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Favicon für qwen

Qwen: Qwen3.8 27B (batch)

qwen/qwen3.8-27b:batch

Modellgewichte
Vergleich

Qwen3.8 27B (batch) is served by 1 provider and supports Tool-Aufrufe, structured outputs und Schlussfolgern.

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.

Modalitäten
In / out price
0,16 $ / 2 $pro 1 Mio.
Kontext
262K
Veröffentlicht
14. Aug. 2026
Vergleich
AnbieterPreiseLeistungVerfügbarkeitLeistungsvergleicheAppsAktivitätFAQEntdecken

Anbieter

Verschiedene Unternehmen hosten dasselbe Modell. OpenRouter leitet Ihre Anfrage je nach gewähltem Routing-Modus an eines davon weiter — Balanced (Preis + Geschwindigkeit), Nitro (am schnellsten) oder Floor (am günstigsten).

Preise

Der durchschnittliche Preis, den Kunden tatsächlich für dieses Modell zahlen, neben den von Anbietern veröffentlichten Preisen. Durch Caching und Rabatte liegt der tatsächlich gezahlte Preis oft deutlich unter dem Listenpreis.

Leistung

Der Durchsatz gibt an, wie schnell das Modell schreibt (Token pro Sekunde – höher ist besser). Die Latenz ist die gesamte Umlaufzeit (niedriger ist besser). TTFT ist die Zeit bis zum ersten Token – also die Wartezeit, bis etwas angezeigt wird (niedriger ist besser).

Verfügbarkeit

Verfügbarkeit ist der prozentuale Anteil der letzten 3 Tage, in dem mindestens ein Anbieter auf Anfragen reagiert hat. Die Verfügbarkeit der Inferenz ist der prozentuale Anteil der Zeit, in der Inferenz erfolgreich bereitgestellt wurde. OpenRouter überwacht dies kontinuierlich und verwendet den nächstbesten Anbieter, wenn ein Anbieter einen Fehler zurückgibt.

Leistungsvergleiche

Ergebnisse standardisierter Bewertungen und eigene Ausgaben dieses Modells zu gemeinsamen Vergleichstest-Prompts. Höhere Prozentwerte sind besser – und jeder Rang zeigt, wo dieses Modell unter den anhand dieser Quelle bewerteten Modellen liegt.

Zusammenfassung der Benchmark-Ergebnisse für Qwen: Qwen3.8 27B (batch) (Artificial Analysis und Vals AI)
QuelleBenchmarkErgebnis
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%

Apps

Öffentliche Apps, die den meisten Datenverkehr an dieses Modell senden. Ein guter Anhaltspunkt dafür, wie echte Produktionsworkloads aussehen – und ein Hinweis darauf, für welche Anwendungsfälle dieses Modell am besten geeignet ist.

Aktivität

Token-Volumen und Anfrageaufkommen für dieses Modell im Zeitverlauf.

API

Direkt einsetzbarer Code zum Aufrufen dieses Modells. Die API von OpenRouter ist OpenAI-kompatibel – bei den meisten SDKs genügt es, die Basis-URL auszutauschen. Zwischen den Modellen ändert sich nur der unten stehende Modell-Slug.

Derzeit nicht über EU-regionales Routing verfügbar. Dokumentation zum regionsinternen Routing

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GPQA DiamondTAU-BenchStreamLake84,9 %--DekaLLM83,4 %78,0 %PrimeIntellect83,2 %78,0 %Mancer 282,2 %78,6 %Parasail83,5 %77,2 %
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Noch nicht genügend Daten zur Verfügbarkeit für eine Anzeige vorhanden.

Wenn bei einem vorgelagerten Anbieter ein Fehler auftritt, können wir diesen durch die Weiterleitung an einen anderen funktionsfähigen Anbieter beheben, sofern Ihre Anfragefilter dies zulassen. Sie können programmgesteuert auf die Verfügbarkeitsdaten pro Anbieter zugreifen, und zwar über die Endpunkt-API. Erfahren Sie mehr über unsere Optionen für Lastverteilung und Anbieter-Routing.

Für Apps, die dieses Modell verwenden, liegen noch nicht genügend Daten vor.

Häufig gestellte Fragen

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) kostet 0,16 $/M Eingabe-Token und 2,00 $/M Ausgabe-Token, mit separaten Tarifen für Cache Read für 0,04 $/M tokens.

Qwen3.8 27B (batch) hat ein Kontextfenster von 262.144 Token.

Ja. Qwen3.8 27B (batch) akzeptiert tools und tool_choice für Funktionsaufrufe. Es unterstützt auch strukturierte Ausgaben über ein JSON-Schema in response_format.

Qwen3.8 27B (batch) akzeptiert Text, Bilder und Video als Eingabe und gibt Text zurück.

Qwen3.8 Max Prime, Qwen3.8 Omni Flash, Qwen3.8 Max (0902) und 37 weitere sind weitere Modelle von Qwen für die Modalität Text.

Qwen3.8 27B (batch) wurde am 14. August 2026 veröffentlicht.

Weitere Modelle von 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.

Bildfrom 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.

Bildfrom 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.

Text1M Kontext4 $ / 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.

Text1M Kontext0,15 $ / 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.

Text1M Kontext2 $ / 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.

Text1M Kontext0,15 $ / 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.

Neubewertung
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.

Neubewertung
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.

Text1,0M Kontext0,035 $ / 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.

Text262K Kontext0,16 $ / 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.

Neubewertung0,20 $/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.

Transkription0,000008 $/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.

Transkription0,000003 $/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.

Text1,0M Kontext2 $ / 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.

Bildfrom 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.

Bildfrom 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.

Text1M Kontext
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.

Text1M Kontext0,03 $ / 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.

Sprache15 $/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.

Sprache20 $/M characters