Qwen: Qwen3.5-9B

Temporarily unavailable

qwen/qwen3.5-9b

0 live providers

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. It uses a unified vision-language design with early fusion of multimodal tokens, allowing the model to process and reason across text and images within the same context.

Context: 64K; tokens
Max output: 32K; tokens
Input: $0.18; per million tokens
Output: $0.54; per million tokens

Providers

Ranked by price and speed. Requests go to the best healthy provider, then fail over down the list.

#	Provider	Input	Output	Cache read	Latency	Throughput	Uptime (3d)
1	Prime IntellectNon-EUPaused Data policy not declared	$0.18	$0.54	$0.018	n/a	n/a	66.7%

n/a: not enough traffic to show yet.

Want to serve this model?Become a provider

Price history

No price changes since Oct 21, 2026.

Prime Intellect$0.18 in, $0.54 out

Performance

Last 24 hours on llm.buzz traffic

Not enough traffic to show yet.

Uptime

Last 72 hours, by hour

With failover

Prime Intellect

Up: 95% or more served
Degraded: 85% to 95%
Down: below 85%
No data
From llm.buzz's test requests

Questions

How much does Qwen: Qwen3.5-9B cost?

Qwen: Qwen3.5-9B costs $0.18 per million input tokens and $0.54 per million output tokens at Prime Intellect, its first provider, paused for now, with cache reads at $0.018 per million tokens.

Do providers train on my prompts?

Each provider declares it, and the table above shows every declaration. You can limit a request to providers that keep nothing, or to providers in the EU.

Can I serve Qwen: Qwen3.5-9B myself?

Yes. Apply as a provider, add your endpoint and list this model at your price. It goes live once the automated check passes.

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Call it

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.llm.buzz/api/v1",
    api_key=os.environ["LLM_BUZZ_KEY"],
)
reply = client.chat.completions.create(
    model="qwen/qwen3.5-9b",
    messages=[{"role": "user", "content": "Hello"}],
)

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.llm.buzz/api/v1",
  apiKey: process.env.LLM_BUZZ_KEY,
});
const reply = await client.chat.completions.create({
  model: "qwen/qwen3.5-9b",
  messages: [{ role: "user", content: "Hello" }],
});

curl https://api.llm.buzz/api/v1/chat/completions \
  -H "Authorization: Bearer $LLM_BUZZ_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "qwen/qwen3.5-9b",
       "messages": [{"role": "user", "content": "Hello"}]}'

Endpoints

POST /api/v1/chat/completionsPOST /api/v1/responsesPOST /api/v1/messages

Authentication

Send your llm.buzz key as a Bearer token: Authorization: Bearer $LLM_BUZZ_KEY. Create keys in the console. The same key calls every model; each request pays the price of the provider that answered it.

More in Authentication and the API reference.

Call Qwen: Qwen3.5-9B with one keyEach request pays the price of the provider that answered it.

Get API key