Use this model when
- The workload fits the text or chat tasks shown in this model's current catalog record.
- The input fits within the published 41.0K-token context record, with output and system overhead budgeted separately.
magistral-medium-2506:thinkingMagistral Medium 2506 (Thinking) by Mistral AI.
Select an endpoint and copy a working example for this model.
from openai import OpenAI client = OpenAI( api_key="YOUR_API_KEY", base_url="https://api.apertis.ai/v1") response = client.chat.completions.create( model="magistral-medium-2506:thinking", 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="magistral-medium-2506:thinking",# messages=[{"role": "user", "content": "Hello!"}],# extra_body={"compression": {"enabled": True, "model": "gpt-4.1-mini"}}# )modelmessagesmax_tokenstemperaturetop_pstreamtoolsreasoning_effortstream_optionsthinkingextra_bodyUse these namespaced identifiers in Cursor IDE to avoid conflicts with built-in models.
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No observed failures in the current observation window