Mistral Small vs Mistral Small
- ✦ Efficient Architecture
- ✦ Instruction Following
- ✦ Code Generation
- ✦ Efficient Architecture
- ✦ Instruction Following
- ✦ Code Generation
Real-World Scenarios: When to Choose Which
The question that matters: “In what situation will I regret choosing A over B after 3 months?”
Mistral Small's sub-$1/million token pricing makes it practical for high-volume classification pipelines that require LLM-quality reasoning but cannot justify frontier model costs.
Mistral Small's sub-$1/million token pricing makes it practical for high-volume classification pipelines that require LLM-quality reasoning but cannot justify frontier model costs.
Mistral Small's open weights run on a single A10G GPU, enabling LLM capability in air-gapped or data-sovereign environments where cloud API calls are prohibited.
Mistral Small's open weights run on a single A10G GPU, enabling LLM capability in air-gapped or data-sovereign environments where cloud API calls are prohibited.
Mistral Small's function calling produces well-structured JSON tool calls with lower latency than larger models, making it a cost-efficient backbone for agent frameworks that make dozens of tool calls per session.
Mistral Small's function calling produces well-structured JSON tool calls with lower latency than larger models, making it a cost-efficient backbone for agent frameworks that make dozens of tool calls per session.
Pricing Intelligence
Mistral Small Plans
Paid plans only
- • $0.1/M input tokens
- • $0.3/M output tokens
- • One of cheapest APIs
- • Open weights available
- • Apache 2.0 license
- • Commercial use allowed
Mistral Small Plans
Paid plans only
- • $0.1/M input tokens
- • $0.3/M output tokens
- • One of cheapest APIs
- • Open weights available
- • Apache 2.0 license
- • Commercial use allowed
Feature Matrix
0 differences found across 15 standardized features
- •Efficient Architecture
- •Instruction Following
- •Code Generation
- •Function Calling
- •JSON Mode
- •Streaming
- •32k Context
- •Open Weights
- •Commercial License
- •API Access
- •Multilingual
- •Low Latency
- •RAG Optimized
- •Tool Use
- •Safety Features
- •Efficient Architecture
- •Instruction Following
- •Code Generation
- •Function Calling
- •JSON Mode
- •Streaming
- •32k Context
- •Open Weights
- •Commercial License
- •API Access
- •Multilingual
- •Low Latency
- •RAG Optimized
- •Tool Use
- •Safety Features
Pros & Cons Face-Off
Evaluative strengths and weaknesses: not feature lists
- +Very affordable API pricing
- +Open weights with commercial license
- +Strong performance for its size
- +Good for high-volume applications
- −Less capable than Mistral Large for complex tasks
- −Limited context compared to GPT-4o
- −Smaller ecosystem
- +Very affordable API pricing
- +Open weights with commercial license
- +Strong performance for its size
- +Good for high-volume applications
- −Less capable than Mistral Large for complex tasks
- −Limited context compared to GPT-4o
- −Smaller ecosystem
At a Glance
Frequently Asked Questions
Related Comparisons
Sources
- 1.Mistral Small Official Pricing–Vendor pricing page
- 2.Mistral Small Official Pricing–Vendor pricing page
- 3.Mistral Small Official Website–Official product website
- 4.Mistral Small Official Website–Official product website