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Qwen3 Next 80B A3B (Reasoning)

AlibabaQwen開源權重Apache 2.0 · 商用許可

描述

Qwen3-Next-80B-A3B-Thinking is the thinking variant of the Qwen3-Next series, featuring the same groundbreaking architecture as the instruct model. Leveraging GSPO, it addresses stability and efficiency challenges of hybrid attention + high-sparsity MoE in RL training. 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), and Multi-Token Prediction. With 80B total parameters and only 3B activated, it demonstrates outstanding performance on complex reasoning tasks — outperforming Qwen3-30B-A3B-Thinking-2507, Qwen3-32B-Thinking, and even the proprietary Gemini-2.5-Flash-Thinking across multiple benchmarks. Architecture: 48 layers, 15T training tokens, hybrid layout of 12*(3*(Gated DeltaNet->MoE)->(Gated Attention->MoE)). Supports only thinking mode with automatic <think> tag inclusion, may generate longer thinking content.

發布日期
2025-09-11
參數規模
80.0B
上下文長度
131K
支援模態
text

能力雷達圖

36
general
41
coding
83
reasoning
50
science
60
agents
0
multimodal

排行榜排名

領域#排名分數來源
智慧體能力模型榜46
53.0
LS
程式碼能力榜268
44.0
AA
通用能力榜237
51.0
AA
科學能力211
54.0
AA

基準測試分數 (LLM Stats)

(LLM Stats (zeroeval))

Agents

BFCL-v372.0%自報

Biology

GPQANYU + Cohere + Anthropic (2023)77.2%自報

Chemistry

SuperGPQA60.8%自報

Code

CFEval2071.00 / 10000自報

Communication

WritingBench84.6%自報
Multi-IF77.8%自報
TAU-bench Retail69.6%自報
Tau2 Retail67.8%自報
Tau2 Airline60.5%自報
TAU-bench Airline49.0%自報
Tau2 Telecom43.9%自報

Creativity

Arena-Hard v262.3%自報

Finance

MMLU-Pro82.7%自報
MMLU-ProX78.7%自報

General

MMLU-Redux92.5%自報
IFEvalGoogle Research (2023)88.9%自報
Include78.9%自報
LiveBench 2024112576.6%自報
LiveCodeBench v668.7%自報

Math

AIME 202587.8%自報
HMMT2573.9%自報
PolyMATH56.3%自報

Reasoning

OJBench29.7%自報

AA 評測指數

(Artificial Analysis)
Math Index(Artificial Analysis)
84.3
Coding Index(Artificial Analysis)
17.4
Intelligence Index(Artificial Analysis)
16.9
Aime 25(MAA (Mathematical Association of America))
0.8
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
0.8
Livecodebench(UC Berkeley + MIT + Cornell (2024))
0.8
Gpqa(NYU + Cohere + Anthropic (2023))
0.8
Lcr(Artificial Analysis)
0.6
Ifbench(Google Research (2023))
0.6
Tau2(Sierra + U Toronto + Vector Institute (2025))
0.4
Scicode(UIUC + Argonne National Lab (2024))
0.4
Hle(Center for AI Safety + Scale AI (2025))
0.1
Terminalbench Hard(Stanford × Laude Institute (2026))
0.1
Terminalbench V2 1
0.1
Tau Banking
0.1

LLM Stats 分類評分

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

定價

輸入價格$0.5 / 1M tokens
輸出價格$6 / 1M tokens
混合價格(3:1)$1.875 / 1M tokens

速度

Tokens/秒201.3
首Token延遲1.17s
首回答延遲11.10s

供應商價格排行

供應商價格排行

10 個供應商

最便宜: Alibaba (China)最貴: Alibaba
供應商輸入輸出
1Alibaba (China)最便宜
$0.144
$1.434
2Cortecs
$0.149
$1.195
3NanoGPT
$0.15
$0.65
4OpenRouter
$0.15
$1.2
5Jiekou.AI
$0.15
$1.5
6NovitaAI
$0.15
$1.5
7Kilo Gateway
$0.15
$1.2
8LLM Gateway
$0.15
$1.2
9Merge Gateway
$0.15
$1.2
10Alibaba主要
$0.5
$6

比較該模型在不同 API 供應商之間的定價。

外部連結