Mistral Saba 24B

Preview

mistral-saba-24b

Try it in Playground

TOKEN SPEED

~330 tps

INPUT

Text

OUTPUT

Text

CAPABILITIES

Tool Use, JSON Mode

Mistral AI

model card

Mistral Saba 24B is a specialized model trained to excel in Arabic, Farsi, Urdu, Hebrew, and Indic languages. Designed for high-performance multilingual capabilities, it delivers exceptional results across a wide range of tasks in these languages while maintaining strong performance in English. With a 32K token context window and tool use capabilities, it's ideal for complex multilingual applications requiring deep language understanding and regional context.

Terms and Conditions: Use of this model is subject to Mistral AI's Terms of Service

PRICING

Input

$0.79

1.3M / $1

Output

$0.79

1.3M / $1

LIMITS

CONTEXT WINDOW

32,768

MAX OUTPUT TOKENS

32,768

Key Technical Specifications

Model Architecture

Built on a 24B dense transformer architecture, Mistral Saba is specifically optimized for Arabic and South Asian languages while maintaining strong general capabilities. The model features advanced multilingual training techniques to ensure high performance across its target languages.

Performance Metrics

The model demonstrates exceptional performance across multilingual benchmarks:

MBZUAI Arabic MMLU (0-shot): 77.39
Arabic MT-Bench-dev (internal translation & gpt-4o-2024-08-06 judge): 7.93
English MT-Bench dev (gpt-4o-2024-05-13 judge): 7.98

Use Cases

Translation & Language Support

Translates between Arabic, Farsi, Urdu, Hebrew, and Indic languages while preserving cultural context and nuance. Valuable for international businesses, educational institutions, and government agencies requiring accurate cross-cultural communication.

Content Creation & Adaptation

Creates and adapts content across multiple languages while maintaining message integrity. Helps organizations develop culturally relevant materials for Arabic and South Asian markets, benefiting content creators, marketers, and educators.

Best Practices

Language Context: Provide prompts in the target language for optimal performance and cultural relevance
Context Window: Leverage the 32K token capacity for comprehensive documents and extended conversations
Few-shot prompting: Include examples in your prompts when working with complex linguistic or cultural tasks

Get Started with Mistral Saba 24B

Experience the exceptional multilingual capabilities of mistral-saba-24b with Groq speed:

shell

pip install groq

Python

from groq import Groq
client = Groq()
completion = client.chat.completions.create(
    model="mistral-saba-24b",
    messages=[
        {
            "role": "user",
            "content": "Explain why fast inference is critical for reasoning models"
        }
    ]
)
print(completion.choices[0].message.content)