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Qwen3 Next 80B A3B Instruct

AlibabaQwenOpen WeightApache 2.0 · Commercial OK

描述

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)).

發布日期
2025-09-11
參數規模
80.0B
上下文長度
262K
支援模態
text

能力雷達圖

37
general
35
coding
68
reasoning
45
science估算
50
agents
0
multimodal

Science 在缺少專門科學評測時使用推理能力代理估算。

排行榜排名

領域#排名分數來源
智能体与工具15
70.0
LS
代码能力榜193
42.0
AA
通用能力榜246
42.0
AA
数学推理130
67.0
AA
科学能力204
47.0
AA

基準測試分數 (LLM Stats)

Agents

BFCL-v370.3%自報

Biology

GPQA72.9%自報

Chemistry

SuperGPQA58.8%自報

Code

Aider-Polyglot49.8%自報

Communication

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

Creativity

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

Finance

MMLU-Pro80.6%自報
MMLU-ProX76.7%自報

General

MMLU-Redux90.9%自報
MultiPL-E87.8%自報
IFEval87.6%自報
Include78.9%自報
LiveBench 2024112575.8%自報
LiveCodeBench v656.6%自報

Math

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

AA 評測指數

Math Index
66.3
Intelligence Index
20.1
Coding Index
15.3
Mmlu Pro
0.8
Gpqa
0.7
Livecodebench
0.7
Aime 25
0.7
Lcr
0.5
Ifbench
0.4
Scicode
0.3
Tau2
0.2
Terminalbench Hard
0.1
Hle
0.1

LLM Stats 分類評分

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

定價

輸入價格$0.5 / 1M tokens
輸出價格$2 / 1M tokens
混合價格(3:1)$0.875 / 1M tokens

速度

Tokens/秒159.3 tokens/s
首Token延遲1.09s
首回答延遲1.09s

可用提供商

(LS 內部計價單位)
提供商輸入價格輸出價格
Novita150K1.5M

外部連結