qwen/qwen3-vl-235b-a22b-instruct
262,144 context · $0.30/M input tokens · $1.50/M output tokens
Qwen3-VL-235B-A22B Instruct is an open-weight multimodal model that unifies strong text generation with visual understanding across images and video. The Instruct model targets general vision-language use (VQA, document parsing, chart/table...
Pay-per-Use
Keine Vorabkosten, zahlen Sie nur, was Sie nutzen
Verwenden Sie die folgenden Codebeispiele zur Integration mit unserer API:
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://llm.wavespeed.ai/v1"
)
response = client.chat.completions.create(
model="qwen/qwen3-vl-235b-a22b-instruct",
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)Qwen3-VL-235B-A22B Instruct is an open-weight multimodal model that unifies strong text generation with visual understanding across images and video
Qwen3-VL-235B-A22B Instruct is an open-weight multimodal model that unifies strong text generation with visual understanding across images and video. The Instruct model targets general vision-language use (VQA, document parsing, chart/table extraction, multilingual OCR). The series emphasizes robust perception (recognition of diverse real-world and synthetic categories), spatial understanding (2D/3D grounding), and long-form visual comprehension, with competitive results on public multimodal benchmarks for both perception and reasoning.
Beyond analysis, Qwen3-VL supports agentic interaction and tool use: it can follow complex instructions over multi-image, multi-turn dialogues; align text to video timelines for precise temporal queries; and operate GUI elements for automation tasks. The models also enable visual coding workflows—turning sketches or mockups into code and assisting with UI debugging—while maintaining strong text-only performance comparable to the flagship Qwen3 language
| Specification | Value |
|---|---|
| Provider | Qwen |
| Model Type | Large Language Model (LLM) |
| Architecture | N/A |
| Context Window | 262144 tokens |
| Max Output | tokens |
| Input | Text |
| Output | Text |
| Vision | Supported |
| Function Calling | Supported |
| Token Type | Cost per Million Tokens |
|---|---|
| Input | $0.2 |
| Output | $0.10 |
Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: qwen/qwen3-vl-235b-a22b-instruct
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://llm.wavespeed.ai/v1"
)
response = client.chat.completions.create(
model="qwen/qwen3-vl-235b-a22b-instruct",
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)
curl https://llm.wavespeed.ai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "qwen/qwen3-vl-235b-a22b-instruct",
"messages": [{"role": "user", "content": "Hello!"}]
}'
qwen/qwen3-vl-235b-a22b-instruct
Qwen3-VL-235B-A22B Instruct is an open-weight multimodal model that unifies strong text generation with visual understanding across images and video. The Instruct model targets general vision-language use (VQA, document parsing, chart/table...
Eingabe
$0.3 /M
Ausgabe
$1.5 /M
Kontext
262K
Vision
Unterstützt
Tool-Nutzung
Unterstützt
Zugriff auf Qwen3 Vl 235b A22b Instruct über unsere einheitliche API — OpenAI-kompatibel, keine Kaltstarts, transparente Preise.
Preise auf WaveSpeedAI: $0.30 pro Million Input-Tokens und $1.50 pro Million Output-Tokens. Prompt-Caching und Batch-Verarbeitung werden separat berechnet und reduzieren die effektiven Kosten bei langen, sich wiederholenden Workloads.
Qwen3 Vl 235b A22b Instruct unterstützt bis zu 262K Kontext-Tokens und bis zu — Output-Tokens pro Anfrage.
Ja. WaveSpeedAI stellt Qwen3 Vl 235b A22b Instruct über einen OpenAI-kompatiblen Endpunkt unter https://llm.wavespeed.ai/v1 bereit. Richten Sie das offizielle OpenAI SDK mit Ihrem WaveSpeedAI-API-Schlüssel auf diese Base-URL — keine weiteren Codeänderungen erforderlich.
Bei WaveSpeedAI anmelden, in Access Keys einen API-Schlüssel erstellen und eine Anfrage an https://llm.wavespeed.ai/v1/chat/completions mit der oben angezeigten Model-ID senden. Neue Konten erhalten kostenlose Credits, um Qwen3 Vl 235b A22b Instruct zu testen.