arcee · Open weights
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
- Tools
- Input
- Text
- Output
- Text
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $0.25
- Output
- $0.90
Reference prices as published by the model provider. API example
Specifications
- Context window
- 262.1K
- Max output
- 80K
- Average output (7 days)
- 327 tokens
- Longer than 35% of 468 models
Side by side
Trinity Large Thinking compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Trinity Large ThinkingarceeThis model | GLM 4.7 FlashZ.aiRemove | |
|---|---|---|
| Provider | arcee | Z.ai |
| Discovery tier | Open weights | Open weights |
| Added | Apr 1, 2026 | Jan 19, 2026 |
| Limits | ||
| Context window | 262.14KBest | 200K |
| Max output | 80K | 128KBest |
| Average output | 327 tokens | 86 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.25 | $0.07Best |
| Output | $0.90 | $0.40Best |
| Cache read | — | $0.01 |
| Performance | ||
| Throughput | — | 31.6 tok/s |
| Time to first token | — | 2.9 s |
| Request success (24h) | — | 100.0% |
| Benchmark indexes | ||
| Intelligence Index | 10.8Best | 10.6 |
| Coding Index | 25.8 | — |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | Yes |
| Structured output | No | Yes |
| Reasoning effort | — | — |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- Trinity Large Thinking
- GLM 4.7 Flash
Intelligence Index
- Trinity Large Thinking10.8
- GLM 4.7 Flash10.6
Trinity Large Thinking: Better than 23% of 326 scored models
Indexes
Coding Index
Composite of the coding evaluations
- Trinity Large Thinking: 25.8
- GLM 4.7 Flash: —
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- Trinity Large Thinking: 1.3%
- GLM 4.7 Flash: —
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- Trinity Large Thinking: 0.2%
- GLM 4.7 Flash: —
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- Trinity Large Thinking: 255 Elo
- GLM 4.7 Flash: —
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- Trinity Large Thinking: 336 Elo
- GLM 4.7 Flash: —
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- Trinity Large Thinking: 1.2%
- GLM 4.7 Flash: —
AA-LCRv1.1
Reasoning across long documents
- Trinity Large Thinking: 38.0%Top
- GLM 4.7 Flash: 20.3%
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Trinity Large Thinking: 15.8%Top
- GLM 4.7 Flash: 5.0%
GPQA Diamond
Graduate-level science questions
- Trinity Large Thinking: 75.2%Top
- GLM 4.7 Flash: 45.2%
IFBench
Following precise output instructions
- Trinity Large Thinking: 56.3%Top
- GLM 4.7 Flash: 46.3%
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- Trinity Large Thinking: 0.5%
- GLM 4.7 Flash: —
SciCode
Scientific computing in Python
- Trinity Large Thinking: 40.6%
- GLM 4.7 Flash: —
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- Trinity Large Thinking: 22.7%Top
- GLM 4.7 Flash: 3.8%
τ²-Bench Telecom
Tool use in a customer-support simulation
- Trinity Large Thinking: 90.1%
- GLM 4.7 Flash: 91.8%Top
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Trinity Large Thinking: 38.0%Top
- GLM 4.7 Flash: 20.3%
Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis
Developers
Use it through the API
Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.
curl https://www.noumen.xyz/api/v1/chat/completions \
-H "Authorization: Bearer $NOUMEN_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "arcee-ai/trinity-large-thinking",
"messages": [{ "role": "user", "content": "Explain this stack trace." }]
}'import os
from openai import OpenAI
client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
model="arcee-ai/trinity-large-thinking",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)