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Alibaba

Qwen3.8 27B

About

Qwen3.8 27B is a 27B open-weight model from Alibaba. Reasoning VLM (image + video + text). It accepts text, images, and video. Context window is 256K. License is Apache-2.0. Released August 13, 2026.

  • Parameters

    27B

    Published parameter count.

  • Context window

    256K

    Tokens of context on a request.

  • License

    Apache-2.0

    License on the weights.

Pricing

Token rates are US dollars per 1M tokens. Image rates are per 1K images. Audio rates are per 1M audio seconds.

RatePrice
Input / 1M$0.35
Cached input / 1M$0.05
Output / 1M$2.55

Compare

Qwen3.8 27B is one of the catalog's chat models. The table is each model's published price, size, and context.

ModelWhat it doesPriceParametersContext
Qwen3.8 27BReasoning VLM (image + video + text)$0.35 / 1M input27B256K
Qwen3.5 0.8BMultimodal chat model with up to 64 images or one video per request.$0.08 / 1M input0.8B256K
Gemini 3.5 Flash LiteFastest and cheapest Gemini tier. Multimodal chat; emits no reasoning tokens.$0.30 / 1M input1M
Gemini 3.7 FlashNewest Gemini Flash tier with extended reasoning. Multimodal chat + native video.$0.75 / 1M input1M

Benchmarks

Published scores for Qwen3.8 27B, from the Qwen3.8 model card.

Evals
ReadingExample
QualitativeClear structure, grounded in the input
QuantitativeOmniDocBench 1.5: 91.1.
Cost and performanceLower listed rate, mid-pack latency

Methods

Methods this model serves. Payload shapes are in the docs.

MethodReturns
chatThe model's reply

Estimate cost

Estimate. An hour of video is 15 frames a minute at 256 tokens a frame, plus the audio in that request, and 500 output tokens a minute.

$197.46

Quick start

Call this model on the OpenAI-compatible gateway. The model id is already filled in.

from openai import OpenAI

client = OpenAI(
    base_url="https://gateway.vlm.run/v1/openai",
    api_key="<VLMRUN_API_KEY>",
)

response = client.chat.completions.create(
    model="qwen/qwen3.8-27b",
    messages=[{"role": "user", "content": "What is in this image?"}],
)

print(response.choices[0].message.content)

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