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qwen의 파비콘

Qwen: Qwen3.6 35B A3B

qwen/qwen3.6-35b-a3b

모델 가중치
비교

Qwen3.6-35B-A3B is an open-weight multimodal model from Alibaba Cloud with 35 billion total parameters and 3 billion active parameters per token. It uses a hybrid sparse mixture-of-experts architecture combining Gated DeltaNet linear attention with standard gated attention layers, enabling efficient inference at a fraction of the compute cost. The model supports a 262K token native context window (extensible to 1M via YaRN) and accepts text, image, and video inputs. It includes integrated thinking mode with reasoning traces preserved across multi-turn conversations, function calling, and structured output. Released under the Apache 2.0 license.

모달리티
입력/출력 가격
US$0.05 / US$0.701M당
컨텍스트
262K
출시
2026년 4월 27일
비교
제공업체가격성능가동 시간벤치마크앱활동자주 묻는 질문탐색

제공업체

같은 모델을 서로 다른 회사가 호스팅합니다. OpenRouter는 사용자가 선택한 라우팅 모드에 따라 요청을 그중 한 곳으로 라우팅합니다 — Balanced(가격 + 속도), Nitro(가장 빠름), Floor(가장 저렴함) 또는 Exacto(가장 높은 도구 호출 정확도).

가격

고객이 이 모델에 실제로 지불하는 평균 가격으로, 제공업체가 게시한 가격과 함께 표시됩니다. 캐싱과 할인으로 인해 실제 지불 가격은 게시된 가격보다 훨씬 낮은 경우가 많습니다.

성능

처리량은 모델이 얼마나 빠르게 출력하는지를 나타냅니다(초당 토큰 수 — 높을수록 좋음). 지연 시간은 전체 왕복 시간입니다(낮을수록 좋음). TTFT는 첫 토큰까지 걸리는 시간으로, 무언가 화면에 표시되기 시작할 때까지의 시간을 뜻합니다(낮을수록 좋음).

가동 시간

가동 시간은 지난 3일 동안 하나 이상의 제공업체가 요청에 응답한 시간의 비율입니다. 가용성은 추론이 성공적으로 제공된 시간의 비율입니다. OpenRouter는 지속적으로 모니터링하며, 한 제공업체에서 오류를 반환하면 다음으로 적합한 제공업체를 사용합니다.

벤치마크

표준화된 평가와 공유 벤치마크 프롬프트에 대한 이 모델 자체의 출력 점수입니다. 백분율이 높을수록 더 좋으며, 각 순위는 이 모델이 해당 출처에서 평가된 모델 중 어디에 위치하는지를 보여줍니다.

벤치마크 점수 요약: Qwen: Qwen3.6 35B A3B (Artificial Analysis)
출처벤치마크점수
Artificial AnalysisQwen3.6 35B A3B (Non-reasoning) Intelligence Index15.2
Artificial AnalysisQwen3.6 35B A3B (Non-reasoning) Coding Index28.1
Artificial AnalysisQwen3.6 35B A3B (Non-reasoning) GPQA Diamond81.7%
Artificial AnalysisQwen3.6 35B A3B (Non-reasoning) HLE13.9%
Artificial AnalysisQwen3.6 35B A3B (Non-reasoning) IFBench36.2%
Artificial AnalysisQwen3.6 35B A3B (Non-reasoning) τ²-Bench Telecom85.1%
Artificial AnalysisQwen3.6 35B A3B (Non-reasoning) AA-LCR64.3%
Artificial AnalysisQwen3.6 35B A3B (Non-reasoning) τ-Bench Banking5.4%
Artificial AnalysisQwen3.6 35B A3B (Non-reasoning) GDPval-AA17.5%
Artificial AnalysisQwen3.6 35B A3B (Non-reasoning) CritPt0.0%
Artificial AnalysisQwen3.6 35B A3B (Non-reasoning) Terminal-Bench Hard25.8%
Artificial AnalysisQwen3.6 35B A3B (Non-reasoning) Terminal-Bench 2.141.6%
Artificial AnalysisQwen3.6 35B A3B (Non-reasoning) AA-Omniscience Accuracy16.7%
Artificial AnalysisQwen3.6 35B A3B (Non-reasoning) AA-Omniscience Non-Hallucination Rate7.9%
Artificial AnalysisQwen3.6 35B A3B (Reasoning) Intelligence Index18.2
Artificial AnalysisQwen3.6 35B A3B (Reasoning) Coding Index41.9
Artificial AnalysisQwen3.6 35B A3B (Reasoning) Agentic Index13.1
Artificial AnalysisQwen3.6 35B A3B (Reasoning) GPQA Diamond84.1%
Artificial AnalysisQwen3.6 35B A3B (Reasoning) HLE22.2%
Artificial AnalysisQwen3.6 35B A3B (Reasoning) IFBench64.4%
Artificial AnalysisQwen3.6 35B A3B (Reasoning) τ²-Bench Telecom95.3%
Artificial AnalysisQwen3.6 35B A3B (Reasoning) AA-LCR71.7%
Artificial AnalysisQwen3.6 35B A3B (Reasoning) τ-Bench Banking9.3%
Artificial AnalysisQwen3.6 35B A3B (Reasoning) GDPval-AA19.8%
Artificial AnalysisQwen3.6 35B A3B (Reasoning) CritPt0.3%
Artificial AnalysisQwen3.6 35B A3B (Reasoning) SciCode36.6%
Artificial AnalysisQwen3.6 35B A3B (Reasoning) Terminal-Bench Hard34.8%
Artificial AnalysisQwen3.6 35B A3B (Reasoning) Terminal-Bench 4.00.0%
Artificial AnalysisQwen3.6 35B A3B (Reasoning) Terminal-Bench 2.144.9%
Artificial AnalysisQwen3.6 35B A3B (Reasoning) AA-Omniscience Accuracy18.8%
Artificial AnalysisQwen3.6 35B A3B (Reasoning) AA-Omniscience Non-Hallucination Rate49.5%

앱

이 모델로 가장 많은 트래픽을 보내는 공개 앱입니다. 실제 프로덕션 워크로드가 어떤 모습인지 파악하는 데 유용하며, 이 모델이 어떤 사용 사례에 가장 적합한지 알려 주는 단서이기도 합니다.

활동

시간 경과에 따른 이 모델의 토큰 사용량과 요청 트래픽입니다.

API

이 모델을 호출하는 데 바로 사용할 수 있는 코드입니다. OpenRouter의 API는 OpenAI와 호환되므로 대부분의 SDK는 기본 URL만 바꾸면 작동합니다. 모델 간에 변경되는 것은 아래의 모델 슬러그뿐입니다.

더 많은 모델 살펴보기

비전 기능을 갖춘 AI 모델: 이미지 이해를 위한 멀티모달 LLM컬렉션AI 모델 순위순위
US$0.050US$0.70000US$0.0252.97s41 tps
100.00%
US$0.100US$0.90000US$0.0500.55s82 tps
99.93%
US$0.100US$0.95000US$0.1000.96s85 tps
70.00%
US$0.100US$1.00000US$0.0500.42s262 tps
98.54%
US$0.100US$1.00000--0.72s91 tps
96.50%
US$0.150US$1.00000US$0.0500.55s83 tps
99.72%
US$0.200US$1.27000US$0.0561.44s41 tps
89.15%
US$0.240US$1.80000US$0.1500.71s111 tps
97.91%
US$0.250US$1.25000US$0.2500.34s122 tps
99.93%
US$0.186US$1.11375US$0.1861.28s109 tps
61.35%
처리량
262tok/s

P50, 제공업체 전체 중 최고

지연 시간
0.34초

P50, 최고 제공업체

AutoExacto benchmarks
GPQA DiamondTAU-BenchSiliconFlow84.3%--CoreWeave82.6%--Parasail85.5%75.6%Phala83.0%76.9%Reka83.6%74.4%
+8 개 추가 제공업체
가동 시간(3일)모델에 연결할 수 있습니다. 요청이 제공업체로 라우팅되었습니다.
100.00%
가용성(3일)모델이 어떤 제공업체에서든 추론 결과를 반환한 비율입니다. 오류와 빈 응답은 가동 시간을 낮춥니다.
98.88%

지난 3일간의 가용성

최근 72시간
가용성 98.88%
3일 전2일 전어제지금

지난 24시간 동안의 가용성

OpenRouter Availability
99.86%
Without Routing
91.62%

업스트림 제공업체에서 오류가 발생하면 요청 필터에서 허용하는 경우 정상 상태인 다른 제공업체로 라우팅하여 복구할 수 있습니다. 제공업체별 가동 시간 데이터는 프로그래밍 방식으로 엔드포인트 API를 통해 확인할 수 있습니다. 로드 밸런싱 및 사용자 지정 옵션에 대해 자세히 알아보세요.

1.
https://sekai.chat/의 파비콘
Sekai
신규
32.3B토큰
2.
https://claude.ai/apple-touch-icon.png의 파비콘
Claude Code
Claude Code is Anthropic's agentic coding tool that reads your entire codebase, plans and executes changes across files, runs tests, and iterates on failures, all from natural language prompts.
6.91B토큰
3.
https://nousresearch.com의 파비콘
Hermes Agent
Hermes Agent is an open-source, self-improving AI agent by Nous Research that runs persistently with memory across sessions, and builds reusable skills from experience. It comes with 40+ built-in tools, including web search, browser automation, and vision, plus scheduled automations and subagents.
5.66B토큰
4.
https://github.com/QwenLM/qwen-code.git의 파비콘
Qwen Code
Powerful command-line AI workflow tool
4.6B토큰
5.
https://portal.nousresearch.com/api-docs의 파비콘
Nous Research API
Nous Research is an AI research team focused on advancing open-source AI.
4.26B토큰

자주 묻는 질문

Qwen3.6-35B-A3B is an open-weight multimodal model from Alibaba Cloud with 35 billion total parameters and 3 billion active parameters per token. It uses a hybrid sparse mixture-of-experts architecture combining Gated DeltaNet linear attention with standard gated attention layers, enabling efficient inference at a fraction of the compute cost.

Qwen3.6 35B A3B의 비용은 US$0.05/M 입력 토큰 및 US$0.70/M 출력 토큰, US$0.025/M tokens의 Cache Read에 대한 요금은 별도입니다.

Qwen3.6 35B A3B의 컨텍스트 윈도우는 262,144토큰입니다. 최대 32,768개의 완료 토큰을 지원합니다.

예. Qwen3.6 35B A3B은(는) 해당 모델을 제공하는 10개 제공업체 중 8곳에서 함수 호출을 위한 tools 및 tool_choice를 지원하며, 도구를 전송하는 요청은 해당 제공업체로 라우팅됩니다. 또한 response_format에서 JSON 스키마를 사용하여 구조화된 출력을 지원합니다.

Qwen3.6 35B A3B은(는) 텍스트, 이미지 및 비디오을(를) 입력으로 받고 텍스트을(를) 반환합니다.

Qwen3.6 35B A3B은(는) OpenRouter에서 10개 제공업체가 제공합니다: Darkbloom, AkashML, DeepInfra, DekaLLM, Venice, Parasail, AtlasCloud, Phala 외 2개. 요청은 사용 가능한 최적의 제공업체로 라우팅되며, 다른 제공업체로 자동 장애 조치됩니다. 제공업체 라우팅을 사용하여 제공업체를 고정하거나 제외할 수도 있습니다.

Qwen3.6 35B A3B은(는) 2026년 4월 27일에 출시되었습니다.

다음 제공업체의 추가 모델 Qwen

Qwen3.8 Max Prime

Qwen3.8 Max Prime is a higher-throughput variant of Qwen3.8 Max from Alibaba's Qwen team, served as a separate SKU at a higher price point. It accepts text, image, and video input and returns text, with a 1M-token context window and reasoning enabled by default. Tool calling, structured outputs, and configurable reasoning effort are supported, matching Qwen3.8 Max.

텍스트컨텍스트 1MUS$4 / US$12
Qwen3.8 Omni Flash

Qwen3.8 Omni Flash is an omni-modal reasoning model from Alibaba, the first Qwen model built around agentic capabilities with native audio-video understanding. It is suited for audio-video analysis and summarization, video editing and production workflows, audio-video dialogue, coding, knowledge work, and GUI interaction, and it is particularly strong at long-form multimedia tasks that combine speech, sound, and visual context. It also supports two-channel and four-channel spatial audio understanding.

텍스트컨텍스트 1MUS$0.15 / US$0.47
Qwen3.8 Max

Qwen3.8 Max 0902 is an updated snapshot of Qwen3.8 Max from Alibaba's Qwen team. It is a 2.4-trillion-parameter mixture-of-experts model that accepts text, image, and video input and returns text, with a 1M-token context window and reasoning enabled by default.

This snapshot is post-trained for coding and agentic work, including multi-step software projects, multi-tool orchestration, and long-horizon task execution. It also targets chart reasoning, document parsing, and multimodal understanding over long documents and extended video. Tool calling, structured outputs, and configurable reasoning effort are supported.

텍스트컨텍스트 1MUS$2 / US$6
Qwen3.8 Flash

Qwen3.8 Flash is a multimodal reasoning model from Alibaba. It is suited for coding assistance, agentic workflows, visual understanding, document and codebase analysis, desktop interaction, chart analysis, and long-video analysis.

텍스트컨텍스트 1MUS$0.15 / US$0.47
Qwen3 Reranker 0.6B

Qwen3 Reranker 0.6B is the smallest text reranking model from Alibaba Cloud in the Qwen3 Reranker series. Built on the Qwen3 architecture, it evaluates query-document pairs to produce relevance scores for retrieval and RAG pipelines. Supports 100+ languages with instruction-aware reranking. Designed for low-latency, resource-constrained deployments.

재순위 지정
Qwen3 Reranker 4B

Qwen3 Reranker 4B is a text reranking model from Alibaba Cloud built on the Qwen3 architecture. It evaluates query-document pairs to produce relevance scores for use in retrieval and RAG pipelines. Supports 100+ languages and programming languages, with instruction-aware reranking that allows customizing scoring criteria per task. A compact 4B alternative balancing performance and inference cost.

재순위 지정
Qwen3.8 27B

Qwen3.8 27B is an open-weight dense vision-language model from Qwen. It is suited for coding, professional workflows, research, multimodal interaction, and long-running agent tasks, with flexible thinking that can be enabled or disabled.

텍스트컨텍스트 1MUS$0.039 / US$1.25
Qwen3 Reranker 8B

Qwen3 Reranker 8B is a text reranking model from Alibaba Cloud built on the Qwen3 architecture. It evaluates query-document pairs to produce relevance scores for use in retrieval and RAG pipelines. Supports 100+ languages and programming languages, with instruction-aware reranking that allows customizing scoring criteria per task. Offers strong performance on multilingual benchmarks including MTEB, CMTEB, and MMTEB.

재순위 지정US$0.20/M tokens
Qwen3 ASR 1.7B

Qwen3 ASR 1.7B is an automatic speech recognition model from Qwen. It supports multilingual language identification and transcription across 30 languages and 22 Chinese dialects, with streaming and offline inference plus segment-level and word-level timestamps.

음성 전사US$0.000008/second
Qwen3 ASR 0.6B

Qwen3 ASR 0.6B is a compact automatic speech recognition model from Qwen. It supports multilingual language identification and transcription across 30 languages and 22 Chinese dialects, with streaming and offline inference plus segment-level and word-level timestamps.

음성 전사US$0.000003/second
Qwen3.8 2.4T A95B

Qwen3.8 2.4T A95B is an open-weight sparse mixture-of-experts model from Qwen and the open-weight variant of Qwen3.8 Max, with 95 billion active parameters out of 2.4 trillion total. It is suited for coding, research, complex reasoning, and agentic workflows.

텍스트컨텍스트 1.0MUS$2 / US$6
Qwen Image 3 Pro

Qwen Image 3 Pro is an image generation and editing model from Qwen. It supports precise rendering of text and details as small as 10px, along with richer world knowledge compared to previous generations.

이미지from US$0.04/image
Qwen Image 3

Qwen Image 3 is a unified image generation and editing model from Qwen. It supports precise rendering of text and details as small as 10px, along with a richer world knowledge base than previous generations.

이미지from US$0.03/image
Qwen3.8 Max

Qwen3.8 Max (0803) is the August 3, 2026 checkpoint of Qwen3.8 Max, the flagship model in Alibaba's Qwen3.8 series and the general-availability successor to the Qwen3.8 Max Preview. It is a multimodal reasoning model intended for complex reasoning, visual understanding, coding, and agentic workflows. This checkpoint was superseded by Qwen3.8 Max (0902) on September 5, 2026.

텍스트컨텍스트 1M
Qwen3.7 Flash

Qwen3.7 Flash is a vision-language reasoning model from Alibaba. It is suited for multimodal agents, visual coding, search, and computer interaction, with strengths in object recognition, spatial understanding, and real-world visual perception.

텍스트컨텍스트 1MUS$0.03 / US$0.13
Qwen-Audio-3.0-TTS Flash

Qwen-Audio-3.0-TTS Flash is Alibaba's fast, cost-efficient text-to-speech model, generating spoken audio from text via the DashScope Speech Synthesizer API.

음성US$15/M characters
Qwen-Audio-3.0-TTS Plus

Qwen-Audio-3.0-TTS Plus is Alibaba's higher-quality text-to-speech model, generating spoken audio from text via the DashScope Speech Synthesizer API.

음성US$20/M characters
Qwen3.7 Plus

Qwen3.7-Plus is a cost-effective model in Alibaba's Qwen3.7 series. It supports text and image input with text output, building on the series' text capabilities with a comprehensive upgrade to its vision-language abilities while retaining full-stack, agent-level intelligence for coding, tool use, and productivity workflows. Its distinguishing trait is multi-modal interactive hybrid agent capability: it can perceive real-world scenes, read screens and interact with GUIs, generate code from visual references, and perform end-to-end navigation within mobile apps.

텍스트컨텍스트 1MUS$0.32 / US$1.28
Qwen3.7 Max

Qwen3.7-Max is the flagship model in Alibaba's Qwen3.7 series. It supports text input and output and is designed for agent-centric workloads, with particular strengths in coding, office and productivity tasks, and long-horizon autonomous execution. The model offers notable gains in coding and agentic performance over prior Qwen generations and supports explicit prompt caching for efficient repeated context use.

텍스트컨텍스트 1MUS$1.475 / US$4.425
Qwen3 ASR Flash

Qwen3-ASR-Flash is Alibaba's automatic speech recognition service, built on the Qwen3-Omni foundation and trained on tens of millions of hours of multimodal speech data. The model handles 11 languages — including Chinese (with Cantonese, Sichuanese, Minnan, and Wu dialects), English, Arabic, French, German, Spanish, Italian, Portuguese, Russian, Japanese, and Korean — with automatic language detection so no manual configuration is needed for mixed-language audio.

The model is designed for difficult acoustic conditions: it transcribes lyrics over background music, handles noisy and far-field recordings, filters silence and non-speech audio, and accepts arbitrary context text (names, jargon, domain terminology) to bias recognition toward specific vocabulary.

음성 전사