Qwen · Open weights
Qwen 3 32b
Qwen 3 32b is a 32b model. 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.
- Tools
- PDF input
- Input
- Text
- Output
- Text
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $0.08
- Output
- $0.24
Reference prices as published by the model provider. API example
Specifications
- Context window
- 41K
- Max output
- 32.8K
- Average output (7 days)
- 646 tokens
- Longer than 58% of 468 models
Side by side
Qwen 3 32b compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Qwen 3 32bQwenThis model | Nvidia Nemotron Super 49BnvidiaRemove | |
|---|---|---|
| Provider | Qwen | nvidia |
| Discovery tier | Open weights | Open weights |
| Added | Jan 1, 2024 | Aug 8, 2025 |
| Limits | ||
| Context window | 41K | 128KBest |
| Max output | 32.77KBest | 16.38K |
| Average output | 646 tokens | — |
| Pricing, USD per 1M tokens | ||
| Input | $0.08Best | $0.15 |
| Output | $0.24 | $0.15Best |
| Performance | ||
| Throughput | 26.6 tok/s | — |
| Time to first token | 2.8 s | — |
| Request success (24h) | 100.0% | — |
| Benchmark indexes | ||
| Intelligence Index | 7.3 | 7.3 |
| Math Index | 19.7Best | 7.7 |
| Capabilities | ||
| Tools | Yes | No |
| PDF input | Yes | No |
| Reasoning effort | — | — |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- Qwen 3 32b
- Nvidia Nemotron Super 49B
Intelligence Index
- Qwen 3 32b7.3
- Nvidia Nemotron Super 49B7.3
Qwen 3 32b: Better than 10% of 326 scored models
Indexes
Math Index
Composite of the math evaluations
- Qwen 3 32b: 19.7Top
- Nvidia Nemotron Super 49B: 7.7
Document reasoning
AA-LCRv1.1
Reasoning across long documents
- Qwen 3 32b: 0.0%
- Nvidia Nemotron Super 49B: 12.0%Top
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Qwen 3 32b: 4.1%Top
- Nvidia Nemotron Super 49B: 3.8%
GPQA Diamond
Graduate-level science questions
- Qwen 3 32b: 53.5%Top
- Nvidia Nemotron Super 49B: 51.7%
MMLU-Pro
Multi-subject knowledge and reasoning
- Qwen 3 32b: 72.7%Top
- Nvidia Nemotron Super 49B: 69.8%
IFBench
Following precise output instructions
- Qwen 3 32b: 31.5%
- Nvidia Nemotron Super 49B: 39.5%Top
Coding
LiveCodeBench
Recent competitive programming problems
- Qwen 3 32b: 28.8%Top
- Nvidia Nemotron Super 49B: 28.0%
Math
AIME 2025
Competition mathematics, 2025 problems
- Qwen 3 32b: 19.7%Top
- Nvidia Nemotron Super 49B: 7.7%
AIME
Competition mathematics
- Qwen 3 32b: 30.3%Top
- Nvidia Nemotron Super 49B: 19.3%
MATH-500
Competition math problems
- Qwen 3 32b: 86.9%Top
- Nvidia Nemotron Super 49B: 77.5%
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- Qwen 3 32b: —
- Nvidia Nemotron Super 49B: 0.0%
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Qwen 3 32b: 0.0%
- Nvidia Nemotron Super 49B: 12.0%Top
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.
- Throughput
- 26.6 tok/s
- Faster than 17% of 263 models
- Time to first token
- 2.8 s
- Quicker than 62% of 263 models
- Prompt cache hits
- 0.0%
- Request success (24h)
- 100.0%
- 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/qwen3-32b",
"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/qwen3-32b",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Qwen
Related models
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