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Mistral AI
mistralai/mistral-nemoCatalogue: 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-nemo
A 12B parameter model with a 128k token context length built by Mistral in collaboration with NVIDIA. The model is multilingual, supporting English, French, German, Spanish, Italian, Portuguese, Chinese, Japanese,...
Mistral Nemo earns a request when it needs tool calls, running on your own hardware; a short, general request would go to Nemotron 3.5 Super VL (free) instead - free per million input tokens against $0.03 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 (this model has no published index).
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 Mistral Nemo
targets:
- id: mistral-nemo
kind: llm
name: Mistral Nemo
metadata:
model: mistralai/mistral-nemo # links the target to this catalogue entry
capabilities:
domains: [general]
supports_tools: true
context_window: 131072
cost:
usd_per_1k_tokens: 0.000029Input list price per million tokens; Mistral Nemo is the 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.