Models/Qwen/Qwen3-VL-235B-A22B-Instruct

Qwen3-VL 235B

ActiveUnknown

Qwen/Qwen3-VL-235B-A22B-Instruct·Qwen · Apache 2.0 · updated 2026-03-12

VisionOCRMultilingual

Overview

Vision and language in one model: documents, screenshots, charts and UI.

Use cases: Vision · OCR · Multilingual

Context262,144

Max output16,384

QuantizationFP8

Capabilities

ToolsParallel toolsStructured outputStreamReasoningCacheBatchVision

GridPort billing priceUSD / 1M tokens

UnitStandardBatch

Input tokens$0.40—

Output tokens$1.60—

Live metricslast hour

Last hour of customer requests; each metric needs at least 20 valid samples.Samples this hour: 0 for TTFT, 0 for throughput · as of 2026-10-07 00:35 EDT

TTFT p50—

Throughput p50—

Success rate—

Routes1 · single route

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://gridport.ai/v1",
    api_key=os.environ["GRIDPORT_API_KEY"],
)
stream = client.chat.completions.create(
    model="Qwen/Qwen3-VL-235B-A22B-Instruct",  # pin a version: "Qwen/Qwen3-VL-235B-A22B-Instruct@2026-03-12"
    messages=[{"role": "user", "content": "Hello"}],
    stream=True,
)
for chunk in stream:
    if chunk.choices and chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)
print()

Known limits

01Prompt cache belongs to a route: a failover to the backup route starts with a cold cache.02Rate limits apply per organization, project and key, and per model where one is set; the strictest applies.03Streaming responses carry usage in the final chunk only when stream_options.include_usage is set.

Versions

VersionStatusReleasedRetires

2026-03-12defaultActive2026-03-12—