identity

open weights
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qwen3.8-27bAlibaba (Qwen)

from /1M in$0.20deepinfra
context262K131K out
providers11 region
endpoints11 region
endpoints
1
regions
1
api
chat
released
August 2026

capabilities 5/8

visionreasoningtoolscachingweb searchjson schemacomputer useimage gen

endpoints

1 / 1 region
Providers serving qwen3.8-27b, with pricing and measured performance. Best value in each column is coloured.
#flags
1DeepInfraGlobal262K$0.20$2.50$0.05zdr
provider price, no markupper 1M tokensblank where no qualifying sample

measured

through Nov 2

no measured traffic for this model yet. the endpoints table above carries provider pricing

benchmarks

artificial analysis
Benchmark scores, each normalised to 100
evalScore as a share of 100/100
GPQA Diamond90.5
SciCode46.6
Humanity's Last Exam33.9
Intelligence Index20.1
4 evalsmean47.8

Scores from Artificial Analysis and public leaderboards, normalised to 100. Bar colour is the band, not the rank: green 80 and up, blue 55 and up, amber 30 and up. Benchmarks measure narrow skills, so test on your own workload before committing. Released 2026-08-14.

call it

model=
deepinfra/qwen3.8-27b

this model has no managed policy yet, so call the provider endpoint directly. every id in the endpoints table works the same way

Base url is https://router.requesty.ai/v1 for every id here. One key reaches the whole catalog.

quickstart

openai compatible
main.py
from openai import OpenAI client = OpenAI(    api_key="YOUR_REQUESTY_API_KEY",    base_url="https://router.requesty.ai/v1",) response = client.chat.completions.create(    model="deepinfra/qwen3.8-27b",    messages=[        {"role": "user", "content": "Explain quantum computing in one paragraph."},    ],) print(response.choices[0].message.content)

Change the base url, use your Requesty key, set the model to any id in the call pane. Existing OpenAI SDK code needs no other edit, and the same key reaches every other model in the catalog, so switching later is a one-parameter change. Browse all models

notes

reference

Qwen3.8-27B is an open weight dense vision language model from Qwen, built on the Qwen3.5 architecture. It understands images and video, offers flexible thinking control, and is suited for coding, professional work, research, and long horizon agentic tasks. Compact and deployment friendly with a 262K native context.

questions 5

Which providers serve qwen3.8-27b?
qwen3.8-27b is available from 1 provider through Requesty: DeepInfra. All endpoints share one OpenAI-compatible API and one key, and Requesty fails over between them automatically.
How much does qwen3.8-27b cost?
Pricing starts at $0.20 per million input tokens and $2.50 per million output tokens on the cheapest provider. Prices vary by provider and region; the table above shows every endpoint. Requesty charges exactly what the upstream provider charges, with no markup.
Is qwen3.8-27b open weights?
Yes. qwen3.8-27b is an open-weights model from Alibaba (Qwen), which is why multiple inference providers can host it. Provider choice affects price, latency, and data-privacy terms, all compared above.
What is the context window of qwen3.8-27b?
qwen3.8-27b supports up to 262K tokens of context, with up to 131K output tokens per response. Some providers expose a smaller window; check the per-endpoint context column above.
How do I use qwen3.8-27b with the OpenAI SDK?
Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "deepinfra/qwen3.8-27b" or any endpoint id from the table above. The quickstart section shows Python, JavaScript and cURL snippets.

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route qwen3.8-27b through one endpoint

One key for 1 provider on this model and 600+ others. No markup on provider prices, automatic failover, caching built in. Weekly aggregates in the measured pane come from production traffic routed through Requesty, one line per provider on a shared axis. Methodology

qwen3.8-27b1 provider1 endpointsfrom $0.20 /1M inctx 262Kupdated Nov 2