Model Detail
Upstage: Solar Pro 3
—Upstage: Solar Pro 3 is a large language model released by Upstage. And supports text->text inputs.
Upstage: Solar Pro 3 is priced at $0.15/M input tokens and $0.6/M output tokens. Operationally the model offers a 128K-token context window, which matters when sizing it for prompt-heavy or latency-sensitive workloads. At this input rate the model sits in the commodity tier and is suitable for high-volume workloads where per-call cost dominates the decision.
Upstage: Solar Pro 3 is published on Hugging Face but our pipeline has not yet captured architecture, license, or parameter-count metadata for this entry. The data is refreshed daily, so these fields typically populate within 24–48 hours of release.
Upstage: Solar Pro 3 is best fit for general-purpose chat and instruction-following workloads, and high-volume batch jobs where per-call cost dominates the budget. Treat this as a starting matrix rather than a benchmark verdict — the right deployment usually depends on the specific evaluation suite that mirrors your workload.
Improving Wind and Solar Power Prediction with Efficient Wrapper-based Feature Selection: An Empirical Study
arXiv:2607.14024v1 Announce Type: cross Abstract: With rising global energy demand and growing awareness of climate change and its impacts, the share of renewable energies in the global energy mix continues to grow. Unlike conventional power generation, the output of renewable energy sources cannot
Climate-Invariant Conformal Prediction Intervals for Multi-Horizon Solar and Wind Forecasting
arXiv:2607.11470v1 Announce Type: cross Abstract: Reliable uncertainty quantification is essential for integrating solar and wind generation into modern power systems, where operators must weigh risk rather than act on point forecasts alone. Existing probabilistic methods, however, often either lack
SolarChain-Eval: A Physics-Constrained Benchmark for Trustworthy Economic Agents in Decentralized Energy Markets
arXiv:2607.08681v1 Announce Type: cross Abstract: As agentic AI systems are increasingly applied to cyber-physical environments, their evaluation requires assessment of both task performance and trustworthiness. In decentralized energy markets, autonomous agents may improve market utility, but may a
SOLAR: AI-Powered Speed-of-Light Performance Analysis
arXiv:2606.26383v1 Announce Type: cross Abstract: How fast could a deep-learning model run on target hardware, and how far is today's implementation from that limit? These questions are central to software, hardware, and algorithm optimizations. Speed-of-Light (SOL) analysis answers them by computin
Review of Machine Learning Models for Solar Energetic Particle Prediction
arXiv:2606.19539v1 Announce Type: cross Abstract: Solar energetic particle (SEP) events have attracted increasing attention due to their significant radiation hazards for aviation, spacecraft electronics, and human missions beyond Earth's magnetosphere. From a scientific perspective, SEP events are
Optimizing Appliance Scheduling for Solar Energy Management Using Metaheuristic Algorithms
arXiv:2606.13407v1 Announce Type: new Abstract: Renewable energy is essential for meeting future energy demands; however, solar energy generation, which occurs only during daylight hours often does not align with household consumption patterns. Appliances such as cookers, washing machines, and dryer
