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Mistral AI
mistralai/mistral-sabaCatalogue: Indexed in the reference catalogue; nothing on this deployment answers as this model yet.
Published by the vendor; the platform bills at the target's declared price.
Mistral AI mistralai/mistral-saba
Mistral Saba is a 24B-parameter language model specifically designed for the Middle East and South Asia, delivering accurate and contextually relevant responses while maintaining efficient performance. Trained on curated regional...
Cached input reads $0.02 per 1M
Saba earns a request when it needs tool calls, file input; a short, general request would go to Nemotron 3.5 Super VL (free) instead - free per million input tokens against $0.20 here; and the hardest requests, where the quality floor rules it out, to Claude Opus 5.5 (batch). Your rules decide the floor; the trace shows the comparison for every request.
Lower input price and an intelligence index within 5 points.
A higher intelligence index, best first, with the price it comes at.
Nothing on this deployment answers as this model yet. Connect your own provider under Model providers, or add a target to your catalogue - the router picks it up without retraining.
# targets.yaml - declare a target that runs Saba
targets:
- id: mistral-saba
kind: llm
name: Saba
metadata:
model: mistralai/mistral-saba # links the target to this catalogue entry
capabilities:
domains: [general]
supports_tools: true
context_window: 32768
cost:
usd_per_1k_tokens: 0.000400Input list price per million tokens; Saba is the 5th cheapest of 13 listed.
Other models by the same vendor in the catalogue.
Photo: RDNE Stock project