Arize AI: Arize AI Qwen 2 1.5B Instruct
arize-ai/qwen-2-1.5b-instruct
Access Arize AI Qwen 2 1.5B Instruct from Arize AI using Puter.js AI API.
Get Started// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms", {
model: "arize-ai/qwen-2-1.5b-instruct"
}).then(response => {
document.body.innerHTML = response.message.content;
});
<html>
<body>
<script src="https://js.puter.com/v2/"></script>
<script>
puter.ai.chat("Explain quantum computing in simple terms", {
model: "arize-ai/qwen-2-1.5b-instruct"
}).then(response => {
document.body.innerHTML = response.message.content;
});
</script>
</body>
</html>
# pip install openai
from openai import OpenAI
client = OpenAI(
base_url="https://api.puter.com/puterai/openai/v1/",
api_key="YOUR_PUTER_AUTH_TOKEN",
)
response = client.chat.completions.create(
model="arize-ai/qwen-2-1.5b-instruct",
messages=[
{"role": "user", "content": "Explain quantum computing in simple terms"}
],
)
print(response.choices[0].message.content)
curl https://api.puter.com/puterai/openai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_PUTER_AUTH_TOKEN" \
-d '{
"model": "arize-ai/qwen-2-1.5b-instruct",
"messages": [
{"role": "user", "content": "Explain quantum computing in simple terms"}
]
}'
Model Card
Arize AI Qwen 2 1.5B Instruct is a compact instruction-tuned chat model published by Arize AI, an LLM observability and evaluation company, built on Alibaba's Qwen2 1.5B Instruct base.
The underlying Qwen2 1.5B is a small, efficient 1.5B-parameter transformer that punches above its size on standard benchmarks, scoring 52.4 on MMLU, 61.6 on GSM8K, and 37.8 on HumanEval, well ahead of its predecessor.
Its low cost and small footprint make it well suited to high-volume, latency-sensitive workloads such as classification, structured extraction, and evaluation or scoring tasks where a large model would be overkill.
Choose it when you want an inexpensive, responsive model for lightweight chat and structured tasks rather than complex reasoning.
Context Window 33K
tokens
Max Output 33K
tokens
Input Cost $0.1
per million tokens
Output Cost $0.1
per million tokens
Input text
modalities
Tool Use Yes
Knowledge Cutoff Sep 2024
Release Date Jun 2024
Model Playground
Try Arize AI Qwen 2 1.5B Instruct instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
Frequently Asked Questions
You can access Arize AI Qwen 2 1.5B Instruct by Arize AI through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required. You can also use it with Python or cURL via Puter's OpenAI-compatible API.
Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Arize AI Qwen 2 1.5B Instruct to your app at no cost — your users pay for their own AI usage directly, making it completely free for you as a developer.
| Price per 1M tokens | |
|---|---|
| Input | $0.1 |
| Output | $0.1 |
Arize AI Qwen 2 1.5B Instruct was created by Arize AI and released on Jun 2024.
Arize AI Qwen 2 1.5B Instruct supports a context window of 33K tokens. For reference, that is roughly equivalent to 66 pages of text.
Arize AI Qwen 2 1.5B Instruct can generate up to 33K tokens in a single response.
Arize AI Qwen 2 1.5B Instruct has a knowledge cutoff date of Sep 2024. This means the model was trained on data available up to that date.
Arize AI Qwen 2 1.5B Instruct accepts the following input types: text. It produces: text.
Yes, Arize AI Qwen 2 1.5B Instruct supports tool use (function calling), allowing it to interact with external tools, APIs, and data sources as part of its response flow.
Yes — the Arize AI Qwen 2 1.5B Instruct API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.
Get started with Puter.js
Add Arize AI Qwen 2 1.5B Instruct to your app without worrying about API keys or setup.
Read the Docs View Tutorials