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Codestral Embed

modelactiveprovisionalcodestral-embed-2424b899·3 events·first seen 15d ago

Aliases: Codestral Embed

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More like this (12)

Recent events (3)

6Mistral Ai News·15d ago·source ↗

Mistral AI Releases Codestral Embed: First Code-Specialized Embedding Model

Mistral AI has launched Codestral Embed (codestral-embed-2505), its first embedding model specialized for code retrieval and semantic understanding. The model claims to outperform leading competitors including Voyage Code 3, Cohere Embed v4.0, and OpenAI's large embedding model across benchmarks including SWE-Bench, CodeSearchNet, and Text2SQL tasks. It supports variable output dimensions and precisions (including int8), enabling storage/quality trade-offs, and is priced at $0.15 per million tokens via Mistral's API with batch discounts available.

7Mistral Ai News·15d ago·source ↗

Mistral Announces Codestral 25.08 and Integrated Enterprise Coding Stack

Mistral AI has released Codestral 25.08, a code generation model update claiming +30% accepted completions, 50% fewer runaway generations, and improved FIM benchmark performance. The announcement also frames a full enterprise coding stack comprising Codestral (completion), Codestral Embed (code-specific retrieval), and Devstral (agentic workflows via OpenHands), all deployable on-prem or in VPC environments. Devstral Medium is reported to achieve 61.6% on SWE-Bench Verified, while Devstral Small (24B, Apache-2.0) reaches 53.6%. The pitch targets regulated industries blocked by SaaS-only competitors through self-hostable, air-gapped deployment options.

7Mistral Ai News·15d ago·source ↗

Mistral AI Launches Mistral Code: Enterprise AI Coding Assistant with On-Prem Deployment

Mistral AI has announced Mistral Code, an enterprise-grade AI coding assistant currently in private beta for JetBrains IDEs and VSCode. The product bundles four specialized models (Codestral, Codestral Embed, Devstral, Mistral Medium) with an IDE plugin, admin controls, and deployment options ranging from serverless to air-gapped on-premises GPUs. It is built on a fork of the open-source Continue project with enterprise additions including RBAC, audit logging, and fine-tuning on private repositories. Early enterprise adopters include Abanca, SNCF (4,000 developers), and Capgemini (1,500+ developers).