跳轉到主要內容

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

領域#排名分數來源
智慧體能力模型榜86
39.0
LS
程式碼能力榜243
59.0
AA
通用能力榜185
56.0
AA
多模態榜44
59.0
LS
科學能力219
57.0
AA

基準測試分數 (LLM Stats)

(LLM Stats (zeroeval))

Agents

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

Code

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

General

C-Eval90.0%自報

Language

MMLU-Redux93.3%自報
MMLU-Pro85.2%自報

Math

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

Multimodal

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

Reasoning

GPQANYU + Cohere + Anthropic (2023)86.0%自報
LiveCodeBench v680.4%自報
CharXiv-R78.0%自報
SWE-Bench Verified73.4%自報
SWE-bench Multilingual67.2%自報
SuperGPQA64.7%自報
MCP Atlas62.8%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 Exam21.4%自報

Search

WideSearch60.1%自報

Video

MLVU86.2%自報

Vision

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

(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。

外部連結