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Upstage
upstage/solar-pro-3Catalogue: 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.
Upstage upstage/solar-pro-3
Solar Pro 3 is Upstage's powerful Mixture-of-Experts (MoE) language model. With 102B total parameters and 12B active parameters per forward pass, it delivers exceptional performance while maintaining computational efficiency. Optimized...
Solar Pro 3 earns a request when it needs step-by-step reasoning, tool calls; a short, general request would go to Nemotron 3.5 Super VL (free) instead - free per million input tokens against $0.15 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 Solar Pro 3
targets:
- id: solar-pro-3
kind: llm
name: Solar Pro 3
metadata:
model: upstage/solar-pro-3 # links the target to this catalogue entry
capabilities:
domains: [general]
supports_tools: true
context_window: 131072
cost:
usd_per_1k_tokens: 0.000375Input list price per million tokens; Solar Pro 3 is the 2nd cheapest of 3 listed.
Other models by the same vendor in the catalogue.
Photo: RDNE Stock project
Cached input reads $0.01 per 1M
A higher intelligence index, best first, with the price it comes at.
The catalogue prints input and output prices and what three typical monthly workloads cost on each.