agent · LLM

Mistral Small 3

mistral.aiupdated Aug 1, 2026view as JSON

15 fields evidenced · 40 with no public information. Every value below links to the document it came from and the date we checked it.

Assurance

Insurance available: no public information
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Insurance carriers: no public information
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Coverage limits: no public information
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Indemnification: no public information
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Liability cap: no public information
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Audit trail: no public information
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Tamper-evident log: no public information
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Explainability: no public information
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Runtime governance: no public information
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Permission scopes: no public information
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Compliance certifications: no public information
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Regulatory alignment: no public information
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Outcome-based pricing: no public information
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Settlement mechanism: no public information
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Dispute process: no public information
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SLA terms: no public information
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Evaluation coverage: Yes (evaluated on 1k proprietary prompts)
“We conducted side by side evaluations with an external third-party vendor, on a set of over 1k proprietary coding and generalist prompts.”
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Agency

Autonomy level: no public information
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Human oversight: no public information
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Goal complexity: no public information
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Action space: no public information
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Operating environment: no public information
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Initiative: no public information
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Safety

Safety evaluations: Side-by-side evaluations with external third-party vendor on 1k prompts
“We conducted side by side evaluations with an external third-party vendor, on a set of over 1k proprietary coding and generalist prompts.”
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Red teaming: no public information
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Safety policy: no public information
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Usage restrictions: no public information
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Model or system card: no public information
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Incident reporting: no public information
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Third-party evaluations: Yes (external third-party vendor)
“We conducted side by side evaluations with an external third-party vendor”
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Data handling: no public information
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Practicality

Pricing model: no public information
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Price point: no public information
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Availability: Introduced (available)
“Today we’re introducing Mistral Small 3”
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Deployment options: serverless API, on-prem, VPC, local deployment
“model weights will be available to download and deploy locally, and free to modify and use in any capacity. These models will also be made available through a serverless API on la Plateforme , through our on-prem and VPC deployments”
mistral.ai · checked Aug 1, 2026
Integrations: Hugging Face, Ollama, Kaggle, Together AI, Fireworks AI, IBM Watson X, NVIDIA NIM, Amazon SageMaker, Groq, Databricks, Snowflake
“We are also excited to collaborate with Hugging Face, Ollama, Kaggle, Together AI, and Fireworks AI to make the model available on their platforms starting today: Hugging Face ( base model ) Ollama Kaggle Together AI Fireworks AI IBM Watson X Coming soon on NVIDIA NIM, Amazon SageMaker, Groq, Databricks and Snowflake”
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Supported regions: no public information
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Support model: no public information
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Foundation models

Base models: no public information
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Model provider: Mistral AI
“Mistral Small 3 | Mistral AI”
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Model swappable: no public information
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Open weights: Yes (Apache 2.0 license)
“We’re releasing both a pretrained and instruction-tuned checkpoint under Apache 2.0.”
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Fine-tuning: Yes
“Fine-tuning to create subject matter experts: Mistral Small 3 can be fine-tuned to specialize in specific domains”
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Context window: no public information
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Ecosystem

Protocols supported: no public information
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Tool use: Function calling
“Low-latency function calling: Mistral Small 3 is able to handle rapid function execution when used as part of automated or agentic workflows.”
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Multi-agent: no public information
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API access: Yes (serverless API on la Plateforme)
“These models will also be made available through a serverless API on la Plateforme”
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Open source: Apache 2.0
“released under the Apache 2.0 license”
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Marketplace presence: Hugging Face, Ollama, Kaggle, Together AI, Fireworks AI
“We are also excited to collaborate with Hugging Face, Ollama, Kaggle, Together AI, and Fireworks AI to make the model available on their platforms starting today”
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Impact

User base: no public information
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Deployment scale: no public information
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Target sectors: Financial services, Healthcare, Robotics, automotive, manufacturing
“Our customers are evaluating Mistral Small 3 across multiple industries, including: Financial services customers for fraud detection Healthcare providers for customer triaging Robotics, automotive, and manufacturing companies for on-device command and control”
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High-risk domains: legal advice, medical diagnostics
“Fine-tuning to create subject matter experts: Mistral Small 3 can be fine-tuned to specialize in specific domains, creating highly accurate subject matter experts. This is particularly useful in fields like legal advice, medical diagnostics, and technical support, where domain-specific knowledge is essential.”
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Documented incidents: no public information
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