Requesty

qwen3.5-9b

Runware Inc./🇬🇧 UK/chat

Qwen3.5 9B is a compact hybrid-reasoning model from the Qwen3.5 family with strong coding, math, and multilingual performance for its size, a 262K token context window, tool calling, and structured output support. Served via Runware.More
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Which id to call

runware/qwen3.5-9b

This exact deployment on Runware Inc., with no routing and no failover. Send it as the model field.

Input /1M

$0.09

Runware Inc.

Output /1M

$0.13

1.4x input

Context

262K

262K output

Added

Aug 2026

chat

Capabilities 0/8

VisionReasoningTool callingCachingWeb searchJSON schemaComputer useImage generation

Provider rates

What qwen3.5-9b costs

Provider prices per 1M tokens, updated August 30, 2026.more

These are the upstream provider rates. Pay as you go adds 5%, or 0% if you bring your own keys, and there is no per-request fee. Prompt caching and routing change what you pay against these rates, not the rates themselves.

Input /1M

$0.09

Output /1M

$0.13

Cache write /1M

-

Cache read /1M

-

What a workload costs

100K input + 10K output
$0.0103
1M input + 100K output
$0.10
10M input + 1M output
$1.03

At the rates above. This endpoint does not offer prompt caching, so repeated context is billed as new input every time.

OpenAI compatible

Call it in three lines

Change the base url, use your Requesty key, set the model to runware/qwen3.5-9b. Existing OpenAI SDK code needs no other edit.

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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="runware/qwen3.5-9b",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

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

Reference

Specs and data terms

What the catalog reports for this deployment, and what the provider does with the traffic.

Context window262K tokens
Max output262K tokens
API typechat
AddedAug 2026
Model id
Data retentionNone
Used for trainingNo
Served from🇬🇧 UK
Privacy policyRunware Privacy Policy→

Released 2026-03-02

Benchmark scores

Benchmarks measure the model, not this endpoint, so they are the same wherever these weights are served.

Coding Indexcoding
28.7%

Artificial Analysis Coding Index: a composite of coding evaluations including LiveCodeBench, SciCode and Terminal-Bench.

GPQA Diamondreasoning
80.6%

Graduate-level physics, chemistry & biology questions designed to resist Googling.

Intelligence Indexreasoning
21.8%

Artificial Analysis Intelligence Index: a composite of multiple evaluations measuring overall model capability.

Scores from official model cards, Artificial Analysis and public leaderboards. They measure specific skills and do not capture every aspect of model quality, so test on your own workload.

Reference

qwen3.5-9b questions

How much does qwen3.5-9b cost?

qwen3.5-9b is priced at $0.09 per million input tokens and $0.13 per million output tokens when accessed via Requesty. Those are the upstream provider rates: pay as you go adds 5% on top, or 0% if you bring your own provider keys.

What is the context window of qwen3.5-9b?

qwen3.5-9b has a context window of 262K tokens, with a maximum output of 262K tokens per response. That's roughly 350 words of input you can fit in a single prompt.

How does qwen3.5-9b perform on benchmarks?

qwen3.5-9b scores 86.8% on τ²-Bench, 80.6% on GPQA Diamond, 28.7% on Coding Index. See the full benchmark chart above for results across MMLU Pro, GPQA Diamond, SWE-Bench Verified, HumanEval, MATH, AIME, MMMU, and LiveBench.

What can qwen3.5-9b do?

qwen3.5-9b is a text-generation model you can call through any OpenAI-compatible client by pointing base_url to Requesty.

How do I use qwen3.5-9b 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 "runware/qwen3.5-9b". The Quickstart above shows Python, JavaScript and cURL snippets.

Can I run qwen3.5-9b through Requesty?

Yes. qwen3.5-9b runs through Requesty's OpenAI-compatible API, served from Runware Inc.. You do not host the model yourself: point base_url at Requesty, set the model to "runware/qwen3.5-9b", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.

Call qwen3.5-9b through one endpoint

One key for this endpoint and 600+ other models. No markup on provider prices, automatic failover, caching built in.

All Runware Inc. models