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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.
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.
Photo: RDNE Stock project
A higher intelligence index, best first, with the price it comes at.
Other models by the same vendor in the catalogue.
The catalogue prints input and output prices and what three typical monthly workloads cost on each.