मुख्य सामग्री पर जाएं

Qwen3 Next 80B A3B Instruct

AlibabaQwenओपन वेटApache 2.0 · व्यावसायिक उपयोग

विवरण

Qwen3-Next-80B-A3B-Instruct is the first in the Qwen3-Next series, featuring groundbreaking architectural innovations. It uses Hybrid Attention combining Gated DeltaNet and Gated Attention for efficient ultra-long context modeling, High-Sparsity MoE with 512 experts (10 activated + 1 shared) achieving extreme low activation ratio, and Multi-Token Prediction for improved performance and faster inference. With 80B total parameters and only 3B activated, it outperforms Qwen3-32B-Base with 10% training cost and 10x throughput for 32K+ contexts. The model performs on par with Qwen3-235B-A22B-Instruct-2507 while excelling at ultra-long-context tasks up to 256K tokens (extensible to 1M with YaRN). Architecture: 48 layers, 15T training tokens, hybrid layout of 12*(3*(Gated DeltaNet->MoE)->(Gated Attention->MoE)).

रिलीज़ तिथि
2025-09-11
पैरामीटर
80.0B
संदर्भ लंबाई
131K
मोडैलिटीज़
text

क्षमता रडार

33
general
60
coding
68
reasoning
45
science
50
agents
0
multimodal

रैंकिंग

बेंचमार्क स्कोर (LLM Stats)

(LLM Stats (zeroeval))

Agents

BFCL-v370.3%स्वयं

Biology

GPQANYU + Cohere + Anthropic (2023)72.9%स्वयं

Chemistry

SuperGPQA58.8%स्वयं

Code

Aider-Polyglot49.8%स्वयं

Communication

WritingBench87.3%स्वयं
Multi-IF75.8%स्वयं
TAU-bench Retail60.9%स्वयं
Tau2 Retail57.3%स्वयं
Tau2 Airline45.5%स्वयं
TAU-bench Airline44.0%स्वयं
Tau2 Telecom13.2%स्वयं

Creativity

Creative Writing v385.3%स्वयं
Arena-Hard v282.7%स्वयं

Finance

MMLU-Pro80.6%स्वयं
MMLU-ProX76.7%स्वयं

General

MMLU-Redux90.9%स्वयं
MultiPL-E87.8%स्वयं
IFEvalGoogle Research (2023)87.6%स्वयं
Include78.9%स्वयं
LiveBench 2024112575.8%स्वयं
LiveCodeBench v656.6%स्वयं

Math

AIME 202569.5%स्वयं
HMMT2554.1%स्वयं
PolyMATH45.9%स्वयं

AA मूल्यांकन सूचकांक

(Artificial Analysis)
Math Index(Artificial Analysis)
66.3
Intelligence Index(Artificial Analysis)
13.8
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
0.8
Gpqa(NYU + Cohere + Anthropic (2023))
0.7
Livecodebench(UC Berkeley + MIT + Cornell (2024))
0.7
Aime 25(MAA (Mathematical Association of America))
0.7
Lcr(Artificial Analysis)
0.5
Ifbench(Google Research (2023))
0.4
Scicode(UIUC + Argonne National Lab (2024))
0.3
Tau2(Sierra + U Toronto + Vector Institute (2025))
0.2
Hle(Center for AI Safety + Scale AI (2025))
0.1
Terminalbench Hard(Stanford × Laude Institute (2026))
0.1

LLM Stats श्रेणी स्कोर

(LLM Stats (zeroeval))
Creativity
90
Writing
90
Instruction Following
80
Language
80
Legal
80
Structured Output
80
Math
70
Physics
70
Finance
70
General
70
Healthcare
70
Agents
70
Biology
70
Chemistry
70
Reasoning
60
Economics
60
Multimodal
50
Spatial Reasoning
50
Code
50
Communication
50
Tool Calling
50
Vision
50

मूल्य निर्धारण

इनपुट मूल्य$0.5 / 1M टोकन
आउटपुट मूल्य$2 / 1M टोकन
मिश्रित मूल्य (3:1)$0.875 / 1M टोकन

गति

टोकन/सेकंड187.6
पहले टोकन में देरी1.05s
पहले उत्तर में देरी1.05s

प्रदाता मूल्य रैंकिंग

प्रदाता मूल्य रैंकिंग

11 प्रदाता

सबसे सस्ता: Kilo Gatewayसबसे महंगा: Alibaba
प्रदाताइनपुटआउटपुट
1Kilo Gatewayसबसे सस्ता
$0.0975
$0.78
2OpenRouter
$0.1
$1.1
3Charm Hyper
$0.1175
$1.136
4Helicone
$0.14
$1.4
5Alibaba (China)
$0.144
$0.574
6Merge Gateway
$0.144
$0.574
7Jiekou.AI
$0.15
$1.5
8NovitaAI
$0.15
$1.5
9LLM Gateway
$0.15
$1.2
10Neon
$0.15
$1.2
11Alibabaप्राथमिक
$0.5
$2

इस मॉडल के लिए विभिन्न API प्रदाताओं के मूल्य निर्धारण की तुलना करें।

बाहरी लिंक