Models / Chat / DeepSeek R1 Distilled Qwen 1.5B API
DeepSeek R1 Distilled Qwen 1.5B API
Chat
Reasoning
Small Qwen 1.5B distilled with reasoning capabilities from Deepseek R1. Beats GPT-4o on MATH-500 whilst being a fraction of the size.
Try our DeepSeek R1 Distilled Qwen 1.5 API
API Usage
How to use DeepSeek R1 Distilled Qwen 1.5BModel CardPrompting DeepSeek R1 Distilled Qwen 1.5BApplications & Use CasesHow to use DeepSeek R1 Distilled Qwen 1.5BDeepSeek R1 Distilled Qwen 1.5B API Usage
Endpoint
deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
RUN INFERENCE
curl -X POST "https://api.together.xyz/v1/chat/completions" \
-H "Authorization: Bearer $TOGETHER_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B",
"messages": [],
"stream": true
}'JSON RESPONSE
RUN INFERENCE
from together import Together
client = Together()
response = client.chat.completions.create(
model="deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B",
messages=[],
stream=True
)
for token in response:
if hasattr(token, 'choices'):
print(token.choices[0].delta.content, end='', flush=True)JSON RESPONSE
RUN INFERENCE
import Together from "together-ai";
const together = new Together();
const response = await together.chat.completions.create({
messages: [],
model: "deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B",
stream: true
});
for await (const token of response) {
console.log(token.choices[0]?.delta?.content)
}JSON RESPONSE
Model Provider:
DeepSeek
Type:
Chat
Variant:
Distilled
Parameters:
1.5B
Deployment:
✔ Serverless
✔️ On-Demand Dedicated
Quantization
FP16
Context length:
Pricing:
$0.18
Check pricing
Run in playground
Deploy model
Quickstart docs
Quickstart docs
How to use DeepSeek R1 Distilled Qwen 1.5B
Model details
Prompting DeepSeek R1 Distilled Qwen 1.5B
Applications & Use Cases
How to use DeepSeek R1 Distilled Qwen 1.5B
Looking for production scale? Deploy on a dedicated endpoint
Deploy DeepSeek R1 Distilled Qwen 1.5B on a dedicated endpoint with custom hardware configuration, as many instances as you need, and auto-scaling.
