跳转到主要内容

Qwen3.6 35B A3B (Reasoning)

AlibabaQwen开源权重Apache 2.0 · 商用许可

描述

Qwen3.6-35B-A3B is the first open-weight variant of the Qwen3.6 series, a multimodal Mixture-of-Experts model with 35B total parameters and 3B activated. It pairs a vision encoder with a hybrid 40-layer language model that interleaves Gated DeltaNet linear-attention blocks and Gated Attention blocks (10 × (3 × DeltaNet + 1 × Attention)) over 256 experts (8 routed + 1 shared, expert dim 512). The release prioritizes stability and real-world utility, with substantial gains in agentic coding (frontend workflows, repo-level reasoning) and a new option to preserve reasoning context across turns. Native context length is 262K tokens, extensible to ~1M via YaRN, and the model thinks by default.

发布日期
2026-04-16
参数规模
35.0B
上下文长度
262K
支持模态
audio, image, text, video

能力雷达图

19
general
41
coding
84
reasoning
55
science
50
agents
80
multimodal

排行榜排名

领域#排名分数来源
智能体能力模型榜86
39.0
LS
代码能力榜246
59.0
AA
通用能力榜188
56.0
AA
多模态榜44
59.0
LS
科学能力221
57.0
AA

基准测试分数 (LLM Stats)

(LLM Stats (zeroeval))

Agents

TAU3-Bench67.2%自报
MCP-Mark37.0%自报
VITA-Bench35.6%自报
Toolathlon26.9%自报
DeepPlanning25.9%自报

Code

ZClawBench52.6%自报
Claw-Eval50.0%自报
NL2Repo29.4%自报
SkillsBench28.7%自报

General

C-Eval90.0%自报

Language

MMLU-Redux93.3%自报
MMLU-Pro85.2%自报

Math

AIME 202692.7%自报
HMMT 202590.7%自报
HMMT2589.1%自报
MathVista-Mini86.4%自报
HMMT Feb 2683.6%自报
IMO-AnswerBench78.9%自报

Multimodal

VideoMMMU83.7%自报
VideoMME w/o sub.82.5%自报
MMMU81.7%自报

Reasoning

GPQANYU + Cohere + Anthropic (2023)86.0%自报
LiveCodeBench v680.4%自报
CharXiv-R78.0%自报
SWE-Bench Verified73.4%自报
SWE-bench Multilingual67.2%自报
SuperGPQA64.7%自报
MCP Atlas62.8%自报
Terminal-Bench 2.0Stanford × Laude Institute (2026)51.5%自报
SWE-Bench ProPrinceton NLP (2024)49.5%自报
Humanity's Last Exam21.4%自报

Search

WideSearch60.1%自报

Video

MLVU86.2%自报

Vision

MMBench-V1.192.8%自报
AI2D92.7%自报
RefCOCO-avg0.92 / 100自报
OmniDocBench 1.589.9%自报
VideoMME w sub.86.6%自报
RealWorldQA85.3%自报
EmbSpatialBench0.84 / 100自报
CC-OCR81.9%自报
MMMU-Pro75.3%自报
MVBench74.6%自报
LVBench71.4%自报
Hallusion Bench69.8%自报
RefSpatialBench0.64 / 100自报
SimpleVQA0.59 / 100自报
ODinW50.8%自报
ZEROBench-Sub0.34 / 100自报

AA 评测指数

(Artificial Analysis)
Tau2(Sierra + U Toronto + Vector Institute (2025))
95.3
Gpqa(NYU + Cohere + Anthropic (2023))
84.1
Lcr(Artificial Analysis)
71.7
Ifbench(Google Research (2023))
64.4
Terminalbench V2 1
44.9
Coding Index(Artificial Analysis)
41.9
Scicode(UIUC + Argonne National Lab (2024))
36.6
Terminalbench Hard(Stanford × Laude Institute (2026))
34.8
Hle(Center for AI Safety + Scale AI (2025))
22.2
Intelligence Index(Artificial Analysis)
18.2
Tau Banking
9.3
Terminalbench V4 0
0.0

LLM Stats 分类评分

(LLM Stats (zeroeval))
Language
90
Structured Output
90
Biology
90
Long Context
80
Math
80
Multimodal
80
Physics
80
Spatial Reasoning
80
Embodied
80
Grounding
80
Healthcare
80
Chemistry
80
Text-to-image
80
Video
80
Legal
70
Reasoning
70
Finance
70
Frontend Development
70
General
70
Vision
70
Image To Text
60
Search
60
Economics
60
Code
50
Tool Calling
50
Agents
40

定价

输入价格$0.375 / 1M tokens
输出价格$2.25 / 1M tokens
混合价格(3:1)$0.844 / 1M tokens

速度

Tokens/秒144.9
首Token延迟1.14s
首回答延迟38.38s

供应商价格排行

供应商价格排行

4 个供应商

最便宜: DeepInfra最贵: Alibaba
供应商输入输出
1DeepInfra最便宜
$0
$0
2EmpirioLabs AI
$0.07
$0.42
3Venice AI
$0.1
$1
4Alibaba主要
$0.375
$2.25

比较该模型在不同 API 供应商之间的定价。

外部链接