Solar Pro 3
Upstage's Solar Pro 3 is a Mixture-of-Experts (MoE) language model with 102B total parameters and 12B active parameters per forward pass, optimized for Korean with strong English and Japanese support.
Added Mar 3, 2026
Pricing
Auto routing · per 1M tokens- Input
- $0.15
- Output
- $0.60
- Cache read
- $0.015
Specifications
- Context window
- 128K
- Max output
- 128K
- Parameters
- 102B / 12B
- Total / active
Benchmarks
Benchmarks
Sourced from Artificial Analysis.
Intelligence Index
7.8
Coding Index
16.2
Agentic Index
1.4
Agentic work
AutomationBench-AA
Workflow automation with guardrail penalties
0.5%
Better than 8% of models compared
AA-Briefcase
Agentic knowledge work (Elo)
96 Elo
Better than 10% of models compared
GDPval-AA v2
Economically valuable tasks (Elo)
268 Elo
Better than 16% of models compared
Document reasoning
GDP.pdf
Professional PDF reasoning: all-pass rate
1.6%
Better than 12% of models compared
AA-LCR v1.1
Long context reasoning with updated grading
32.3%
Better than 31% of models compared
MLCR-AA
Medical long-context reasoning
0.6%
Better than 4% of models compared
Reasoning
HLE
Humanity's Last Exam
10.3%
Better than 51% of models compared
IFBench
Instruction-following benchmark
71.2%
Better than 87% of models compared
CritPt
Research-level physics reasoning
0.0%
Coding
Terminal-Bench v4.0
Practical coding and terminal tasks
0.0%
Better than 16% of models compared
SciCode
Python programming for scientific computing
25.5%
Better than 6% of models compared
Knowledge
AA-Omniscience Accuracy
Proportion of correctly answered questions
18.5%
AA-Omniscience Hallucination Rate
Rate of incorrect answers among non-correct responses
88.2%
Legacy benchmarks
GPQA Diamond (legacy)
Graduate-level scientific reasoning
72.4%
Better than 52% of models compared
Terminal-Bench Hard (legacy)
Agentic coding and terminal use
7.6%
Better than 40% of models compared
T²-Bench Telecom (legacy)
Conversational AI agents in dual-control scenarios
86.3%
Better than 79% of models compared
AA-LCR (unversioned / legacy)
Long context reasoning evaluation
32.3%
Better than 31% of models compared
GDPval-AA (unversioned / legacy)
Economically valuable tasks
0.0%
Last updated Oct 3, 2026
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