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Hy3

Tencent오픈 웨이트Apache 2.0 · 상업적 사용 가능

설명

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.

출시일
2026-07-06
파라미터
295.0B
컨텍스트 길이
262K
모달리티
text

능력 레이더

27
general
57
coding
90
reasoning
64
science
70
agents
0
multimodal

랭킹

도메인#순위점수소스
에이전트형 역량53
48.0
LS
코딩 랭킹120
78.0
AA
종합 랭킹315
41.0
AA
과학104
72.0
AA

벤치마크 점수 (LLM Stats)

(LLM Stats (zeroeval))

Agents

WildClawBench53.6%자체 보고
Toolathlon48.5%자체 보고

Chemistry

SuperChem54.9%자체 보고

Code

Claw-Eval68.5%자체 보고
SkillsBench55.3%자체 보고
NL2Repo45.6%자체 보고
DeepSWE28.0%자체 보고
CL-bench23.8%자체 보고
CL-bench (Life)17.0%자체 보고

Math

USAMO 202630.24 / 42자체 보고
IMO-AnswerBench90.0%자체 보고
ArXivMath52.2%자체 보고
MathArena Apex38.7%자체 보고
HorizonMath7.1%자체 보고

Physics

PHYBench77.4%자체 보고
CMT-Benchmark37.9%자체 보고

Reasoning

GPQANYU + Cohere + Anthropic (2023)90.4%자체 보고
BrowseCompOpenAI (2025)84.2%자체 보고
MCP Atlas79.1%자체 보고
SWE-Bench Verified78.0%자체 보고
SWE-bench Multilingual75.8%자체 보고
FrontierScience Olympiad74.8%자체 보고
AA-LCR73.4%자체 보고
Terminal-Bench 2.171.7%자체 보고
SWE-Bench ProPrinceton NLP (2024)57.9%자체 보고
Humanity's Last Exam (with tools, text-only)53.2%자체 보고
Humanity's Last Exam (no tools, text-only)47.0%자체 보고
APEX-Agents25.6%자체 보고
FrontierScience Research21.3%자체 보고

Search

DeepSearchQA91.0%자체 보고
WideSearch76.4%자체 보고

AA 평가 지수

(Artificial Analysis)
Gpqa(NYU + Cohere + Anthropic (2023))
89.7
Lcr(Artificial Analysis)
79.0
Terminalbench V2 1
64.4
Coding Index(Artificial Analysis)
58.8
Scicode(UIUC + Argonne National Lab (2024))
48.6
Hle(Center for AI Safety + Scale AI (2025))
33.5
Intelligence Index(Artificial Analysis)
25.3
Tau Banking
22.9

LLM Stats 카테고리 점수

(LLM Stats (zeroeval))
Math
4
Reasoning
2
General
2
Biology
90
Physics
80
Search
80
Frontend Development
80
Long Context
70
Chemistry
70
Tool Calling
70
Science
60
Agents
60
Code
60
Knowledge
50
Coding
50

가격

입력 가격$0.136 / 1M 토큰
출력 가격$0.555 / 1M 토큰
혼합 가격 (3:1)$0.241 / 1M 토큰
캐시 읽기 가격$0.033 / 1M 토큰

속도

토큰/초96.0
첫 토큰 지연1.99s
첫 응답 지연22.83s

공급자 가격 순위

공급자 가격 순위

14개 공급자

최저가: DeepInfra최고가: OrcaRouter
공급자입력출력
1DeepInfra최저가
$0
$0
2NanoGPT
$0.066
$0.26
3Kilo Gateway
$0.13
$0.53
4OpenRouter
$0.132
$0.528
5DevPass (LLM Gateway)
$0.132
$0.528
6LLM Gateway
$0.132
$0.528
7Tencent주요
$0.136
$0.555
8OpenCode Go
$0.14
$0.58
9Requesty
$0.14
$0.58
10Vercel AI Gateway
$0.14
$0.58
11Jalapeno Cloud
$0.14
$0.58
12AIHubMix
$0.1562
$0.6248
13CrossModel
$0.16
$0.64
14OrcaRouter
$0.18
$0.59

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