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Favicon de qwen

Qwen: Qwen3.8 27B (batch)

qwen/qwen3.8-27b:batch

Pesos do modelo
Comparar

Qwen3.8 27B (batch) is served by 1 provider and supports chamada de ferramentas, structured outputs e raciocínio.

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.

Modalidades
In / out price
US$ 0,16 / US$ 2por 1M
Contexto
262K
Lançado
14 de ago. de 2026
Comparar
ProvedoresPreçosDesempenhoDisponibilidadeAvaliações de desempenhoAplicativosAtividadePerguntas frequentesExplorar

Provedores

Diferentes empresas hospedam o mesmo modelo. O OpenRouter encaminha sua solicitação para uma delas com base no modo de roteamento que você escolhe — Equilibrado (preço + velocidade), Nitro (mais rápido) ou Floor (mais barato).

Preços

O preço médio que os clientes realmente pagam por este modelo, ao lado dos preços publicados pelos provedores. O cache e os descontos fazem com que o preço efetivamente pago seja frequentemente bem inferior ao preço anunciado.

Desempenho

A vazão indica a velocidade com que o modelo escreve (tokens por segundo — quanto maior, melhor). A latência é o tempo total de ida e volta (quanto menor, melhor). TTFT é o tempo até o primeiro token — quanto tempo leva para você ver algo aparecer (quanto menor, melhor).

Disponibilidade

A disponibilidade é a porcentagem dos últimos 3 dias em que pelo menos um provedor estava respondendo às solicitações. A disponibilidade é a porcentagem de tempo em que a inferência foi realizada com sucesso. O OpenRouter monitora continuamente e usa o próximo melhor provedor quando um deles retorna um erro.

Avaliações de desempenho

Pontuações em avaliações padronizadas e as próprias saídas deste modelo para prompts compartilhados de testes de desempenho. Porcentagens maiores são melhores — e cada posição mostra onde este modelo fica entre os modelos avaliados naquela fonte.

Resumo das pontuações de avaliações comparativas para Qwen: Qwen3.8 27B (batch) (Artificial Analysis e Vals AI)
FonteAvaliação comparativaPontuação
Artificial AnalysisQwen3.8 27B (Non-reasoning) Intelligence Index10,0
Artificial AnalysisQwen3.8 27B (Non-reasoning) Coding Index44,6
Artificial AnalysisQwen3.8 27B (Non-reasoning) Agentic Index22,4
Artificial AnalysisQwen3.8 27B (Non-reasoning) GPQA Diamond81.8%
Artificial AnalysisQwen3.8 27B (Non-reasoning) HLE12.1%
Artificial AnalysisQwen3.8 27B (Non-reasoning) AA-LCR69.3%
Artificial AnalysisQwen3.8 27B (Non-reasoning) τ-Bench Banking20.0%
Artificial AnalysisQwen3.8 27B (Non-reasoning) GDPval-AA29.1%
Artificial AnalysisQwen3.8 27B (Non-reasoning) CritPt0.3%
Artificial AnalysisQwen3.8 27B (Non-reasoning) SciCode36.2%
Artificial AnalysisQwen3.8 27B (Non-reasoning) Terminal-Bench 4.00.0%
Artificial AnalysisQwen3.8 27B (Non-reasoning) Terminal-Bench 2.149.1%
Artificial AnalysisQwen3.8 27B (Non-reasoning) AA-Omniscience Accuracy9.1%
Artificial AnalysisQwen3.8 27B (Non-reasoning) AA-Omniscience Non-Hallucination Rate82.0%
Artificial AnalysisQwen3.8 27B (Xhigh) Intelligence Index20,1
Artificial AnalysisQwen3.8 27B (Xhigh) Coding Index68,1
Artificial AnalysisQwen3.8 27B (Xhigh) Agentic Index45,8
Artificial AnalysisQwen3.8 27B (Xhigh) GPQA Diamond90.5%
Artificial AnalysisQwen3.8 27B (Xhigh) HLE33.9%
Artificial AnalysisQwen3.8 27B (Xhigh) AA-LCR82.0%
Artificial AnalysisQwen3.8 27B (Xhigh) τ-Bench Banking48.0%
Artificial AnalysisQwen3.8 27B (Xhigh) GDPval-AA46.3%
Artificial AnalysisQwen3.8 27B (Xhigh) CritPt5.4%
Artificial AnalysisQwen3.8 27B (Xhigh) SciCode46.6%
Artificial AnalysisQwen3.8 27B (Xhigh) Terminal-Bench 4.05.6%
Artificial AnalysisQwen3.8 27B (Xhigh) Terminal-Bench 2.179.8%
Artificial AnalysisQwen3.8 27B (Xhigh) AA-Omniscience Accuracy17.3%
Artificial AnalysisQwen3.8 27B (Xhigh) AA-Omniscience Non-Hallucination Rate71.4%
Artificial AnalysisQwen3.8 27B (Low) Intelligence Index15,7
Artificial AnalysisQwen3.8 27B (Low) Coding Index58,2
Artificial AnalysisQwen3.8 27B (Low) Agentic Index38,9
Artificial AnalysisQwen3.8 27B (Low) GPQA Diamond84.5%
Artificial AnalysisQwen3.8 27B (Low) HLE14.0%
Artificial AnalysisQwen3.8 27B (Low) AA-LCR77.3%
Artificial AnalysisQwen3.8 27B (Low) τ-Bench Banking32.2%
Artificial AnalysisQwen3.8 27B (Low) GDPval-AA43.5%
Artificial AnalysisQwen3.8 27B (Low) CritPt0.0%
Artificial AnalysisQwen3.8 27B (Low) SciCode40.0%
Artificial AnalysisQwen3.8 27B (Low) Terminal-Bench 4.02.5%
Artificial AnalysisQwen3.8 27B (Low) Terminal-Bench 2.167.4%
Artificial AnalysisQwen3.8 27B (Low) AA-Omniscience Accuracy18.3%
Artificial AnalysisQwen3.8 27B (Low) AA-Omniscience Non-Hallucination Rate51.3%
Artificial AnalysisQwen3.8 27B (Medium) Intelligence Index17,5
Artificial AnalysisQwen3.8 27B (Medium) Coding Index56,1
Artificial AnalysisQwen3.8 27B (Medium) Agentic Index44,4
Artificial AnalysisQwen3.8 27B (Medium) GPQA Diamond84.5%
Artificial AnalysisQwen3.8 27B (Medium) HLE14.1%
Artificial AnalysisQwen3.8 27B (Medium) AA-LCR79.7%
Artificial AnalysisQwen3.8 27B (Medium) τ-Bench Banking47.4%
Artificial AnalysisQwen3.8 27B (Medium) GDPval-AA44.4%
Artificial AnalysisQwen3.8 27B (Medium) CritPt0.0%
Artificial AnalysisQwen3.8 27B (Medium) SciCode39.0%
Artificial AnalysisQwen3.8 27B (Medium) Terminal-Bench 4.05.1%
Artificial AnalysisQwen3.8 27B (Medium) Terminal-Bench 2.165.2%
Artificial AnalysisQwen3.8 27B (Medium) AA-Omniscience Accuracy17.9%
Artificial AnalysisQwen3.8 27B (Medium) AA-Omniscience Non-Hallucination Rate34.6%
Vals AIQwen 3.8 27B Code Migration14.2%
Vals AIQwen 3.8 27B CyberBench v1.167.8%
Vals AIQwen 3.8 27B EMB59.7%
Vals AIQwen 3.8 27B Finance Agent (v2)48.6%
Vals AIQwen 3.8 27B GPQA Diamond88.9%
Vals AIQwen 3.8 27B Harvey's Legal Agent Benchmark v111.3%
Vals AIQwen 3.8 27B IOI39.1%
Vals AIQwen 3.8 27B LiveCodeBench84.0%
Vals AIQwen 3.8 27B LegalBench82.4%
Vals AIQwen 3.8 27B Legal Research Bench36.1%
Vals AIQwen 3.8 27B MedCode28.7%
Vals AIQwen 3.8 27B MedScribe83.8%
Vals AIQwen 3.8 27B MMLU Pro84.3%
Vals AIQwen 3.8 27B MMMU Pro83.9%
Vals AIQwen 3.8 27B MortgageTax64.9%
Vals AIQwen 3.8 27B ProgramBench0.0%
Vals AIQwen 3.8 27B ProofBench v1.116.0%
Vals AIQwen 3.8 27B SAGE v152.4%
Vals AIQwen 3.8 27B SkillsBench38.1%
Vals AIQwen 3.8 27B SWE-bench86.0%
Vals AIQwen 3.8 27B Tax Agent Bench30.9%
Vals AIQwen 3.8 27B TaxEval v270.8%
Vals AIQwen 3.8 27B Terminal-Bench 2.158.4%
Vals AIQwen 3.8 27B Terminal-Bench-Science0.0%
Vals AIQwen 3.8 27B Vals Index48.5%
Vals AIQwen 3.8 27B Vibe Code Bench v1.164.8%

Aplicativos

Aplicativos públicos que enviam mais tráfego para este modelo. Um bom indicador de como são as cargas de trabalho reais em produção — e uma pista sobre os casos de uso para os quais este modelo é mais adequado.

Atividade

Volume de tokens e tráfego de requisições para este modelo ao longo do tempo.

API

Código pronto para chamar este modelo. A API do OpenRouter é compatível com a OpenAI — a maioria dos SDKs funciona apenas trocando a URL base. A única coisa que muda entre os modelos é o slug do modelo abaixo.

Atualmente indisponível por meio do roteamento intrarregional da UE. Documentação de roteamento na região

Explorar mais modelos

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    Entrada US$ 0,16 / Saída US$ 2,00
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Avaliações de desempenho do AutoExacto
GPQA DiamondTAU-BenchStreamLake84,9%--DekaLLM83,4%78,0%PrimeIntellect83,2%78,0%Mancer 282,2%78,6%Parasail83,5%77,2%
+20 provedores adicionais

Ainda não há dados de disponibilidade suficientes para exibição.

Quando ocorre um erro em um provedor upstream, podemos nos recuperar roteando para outro provedor saudável, se os filtros da sua solicitação permitirem. Você pode acessar os dados de disponibilidade por provedor de forma programática pela API de endpoints. Saiba mais sobre nossas opções de balanceamento de carga e roteamento de provedores.

Ainda não há dados suficientes sobre aplicativos que usam este modelo.

Perguntas frequentes

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.

Qwen3.8 27B (batch) custa US$ 0,16/M de tokens de entrada e US$ 2,00/M de tokens de saída, com taxas separadas para Cache Read por US$ 0,04/M tokens.

Qwen3.8 27B (batch) tem uma janela de contexto de 262.144 tokens.

Sim. Qwen3.8 27B (batch) aceita tools e tool_choice para chamadas de função. Também oferece suporte a saídas estruturadas por meio de um esquema JSON em response_format.

Qwen3.8 27B (batch) aceita texto, imagens e vídeo como entrada e retorna texto.

Qwen3.8 Max Prime, Qwen3.8 Omni Flash, Qwen3.8 Max (0902) e mais 37 são outros modelos de texto de Qwen.

Qwen3.8 27B (batch) foi lançado em 14 de agosto de 2026.

Mais modelos de Qwen

Qwen Image 2.1 Turbo

Qwen Image 2.1 Turbo is the fast, lower-cost tier of the Qwen Image 2.1 series from Qwen, for image generation and editing where throughput and price matter more than peak fidelity. See Qwen Image 2.1 Pro for the higher-quality tier.

Imagemfrom US$ 0,0184/image
Qwen Image 2.1 Pro

Qwen Image 2.1 Pro is an image generation and editing model from Qwen, the higher-quality tier of the Qwen Image 2.1 series. Choose it over Qwen Image 2.1 Turbo when output fidelity matters more than cost or speed.

Imagemfrom US$ 0,046/image
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.

TextoContexto de 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.

TextoContexto de 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.

TextoContexto de 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.

TextoContexto de 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.

Reclassificação
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.

Reclassificação
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.

TextoContexto de 1,0MUS$ 0,035 / US$ 1,50
Qwen3.8 27B (batch)

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.

TextoContexto de 262KUS$ 0,16 / US$ 2
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.

ReclassificaçãoUS$ 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.

TranscriçãoUS$ 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.

TranscriçãoUS$ 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.

TextoContexto de 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.

Imagemfrom 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.

Imagemfrom 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.

TextoContexto de 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.

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Qwen-Audio-3.0-TTS Flash

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FalaUS$ 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.

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