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Mistral AI
mistralai/mistral-large-2512:batchCatalogue: 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-large-2512:batch
Mistral Large 3 2512 is Mistral’s most capable model to date, featuring a sparse mixture-of-experts architecture with 41B active parameters (675B total), and released under the Apache 2.0 license.
Mistral Large 3 2512 (batch) earns a request when it needs tool calls, very long inputs, image and file input; a short, general request would go to MiniMax M3.1 Flash (free) instead - free per million input tokens against $0.25 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 Mistral Large 3 2512 (batch)
targets:
- id: mistral-large-2512-batch
kind: llm
name: Mistral Large 3 2512 (batch)
metadata:
model: mistralai/mistral-large-2512:batch # links the target to this catalogue entry
capabilities:
domains: [general]
supports_tools: true
context_window: 262144
cost:
usd_per_1k_tokens: 0.000500Input list price per million tokens; Mistral Large 3 2512 (batch) is the 8th cheapest of 13 listed.
Photo: RDNE Stock project
Cached input reads $0.03 per 1M
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.
