Solar Mini 4
Upstage's compact 35B-parameter mixture-of-experts model with 3B active parameters and a 524K context window. Built for fast, cost-efficient agentic tasks, with strong Korean and English support.
- Tool Calling
- Structured Output
Added Sep 23, 2026
Pricing
Auto routing · per 1M tokens- Input
- $0.05
- Output
- $0.20
- Cache read
- $0.005
Specifications
- Context window
- 524.3K
- Max output
- 131.1K
- Parameters
- 35B / 3B
- Total / active
- Avg output (7d)
- 379 tokens
- Longer than 40% of models
Benchmarks
Benchmarks
Sourced from Artificial Analysis.
Agentic work
AutomationBench-AA
Workflow automation with guardrail penalties
22.3%
Better than 39% of models compared
AutomationBench-AA Tasks Completed
Fully completed workflows without guardrail violations
2.4%
Better than 35% of models compared
AA-Briefcase v1.1
Agentic knowledge work (Elo)
868 Elo
Better than 33% of models compared
GDPval-AA v2.1
Economically valuable tasks (Elo)
1092 Elo
Better than 49% of models compared
Document reasoning
GDP.pdf
Professional PDF reasoning: all-pass rate
5.0%
Better than 24% of models compared
AA-LCR v1.1
Long context reasoning with updated grading
83.3%
Better than 96% of models compared
MLCR-AA
Medical long-context reasoning
6.7%
Better than 19% of models compared
Reasoning
HLE
Humanity's Last Exam
25.8%
Better than 72% of models compared
CritPt
Research-level physics reasoning
1.4%
Coding
Terminal-Bench v4.0
Practical coding and terminal tasks
1.0%
Better than 38% of models compared
SciCode
Python programming for scientific computing
47.6%
Better than 42% of models compared
Knowledge
AA-Omniscience Accuracy
Proportion of correctly answered questions
18.2%
AA-Omniscience Hallucination Rate
Rate of incorrect answers among non-correct responses
36.5%
Legacy benchmarks
AA-LCR (unversioned / legacy)
Long context reasoning evaluation
83.3%
Better than 96% of models compared
GDPval-AA (unversioned / legacy)
Economically valuable tasks
29.6%
Last updated Nov 3, 2026
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