codestral-embed-2505Mistral Codestral Embed is an embedding model specialized for code, ideal for indexing repositories and powering coding assistants with high-quality code retrieval.
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from openai import OpenAI client = OpenAI( api_key="YOUR_API_KEY", base_url="https://api.apertis.ai/v1") response = client.chat.completions.create( model="codestral-embed-2505", 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="codestral-embed-2505",# messages=[{"role": "user", "content": "Hello!"}],# extra_body={"compression": {"enabled": True, "model": "gpt-4.1-mini"}}# )modelinputencoding_formatdimensionsuserUse these namespaced identifiers in Cursor IDE to avoid conflicts with built-in models.
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Mistral Small 4 is the latest release in the Mistral Small family, unifying capabilities from multiple flagship models into a single system. It integrates strong reasoning (Magistral), multimodal understanding (Pixtral), and agentic coding capabilities (Devstral), enabling a versatile, all-in-one model. Designed to handle complex analysis, software development, and visual tasks within the same workflow, Mistral Small 4 is well suited for integrated agentic applications and end-to-end problem solving across domains.
Initialized observational baseline with no recorded failures