aisingapore · Open weights
Qwen SEA-LION v4 32B
AI Singapore’s Qwen-based multilingual model, adapted for Southeast Asian languages and cultural contexts. Supports text chat and tool calling with a 128K context window.
- Tools
- Input
- Text
- Output
- Text
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $0.30
- Output
- $0.60
Reference prices as published by the model provider. API example
Specifications
- Context window
- 131.1K
- Max output
- —
Side by side
Qwen SEA-LION v4 32B compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Qwen SEA-LION v4 32BaisingaporeThis model | Qwen3.5 27B TEEQwenRemove | |
|---|---|---|
| Provider | aisingapore | Qwen |
| Discovery tier | Open weights | Open weights |
| Added | Oct 15, 2026 | Mar 13, 2026 |
| Limits | ||
| Context window | 131.07K | 262.14KBest |
| Max output | — | 65.54K |
| Average output | — | 1.4K tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.30 | $0.30 |
| Output | $0.60Best | $2.40 |
| Benchmark indexes | ||
| Intelligence Index | — | 22.9 |
| Capabilities | ||
| Tools | Yes | No |
| Vision | No | Yes |
| Video input | No | Yes |
| Reasoning effort | — | — |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- Qwen SEA-LION v4 32B
- Qwen3.5 27B TEE
Intelligence Index
- Qwen SEA-LION v4 32B—
- Qwen3.5 27B TEE22.9
Document reasoning
AA-LCRv1.1
Reasoning across long documents
- Qwen SEA-LION v4 32B: —
- Qwen3.5 27B TEE: 77.7%
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Qwen SEA-LION v4 32B: —
- Qwen3.5 27B TEE: 23.9%
GPQA Diamond
Graduate-level science questions
- Qwen SEA-LION v4 32B: —
- Qwen3.5 27B TEE: 85.8%
IFBench
Following precise output instructions
- Qwen SEA-LION v4 32B: —
- Qwen3.5 27B TEE: 75.6%
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- Qwen SEA-LION v4 32B: —
- Qwen3.5 27B TEE: 32.6%
τ²-Bench Telecom
Tool use in a customer-support simulation
- Qwen SEA-LION v4 32B: —
- Qwen3.5 27B TEE: 93.9%
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Qwen SEA-LION v4 32B: —
- Qwen3.5 27B TEE: 77.7%
Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis
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": "aisingapore/qwen-sea-lion-v4-32b-it",
"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="aisingapore/qwen-sea-lion-v4-32b-it",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)aisingapore
Related models
Other aisingapore models, starting with the same family.