Qwen · Open weights
Qwen3.5 9B
Qwen3.5 9B is a multimodal foundation model from the Qwen 3.5 family, built for efficient reasoning, coding, and visual understanding in a compact 9B architecture. Requests containing video cost $0.17 per million input tokens and $0.25 per million output tokens.
- Reasoning
- Tools
- Vision
- Video input
- Input
- Text, Images, Video
- Output
- Text
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $0.05
- Output
- $0.15
Reference prices as published by the model provider. API example
Specifications
- Context window
- 262.1K
- Max output
- 65.5K
- Average output (7 days)
- 1.4K tokens
- Longer than 84% of 465 models
Side by side
Qwen3.5 9B compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Qwen3.5 9BQwenThis model | Qwen 3.8 27B KiwenQwenRemove | |
|---|---|---|
| Provider | Qwen | Qwen |
| Discovery tier | Open weights | Open weights |
| Added | Mar 10, 2026 | Oct 5, 2026 |
| Limits | ||
| Context window | 262.14K | 262.14K |
| Max output | 65.54KBest | 32.77K |
| Average output | 1.4K tokens | 222 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.05Best | $0.10 |
| Output | $0.15Best | $0.60 |
| Cache read | — | $0.05 |
| Performance | ||
| Request success (24h) | 99.8%Best | 94.4% |
| Benchmark indexes | ||
| Intelligence Index | 13.3 | — |
| Coding Index | 23.5 | — |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | Yes |
| Vision | Yes | Yes |
| Video input | Yes | No |
| Reasoning effort | — | — |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- Qwen3.5 9B
- Qwen 3.8 27B Kiwen
Intelligence Index
- Qwen3.5 9B13.3
- Qwen 3.8 27B Kiwen—
Qwen3.5 9B: Better than 33% of 326 scored models
Indexes
Coding Index
Composite of the coding evaluations
- Qwen3.5 9B: 23.5
- Qwen 3.8 27B Kiwen: —
Document reasoning
AA-LCRv1.1
Reasoning across long documents
- Qwen3.5 9B: 46.0%
- Qwen 3.8 27B Kiwen: —
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Qwen3.5 9B: 9.4%
- Qwen 3.8 27B Kiwen: —
GPQA Diamond
Graduate-level science questions
- Qwen3.5 9B: 78.6%
- Qwen 3.8 27B Kiwen: —
IFBench
Following precise output instructions
- Qwen3.5 9B: 37.8%
- Qwen 3.8 27B Kiwen: —
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- Qwen3.5 9B: 18.2%
- Qwen 3.8 27B Kiwen: —
τ²-Bench Telecom
Tool use in a customer-support simulation
- Qwen3.5 9B: 85.1%
- Qwen 3.8 27B Kiwen: —
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Qwen3.5 9B: 46.0%
- Qwen 3.8 27B Kiwen: —
Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis
Live routing data
Performance and reliability
Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.
- Prompt cache hits
- 14.3%
- Request success (24h)
- 99.8%
- Reliable
Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.
- Healthy (98% or more)
- Degraded (90–98%)
- Down (under 90%)
- No requests
Developers
Use it through the API
Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.
curl https://www.noumen.xyz/api/v1/chat/completions \
-H "Authorization: Bearer $NOUMEN_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "qwen/qwen3.5-9b",
"messages": [{ "role": "user", "content": "Explain this stack trace." }]
}'import os
from openai import OpenAI
client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
model="qwen/qwen3.5-9b",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Qwen
Related models
Other Qwen models, starting with the same family.