Qwen3.6 35B A3B (Reasoning)
AlibabaQwen開源權重Apache 2.0 · 商用許可
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.
發布日期
2026-04-16
參數規模
35.0B
上下文長度
262K
支援模態
audio, image, text, video
能力雷達圖
19
general
41
coding
84
reasoning
55
science
50
agents
80
multimodal
排行榜排名
基準測試分數 (LLM Stats)
(LLM Stats (zeroeval))Agents
TAU3-Bench
67.2%自報
MCP-Mark
37.0%自報
VITA-Bench
35.6%自報
Toolathlon
26.9%自報
DeepPlanning
25.9%自報
Code
ZClawBench
52.6%自報
Claw-Eval
50.0%自報
NL2Repo
29.4%自報
SkillsBench
28.7%自報
General
C-Eval
90.0%自報
Language
MMLU-Redux
93.3%自報
MMLU-Pro
85.2%自報
Math
AIME 2026
92.7%自報
HMMT 2025
90.7%自報
HMMT25
89.1%自報
MathVista-Mini
86.4%自報
HMMT Feb 26
83.6%自報
IMO-AnswerBench
78.9%自報
Multimodal
VideoMMMU
83.7%自報
VideoMME w/o sub.
82.5%自報
MMMU
81.7%自報
Reasoning
GPQANYU + Cohere + Anthropic (2023)
86.0%自報
LiveCodeBench v6
80.4%自報
CharXiv-R
78.0%自報
SWE-Bench Verified
73.4%自報
SWE-bench Multilingual
67.2%自報
SuperGPQA
64.7%自報
MCP Atlas
62.8%自報
Terminal-Bench 2.0Stanford × Laude Institute (2026)
51.5%自報
SWE-Bench ProPrinceton NLP (2024)
49.5%自報
Humanity's Last Exam
21.4%自報
Search
WideSearch
60.1%自報
Video
MLVU
86.2%自報
Vision
MMBench-V1.1
92.8%自報
AI2D
92.7%自報
RefCOCO-avg
0.92 / 100自報
OmniDocBench 1.5
89.9%自報
VideoMME w sub.
86.6%自報
RealWorldQA
85.3%自報
EmbSpatialBench
0.84 / 100自報
CC-OCR
81.9%自報
MMMU-Pro
75.3%自報
MVBench
74.6%自報
LVBench
71.4%自報
Hallusion Bench
69.8%自報
RefSpatialBench
0.64 / 100自報
SimpleVQA
0.59 / 100自報
ODinW
50.8%自報
ZEROBench-Sub
0.34 / 100自報
AA 評測指數
(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 144.9
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 Banking9.3
Terminalbench V4 00.0
LLM Stats 分類評分
(LLM Stats (zeroeval))Language90
Structured Output90
Biology90
Long Context80
Math80
Multimodal80
Physics80
Spatial Reasoning80
Embodied80
Grounding80
Healthcare80
Chemistry80
Text-to-image80
Video80
Legal70
Reasoning70
Finance70
Frontend Development70
General70
Vision70
Image To Text60
Search60
Economics60
Code50
Tool Calling50
Agents40
定價
輸入價格$0.375 / 1M tokens
輸出價格$2.25 / 1M tokens
混合價格(3:1)$0.844 / 1M tokens
速度
Tokens/秒135.3
首Token延遲1.20s
首回答延遲41.09s
供應商價格排行
供應商價格排行
4 個供應商
最便宜: DeepInfra最貴: Alibaba
供應商輸入輸出
1DeepInfra最便宜
$0
$0
2EmpirioLabs AI
$0.07
$0.42
3Venice AI
$0.1
$1
4Alibaba主要
$0.375
$2.25
比較該模型在不同 API 供應商之間的定價。