Qwen3.8 27B

Qwen3.8 27B is an open-weight dense vision-language model from Alibaba's Qwen3.8 family, suited to coding, professional workflows, research, and long-running agent tasks.

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input · usd / 1m tok

$0.50

output · usd / 1m tok

$3.00

context window

1.05mtokens

modalities · in → out

pricing

base api ratesusd per 1m tokens

input: $0.50
output: $3.00
cache read: $0.10

providers

Different companies host Qwen3.8 27B. Impossibl routes your request intelligently and handles failover automatically when a provider is down.

Qwen
Groq

specifications

takes text and image in, gives text outqwen/qwen3.8-27b

creatorQwen
model typeText generation
context window1,048,576 tokens
maximum outputnot published
input
takes text and image in, gives text out
outputtext
tool callingnot verified
releasedaug 14, 2026
endpoint/v1/chat/completions

unknown means the public catalog does not establish that fact. a model's documented capabilities can differ from what a particular api supports. see the model documentation for integration details.

try it · your prompt, this model, live

# responses API
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["IMPOSSIBL_API_KEY"],
    base_url="https://api.impossibl.com/v1",
)

resp = client.responses.create(
    model="qwen/qwen3.8-27b",
    input="▌",
)
print(resp.output_text)

edit the prompt, then run

# responses API
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["IMPOSSIBL_API_KEY"],
    base_url="https://api.impossibl.com/v1",
)

resp = client.responses.create(
    model="qwen/qwen3.8-27b",
    input="▌",
)
print(resp.output_text)

edit the prompt, then run

benchmarks

intelligence index

20.1#29 of 35 models on the gateway

coding index68.1#31 of 59
agentic index45.8#13 of 52

Intelligence Index20.11
legal index (API)34.6
coding index (API)68.1
agentic index (API)45.8
economics index (API)42.8
engineering index (API)33.3
intelligence index (API)33.7
strategy and ops index (API)37.1
finance and accounting index (API)34.3
healthcare and medical index (API)34.4

view source ↗all source data and breakdowns (json) ↗

each configuration is listed separately; these evaluations describe the tested model configuration, and performance and costs can differ on impossibl. unmeasured scores are omitted and api values keep their source units. last checked 2026-11-03. some source data could not be refreshed; retained results may be older.

compare Qwen3.8 27B with other models

frontier labs and open weights, best-ranked firstusd / 1m tok · in / out

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frequently asked questions

What is Qwen3.8 27B?

Qwen3.8 27B is an open-weight dense vision-language model from Alibaba's Qwen3.8 family, suited to coding, professional workflows, research, and long-running agent tasks. It builds on Qwen3.6 27B with gains in coding and office productivity, and offers flexible thinking control via reasoning effort and preserved thinking.

How much does Qwen3.8 27B cost?

Qwen3.8 27B costs $0.50 per million input tokens and $3.00 per million output tokens through the Impossibl API. Cache reads cost $0.10 per million tokens. All rates are in USD.

view the pricing table ↑

What is the context length of Qwen3.8 27B?

Qwen3.8 27B has a 1,048,576-token context window through the Impossibl API.

What inputs and outputs does Qwen3.8 27B support?

Qwen3.8 27B accepts text and image as input. Qwen3.8 27B returns text.

How do I use Qwen3.8 27B through an API?

Qwen3.8 27B is available through the Impossibl API. Use qwen/qwen3.8-27b as the model identifier with /v1/chat/completions. The quickstart explains how to create an API key and send your first request.

follow the api quickstart →

When was Qwen3.8 27B released?

Qwen released Qwen3.8 27B on August 14, 2026.

Creator release announcement ↗

this page describes Qwen3.8 27B as listed by the impossibl public api. prices and availability come from that catalog, refreshed here every five minutes. this is an impossibl offering, not a comparison of independent hosting-provider quotes. model descriptions and release dates, where available, use the creator sources linked under the answers above.

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