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 | GPT 5.1OpenAIRemove | |
|---|---|---|
| Provider | Qwen | OpenAI |
| Discovery tier | Open weights | Frontier |
| Added | Mar 10, 2026 | Nov 13, 2025 |
| Limits | ||
| Context window | 262.14K | 400KBest |
| Max output | 65.54K | 128KBest |
| Average output | 1.4K tokens | 294 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.05Best | $1.25 |
| Output | $0.15Best | $10.00 |
| Cache read | — | $0.13 |
| Performance | ||
| Request success (24h) | 99.8% | 100.0%Best |
| Benchmark indexes | ||
| Intelligence Index | 13.3 | 13.3 |
| Coding Index | 23.5 | — |
| Math Index | — | 38.0 |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | Yes |
| Vision | Yes | Yes |
| Structured output | No | Yes |
| PDF input | No | Yes |
| Video input | Yes | No |
| Reasoning effort | — | none, low, medium, high |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- Qwen3.5 9B
- GPT 5.1
Intelligence Index
- Qwen3.5 9B13.3
- GPT 5.113.3
Qwen3.5 9B: Better than 33% of 326 scored models
Indexes
Coding Index
Composite of the coding evaluations
- Qwen3.5 9B: 23.5
- GPT 5.1: —
Math Index
Composite of the math evaluations
- Qwen3.5 9B: —
- GPT 5.1: 38.0
Document reasoning
AA-LCRv1.1
Reasoning across long documents
- Qwen3.5 9B: 46.0%Top
- GPT 5.1: 45.0%
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Qwen3.5 9B: 9.4%Top
- GPT 5.1: 5.3%
GPQA Diamond
Graduate-level science questions
- Qwen3.5 9B: 78.6%Top
- GPT 5.1: 64.3%
MMLU-Pro
Multi-subject knowledge and reasoning
- Qwen3.5 9B: —
- GPT 5.1: 80.1%
IFBench
Following precise output instructions
- Qwen3.5 9B: 37.8%
- GPT 5.1: 43.2%Top
Coding
LiveCodeBench
Recent competitive programming problems
- Qwen3.5 9B: —
- GPT 5.1: 49.4%
Math
AIME 2025
Competition mathematics, 2025 problems
- Qwen3.5 9B: —
- GPT 5.1: 38.0%
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- Qwen3.5 9B: 18.2%
- GPT 5.1: 22.7%Top
τ²-Bench Telecom
Tool use in a customer-support simulation
- Qwen3.5 9B: 85.1%Top
- GPT 5.1: 46.5%
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Qwen3.5 9B: 46.0%Top
- GPT 5.1: 45.0%
Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis
- Qwen3.5 9B
- GPT 5.1
| Leaderboard | Qwen3.5 9B | GPT 5.1 |
|---|---|---|
| Vision Style Control · Creative Writing | Not in top 20 | #3 · 1284.6 |
| Vision Style Control · Captioning | Not in top 20 | #4 · 1248.2 |
| Vision Style Control · Entity Recognition | Not in top 20 | #11 · 1228.2 |
Ranks among Noumen catalog models on LMArena leaderboards. Only top-20 placements are listed.LMArena
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.