Qwen/Qwen3-VL-4B-Instruct
Open-weights chat model from Alibaba Cloud Model Studio. One API key reaches this provider and every other model in the catalog.
No card required. Start with 1 million free tokens.
About Qwen/Qwen3-VL-4B-Instruct
Qwen/Qwen3-VL-4B-Instruct is an open-weights chat model published by Alibaba Cloud Model Studio, with a 32,768-token context window. Through TrustedRouter it runs on 1 provider, with options in the US, from $0.42 per million input tokens. One provider offers zero data retention.
- Model ID
qwen/qwen3-vl-4b-instruct- Publisher
- Alibaba Cloud Model Studio
- Modes
- chat
- Billing
- Credits
Set it up with your agent
Paste this into Claude Code, Cursor or any coding agent.
Use Qwen/Qwen3-VL-4B-Instruct through TrustedRouter in this project.
1. Read https://trustedrouter.com/llms.txt
2. Point the OpenAI-compatible client at
https://api.trustedrouter.com/v1 and read the key from
TRUSTEDROUTER_API_KEY.
3. Set the model to qwen/qwen3-vl-4b-instruct.
4. Run the tests, then show me the diff before committing.import os
from openai import OpenAI
client = OpenAI(
base_url="https://api.trustedrouter.com/v1",
api_key=os.environ["TRUSTEDROUTER_API_KEY"],
)
response = client.chat.completions.create(
model="qwen/qwen3-vl-4b-instruct",
messages=[{"role": "user", "content": "What is the capital of France?"}],
)
print(response.choices[0].message.content)curl https://api.trustedrouter.com/v1/chat/completions \
-H "Authorization: Bearer $TRUSTEDROUTER_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "qwen/qwen3-vl-4b-instruct",
"messages": [{"role": "user", "content": "What is the capital of France?"}]
}'Providers
Open the row for retention, location and weight format, or see how we check privacy claims and the live speed leaderboard.
| Provider | Input | Cached | Output | Cost per 1M in + out | Details |
|---|---|---|---|---|---|
Featherless AI
Zero retention
|
$0.422 | — | $0.844 | $1.27 | |
|
Retention Zero data retention. Featherless's published privacy policy states that prompts and completions are neither collected nor stored. Account, payment and usage metadata, including token counts and sampler settings, may be retained. This is policy-backed ZDR, not verified confidential compute or E2EE. Location Operator country: US Headquarters / registered office: Not verified. Inference: Inference location not verified; no country-specific residency commitment. No inference-location declaration has been verified for this provider. Region pinning through TR: No verified provider-specific location pin documented here. Weight format Unknown Price and speed Input $0.422/1M · Cached input Not published · Output $0.844/1M TTFT: insufficient data Speed: insufficient data Last sample: |
|||||
Questions
What model ID should I use for Qwen/Qwen3-VL-4B-Instruct?
Use qwen/qwen3-vl-4b-instruct as the model field with the TrustedRouter OpenAI-compatible API. Credits routing and provider fallback happen behind that model ID.
Do you log my prompts or outputs?
No. Prompt and output content are intentionally excluded from the control plane and metadata systems. Optional content export requires explicit destination-level configuration.
Which providers serve Qwen/Qwen3-VL-4B-Instruct?
TrustedRouter currently lists Featherless AI for Qwen/Qwen3-VL-4B-Instruct. Provider availability and routing eligibility can change as catalog and health data update.
How much does Qwen/Qwen3-VL-4B-Instruct cost through TrustedRouter?
The current lowest Credits input price is $0.422/1M and the lowest Credits output price is $0.844/1M. Prices are per one million tokens and come from the current route catalog.
How do I require zero data retention for Qwen/Qwen3-VL-4B-Instruct?
Set provider.min_privacy to zdr on the request. TrustedRouter considers only routes with a recorded zero-data-retention posture and fails closed if no eligible route remains.
Qwen/Qwen3-VL-4B-Instruct vs other models
Start building with Qwen/Qwen3-VL-4B-Instruct.
No card required. Start with 1 million free tokens.