешанная цена (3:1)$0.241 / 1M токенов
Цена чтения кэша$0.033 / 1M токенов

Скорость

Токенов/сек68.0
Задержка первого токена1.81s
Время до первого ответа31.22s

Рейтинг цен провайдеров

Рейтинг цен провайдеров

8 провайдеров

Самый дешевый: NanoGPTСамый дорогой: CrossModel
ПровайдерВводВывод
1NanoGPTСамый дешевый
$0.066
$0.26
2OpenRouter
$0.132
$0.528
3TencentОсновной
$0.136
$0.557
4OpenCode Go
$0.14
$0.58
5Kilo Gateway
$0.14
$0.58
6Vercel AI Gateway
$0.14
$0.58
7LLM Gateway
$0.14
$0.58
8CrossModel
$0.16
$0.64

Сравнение цен разных API-провайдеров для этой модели.

Внешние ссылки