How much does Qwen3.5 9B cost?

On the Respan gateway, Qwen3.5 9B costs from $0.09 per 1M input tokens and $0.13 per 1M output tokens on EmpirioLabs, after gateway discounts. Averaged across its 6 providers, it costs $0.13 per 1M input tokens and $0.21 per 1M output tokens.

Which providers serve Qwen3.5 9B on Respan?

Qwen3.5 9B is available through 6 providers: EmpirioLabs, DeepInfra, Parasail, Featherless, OpenRouter, and TogetherAI.

What is Qwen3.5 9B's context window?

Qwen3.5 9B accepts up to 262K tokens of context on its largest provider route.

How do I use Qwen3.5 9B with the Respan gateway?

Point any OpenAI-compatible SDK at https://api.respan.ai/api/ with your Respan API key and set the model to "qwen3.5-9b". To set it up with a coding agent, copy the agent setup prompt at the top of this page.

Where does Qwen3.5 9B rank on the Respan Index?

Qwen3.5 9B scores 20.5 out of 100 on the Respan Index v1.1, ranking #115 of 161 models. By category: Coding 2.8, Agents 23.0, Reasoning 23.4, Knowledge & language 14.6, and Human preference 44.6 (estimated). The Respan Index combines independent and lab-reported benchmark results into one score, using benchmark data collected by Respan.

How does Qwen3.5 9B score on benchmarks?

Qwen3.5 9B has 19 published benchmark scores, including LiveCodeBench v6 65.6%, TAU2-Bench 79.1%, and GPQA Diamond 81.7%. Each score links to where it was published; the data is collected by Respan.

Qwen3.5 9B

Q: What is Qwen3.5 9B?

Qwen3.5 9B is a model from Qwen, released on Mar 2, 2026. Qwen3.5-9B is a multimodal foundation model from the Qwen3.5 family, designed to deliver strong reasoning, coding, and visual understanding in an efficient 9B-parameter architecture.

Qwen3.5-9B is a multimodal foundation model from the Qwen3.5 family, designed to deliver strong reasoning, coding, and visual understanding in an efficient 9B-parameter architecture.

Input / output, from: $0.09 / $0.13 per 1M
Context: 262K tokens
Released: Mar 2, 2026

Try Respan for free

Agent setup

Paste into Claude Code, Cursor, or Codex

Help me set up the Respan gateway: fetch and follow https://www.respan.ai/docs/agent-setup.md. Use model "qwen3.5-9b".

from openai import OpenAI

client = OpenAI(

    base_url="https://api.respan.ai/api/",

    api_key="YOUR_RESPAN_API_KEY",

)

response = client.chat.completions.create(

    model="qwen3.5-9b",

    messages=[{"role": "user", "content": "Hello!"}],

)

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

import OpenAI from "openai";

const client = new OpenAI({

  baseURL: "https://api.respan.ai/api/",

  apiKey: "YOUR_RESPAN_API_KEY",

});

const response = await client.chat.completions.create({

  model: "qwen3.5-9b",

  messages: [{ role: "user", content: "Hello!" }],

});

console.log(response.choices[0].message.content);

curl https://api.respan.ai/api/chat/completions \

  -H "Authorization: Bearer YOUR_RESPAN_API_KEY" \

  -H "Content-Type: application/json" \

  -d '{

    "model": "qwen3.5-9b",

    "messages": [{"role": "user", "content": "Hello!"}]

}'

Read docs

Providers

6 providers, cheapest first, priced per 1M tokens after gateway discounts.

Provider	Context	Input	Output	Cache read
EmpirioLabs`empiriolabs/qwen3-5-9b`	262K	$0.09/M	$0.13/M	$0.04/M
DeepInfra`deepinfra/Qwen/Qwen3.5-9B`	262K	$0.10/M	$0.15/M	$0.00/M
Parasail`parasail/qwen/qwen3.5-9b`	262K	$0.10/M	$0.25/M	$0.00/M
Featherless`featherless_ai/Qwen/Qwen3.5-9B`	33K	$0.17/M	$0.25/M	$0.30/M
OpenRouter`openrouter/qwen/qwen3.5-9b`	262K	$0.17/M	$0.25/M	$0.04/M
TogetherAI`together_ai/Qwen/Qwen3.5-9B`	262K	$0.17/M	$0.25/M	$0.01/M

Is a provider down? OpenRouter status, Together AI status

Pricing

Averaged across 6 providers, in USD per 1M tokens after gateway discounts.

Average input: $0.13 per 1M
Average output: $0.21 per 1M
Average cache read: $0.07 per 1M

Cost by volume

Total cost from 0 to 1T tokens on the cheapest and most expensive provider.

Highest$0.17/MFeatherless, OpenRouter, and TogetherAILowest$0.09/MEmpirioLabs

Throughput and latency

30-day averages from requests through the Respan gateway. Under each figure, every model on the gateway by its average, this one in blue.

Output speed

Higher is better

39tokens/sacross providers

Faster than 51% of the other 470 models on the gateway

Response latency

Lower is better

3.7sacross providers

Faster than 38% of the other 495 models on the gateway

Benchmarks

The Respan Index plus 19 published scores from 3 sources, each linked to where it was published.

20.5/ 100

Respan Index#115 of 161

161 ranked models. The shaded band is this model's 95% interval, 14.7 to 29.3. DeepSeek V3.1-Terminus and Grok 4 Fast Reasoning fall inside it, so the gap is within the margin of error.

115Qwen3.5 9B20.5
114DeepSeek V3.1-Terminus20.6
116Grok 4 Fast Reasoning20.4

Published scores

Benchmark	Score	Source	Published
LiveCodeBench v6huggingface.co	65.6%	huggingface.co	Mar 2, 2026

Benchmark	Score	Source	Published
TAU2-Benchhuggingface.co	79.1%	huggingface.co	Mar 2, 2026
BFCL-V4huggingface.co	66.1%	huggingface.co	Mar 2, 2026
OSWorld-Verifiedhuggingface.co	41.8%	huggingface.co	Mar 2, 2026

Benchmark	Score	Source	Published
GPQA Diamondhuggingface.co	81.7%	huggingface.co	Mar 2, 2026
GPQA DiamondEpoch AI	79%	Epoch AI	Oct 5, 2026
SuperGPQAhuggingface.co	58.2%	huggingface.co	Mar 2, 2026
LongBench v2huggingface.co	55.2%	huggingface.co	Mar 2, 2026
Chess PuzzlesEpoch AI	12%	Epoch AI	Oct 5, 2026

Benchmark	Score	Source	Published
AIME 2026MathArena	92.5%	MathArena	Oct 13, 2026
HMMT Feb 25huggingface.co	83.2%	huggingface.co	Mar 2, 2026
OTIS Mock AIME 2024-2025Epoch AI	61.7%	Epoch AI	Oct 5, 2026

Benchmark	Score	Source	Published
IFEvalhuggingface.co	91.5%	huggingface.co	Mar 2, 2026
MMLU-Reduxhuggingface.co	91.1%	huggingface.co	Mar 2, 2026
MMLU-Prohuggingface.co	82.5%	huggingface.co	Mar 2, 2026
MMMLUhuggingface.co	81.2%	huggingface.co	Mar 2, 2026
IFBenchhuggingface.co	64.5%	huggingface.co	Mar 2, 2026