RerankerChat
Qwen3 Reranker 4B
Qwen/Qwen3-Reranker-4BQwen3 Reranker 4B by Reranker.
- Context
- 8.2K tokens
- Endpoint
Pricing
Input$0.28 / 1M
Output$0.28 / 1M
Cache Write$0 / 1M
Cache Read$0 / 1M
Web Search$0 / 1M
Prompt cache writes and reads are included at no additional cost.
Quick Start
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Endpoint:
python
from openai import OpenAI client = OpenAI( api_key="YOUR_API_KEY", base_url="https://api.apertis.ai/v1") response = client.chat.completions.create( model="Qwen/Qwen3-Reranker-4B", messages=[ {"role": "user", "content": "Hello!"} ], max_tokens=1024, temperature=0.7) print(response.choices[0].message.content) # Optional: Enable context compression to reduce token usage# response = client.chat.completions.create(# model="Qwen/Qwen3-Reranker-4B",# messages=[{"role": "user", "content": "Hello!"}],# extra_body={"compression": {"enabled": True, "model": "gpt-4.1-mini"}}# )Supported Parameters
API docsCommon4 params
modelquerydocumentstop_nExtended2 params
return_documentsmax_chunks_per_docCursor IDE Model IDs
Use these namespaced identifiers in Cursor IDE to avoid conflicts with built-in models.
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