Trinity Large Thinking
Open source Arcee reasoning model with a 262K context window, 80K max output, and native reasoning and tool support for agentic workloads.
- Reasoning
- Tool Calling
Added Apr 1, 2026
Model weightsPricing
Auto routing · per 1M tokens- Input
- $0.25
- Output
- $0.90
Specifications
- Context window
- 262.1K
- Max output
- 80K
- Parameters
- 400B / 13B
- Total / active
- Avg output (7d)
- 555 tokens
- Longer than 48% of models
Benchmarks
Benchmarks
Sourced from Artificial Analysis.
Intelligence Index
10.8
Coding Index
25.8
Agentic Index
1.0
Agentic work
AutomationBench-AA
Workflow automation with guardrail penalties
1.3%
Better than 16% of models compared
AA-Briefcase
Agentic knowledge work (Elo)
251 Elo
Better than 15% of models compared
GDPval-AA v2
Economically valuable tasks (Elo)
340 Elo
Better than 19% of models compared
Document reasoning
GDP.pdf
Professional PDF reasoning: all-pass rate
1.2%
Better than 9% of models compared
AA-LCR v1.1
Long context reasoning with updated grading
38.0%
Better than 35% of models compared
Reasoning
HLE
Humanity's Last Exam
15.8%
Better than 63% of models compared
IFBench
Instruction-following benchmark
56.3%
Better than 67% of models compared
CritPt
Research-level physics reasoning
0.9%
Coding
Terminal-Bench v4.0
Practical coding and terminal tasks
0.5%
Better than 35% of models compared
SciCode
Python programming for scientific computing
40.6%
Better than 29% of models compared
Knowledge
AA-Omniscience Accuracy
Proportion of correctly answered questions
22.5%
AA-Omniscience Hallucination Rate
Rate of incorrect answers among non-correct responses
85.9%
Legacy benchmarks
GPQA Diamond (legacy)
Graduate-level scientific reasoning
75.2%
Better than 57% of models compared
Terminal-Bench Hard (legacy)
Agentic coding and terminal use
22.7%
Better than 62% of models compared
T²-Bench Telecom (legacy)
Conversational AI agents in dual-control scenarios
90.1%
Better than 84% of models compared
AA-LCR (unversioned / legacy)
Long context reasoning evaluation
38.0%
Better than 35% of models compared
GDPval-AA (unversioned / legacy)
Economically valuable tasks
0.0%
Last updated Oct 3, 2026
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