Qwen · Open weights
Qwen3 30B A3B
Qwen 3 30b A3B is a 30b model with 3 billion active parameters per pass. Supports switching between thinking and non thinking: trigger thinking with /think and /no_think anywhere in a prompt or system message to toggle chain-of-thought reasoning.
- Input
- Text
- Output
- Text
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $0.10
- Output
- $0.30
Reference prices as published by the model provider. API example
Specifications
- Context window
- 41K
- Max output
- 32.8K
- Average output (7 days)
- 228 tokens
- Longer than 24% of 465 models
Side by side
Qwen3 30B A3B compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Qwen3 30B A3BQwenThis model | Qwen 3.8 27B NovelistQwenRemove | |
|---|---|---|
| Provider | Qwen | Qwen |
| Discovery tier | Open weights | Open weights |
| Added | Feb 27, 2025 | Oct 5, 2026 |
| Limits | ||
| Context window | 41K | 262.14KBest |
| Max output | 32.77K | 32.77K |
| Average output | 228 tokens | 745 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.10 | $0.10 |
| Output | $0.30Best | $0.60 |
| Cache read | — | $0.05 |
| Performance | ||
| Throughput | — | 35.0 tok/s |
| Time to first token | — | 3.1 s |
| Request success (24h) | 99.2%Best | 98.2% |
| Benchmark indexes | ||
| Intelligence Index | 6.6 | — |
| Math Index | 21.7 | — |
| Capabilities | ||
| Reasoning | No | Yes |
| Tools | No | Yes |
| Vision | No | Yes |
| Reasoning effort | — | — |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- Qwen3 30B A3B
- Qwen 3.8 27B Novelist
Intelligence Index
- Qwen3 30B A3B6.6
- Qwen 3.8 27B Novelist—
Qwen3 30B A3B: Better than 5% of 326 scored models
Indexes
Math Index
Composite of the math evaluations
- Qwen3 30B A3B: 21.7
- Qwen 3.8 27B Novelist: —
Document reasoning
AA-LCRv1.1
Reasoning across long documents
- Qwen3 30B A3B: 0.0%
- Qwen 3.8 27B Novelist: —
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Qwen3 30B A3B: 4.6%
- Qwen 3.8 27B Novelist: —
GPQA Diamond
Graduate-level science questions
- Qwen3 30B A3B: 51.5%
- Qwen 3.8 27B Novelist: —
MMLU-Pro
Multi-subject knowledge and reasoning
- Qwen3 30B A3B: 71.0%
- Qwen 3.8 27B Novelist: —
IFBench
Following precise output instructions
- Qwen3 30B A3B: 31.9%
- Qwen 3.8 27B Novelist: —
Coding
LiveCodeBench
Recent competitive programming problems
- Qwen3 30B A3B: 32.2%
- Qwen 3.8 27B Novelist: —
Math
AIME 2025
Competition mathematics, 2025 problems
- Qwen3 30B A3B: 21.7%
- Qwen 3.8 27B Novelist: —
AIME
Competition mathematics
- Qwen3 30B A3B: 26.0%
- Qwen 3.8 27B Novelist: —
MATH-500
Competition math problems
- Qwen3 30B A3B: 86.3%
- Qwen 3.8 27B Novelist: —
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- Qwen3 30B A3B: 6.8%
- Qwen 3.8 27B Novelist: —
τ²-Bench Telecom
Tool use in a customer-support simulation
- Qwen3 30B A3B: 22.2%
- Qwen 3.8 27B Novelist: —
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Qwen3 30B A3B: 0.0%
- Qwen 3.8 27B Novelist: —
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.
- Request success (24h)
- 99.2%
- Reliable
- 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/qwen3-30b-a3b",
"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/qwen3-30b-a3b",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Qwen
Related models
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