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arcee · Open weights

Trinity Large Thinking

Added Apr 1, 2026Open weights

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Use in the app

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.

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Trinity Large ThinkingarceeThis modelMercury 2InceptionRemove
ProviderarceeInception
Discovery tierOpen weightsBalanced
AddedApr 1, 2026Jan 1, 2024
Limits
Context window262.14KBest128K
Max output80KBest50K
Average output327 tokens—
Pricing, USD per 1M tokens
Input$0.25$0.25
Output$0.90$0.75Best
Cache read—$0.025
Benchmark indexes
Intelligence Index10.810.8
Coding Index25.831.1Best
Capabilities
ReasoningYesYes
ToolsYesYes
Structured outputNoYes
Reasoning effort——

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

  • Trinity Large Thinking
  • Mercury 2

Intelligence Index

  • Trinity Large Thinking10.8
  • Mercury 210.8

Trinity Large Thinking: Better than 23% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • Trinity Large Thinking: 25.8
    • Mercury 2: 31.1Top

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Trinity Large Thinking: 1.3%
    • Mercury 2: 1.7%Top

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Trinity Large Thinking: 0.2%
    • Mercury 2: 0.3%Top

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Trinity Large Thinking: 255 Elo
    • Mercury 2: 265 EloTop

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Trinity Large Thinking: 336 Elo
    • Mercury 2: 494 EloTop

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Trinity Large Thinking: 1.2%
    • Mercury 2: 3.8%Top

  • AA-LCRv1.1

    Reasoning across long documents

    • Trinity Large Thinking: 38.0%
    • Mercury 2: 43.7%Top

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Trinity Large Thinking: 15.8%
    • Mercury 2: 17.1%Top

  • GPQA Diamond

    Graduate-level science questions

    • Trinity Large Thinking: 75.2%
    • Mercury 2: 77.0%Top

  • IFBench

    Following precise output instructions

    • Trinity Large Thinking: 56.3%
    • Mercury 2: 69.8%Top

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Trinity Large Thinking: 0.5%Top
    • Mercury 2: 0.0%

  • SciCode

    Scientific computing in Python

    • Trinity Large Thinking: 40.6%Top
    • Mercury 2: 37.7%

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Trinity Large Thinking: 22.7%
    • Mercury 2: 26.5%Top

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • Trinity Large Thinking: 90.1%Top
    • Mercury 2: 70.8%

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Trinity Large Thinking: 38.0%
    • Mercury 2: 43.7%Top

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.

Read the quickstart
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)