baichuan-m2-32bBaichuan
- endpoints
- 1
- regions
- 1
- api
- chat
- released
- August 2025
capabilities 0/8
| # | flags | |||||
|---|---|---|---|---|---|---|
| 1 | Global | 131K | $0.07 | $0.07 | zdr |
no measured traffic for this model yet. the endpoints table above carries provider pricing
no published benchmark scores for this model
novita/baichuan/baichuan-m2-32bthis model has no managed policy yet, so call the provider endpoint directly. every id in the endpoints table works the same way
Base url is https://router.requesty.ai/v1 for every id here. One key reaches the whole catalog.
from openai import OpenAI client = OpenAI( api_key="YOUR_REQUESTY_API_KEY", base_url="https://router.requesty.ai/v1",) response = client.chat.completions.create( model="novita/baichuan/baichuan-m2-32b", messages=[ {"role": "user", "content": "Explain quantum computing in one paragraph."}, ],) print(response.choices[0].message.content)
Change the base url, use your Requesty key, set the model to any id in the call pane. Existing OpenAI SDK code needs no other edit, and the same key reaches every other model in the catalog, so switching later is a one-parameter change. Browse all models
Baichuan-M2 is a medically-enhanced reasoning model specifically designed for real-world medical reasoning tasks. We begin with real-world medical questions and conduct reinforcement learning training based on a large-scale verifier system. While maintaining the model's general capabilities, the medical effectiveness of Baichuan-M2 has achieved breakthrough improvements. Baichuan-M2 is currently the world's best open-source medical model. On the HealthBench Benchmark, it surpasses all open-sour
questions 5
Which providers serve baichuan-m2-32b?
How much does baichuan-m2-32b cost?
Is baichuan-m2-32b open weights?
What is the context window of baichuan-m2-32b?
How do I use baichuan-m2-32b with the OpenAI SDK?
route baichuan-m2-32b through one endpoint
One key for 1 provider on this model and 600+ others. No markup on provider prices, automatic failover, caching built in. Weekly aggregates in the measured pane come from production traffic routed through Requesty, one line per provider on a shared axis. Methodology
