NOUMENOpen app
NOUMEN

arcee · Open weights

Trinity Large Thinking

Added Apr 1, 2026Open weights

Compare models

Choose up to 3 models to compare.0 of 3 chosen

Loading models…

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

Compare models

Put Trinity Large Thinking next to up to three other models. The comparison stays in the link, so you can share it.

Compare models

Choose up to 3 models to compare.0 of 3 chosen

Loading models…

TryMercury 2GLM 4.7 FlashGranite 4.2 8BAll 3

Public evaluations

Benchmarks

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

Intelligence Index

10.8

Better than 23% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    25.8

    Composite of the coding evaluations

    Better than 18% of 168 scored models

Agentic work

  • AutomationBench-AA

    1.3%

    Workflow automation, penalized for guardrail violations

    Better than 11% of 173 scored models

  • AutomationBench-AA tasks completed

    0.2%

    Workflows finished end to end without a guardrail violation

    Better than 13% of 173 scored models

  • AA-Briefcasev1.1

    255 Elo

    Agentic knowledge work, rated head to head

    Better than 4% of 166 scored models

  • GDPval-AAv2.1

    336 Elo

    Economically valuable occupational tasks, rated head to head

    Better than 5% of 187 scored models

Document reasoning

  • GDP.pdf

    1.2%

    Professional reasoning over PDF documents, all-pass rate

    Better than 4% of 171 scored models

  • AA-LCRv1.1

    38.0%

    Reasoning across long documents

    Better than 17% of 309 scored models

Reasoning and knowledge

  • Humanity’s Last Exam

    15.8%

    Expert-level questions across academic fields

    Better than 42% of 323 scored models

  • GPQA Diamond

    75.2%

    Graduate-level science questions

    Better than 38% of 291 scored models

  • IFBench

    56.3%

    Following precise output instructions

    Better than 56% of 215 scored models

Coding

  • Terminal-Benchv4.0

    0.5%

    Practical software engineering in a terminal

    Better than 30% of 171 scored models

  • SciCode

    40.6%

    Scientific computing in Python

    Better than 24% of 174 scored models

Legacy evaluations

  • Terminal-Bench Hard

    22.7%

    Earlier terminal task suite

    Better than 42% of 212 scored models

  • τ²-Bench Telecom

    90.1%

    Tool use in a customer-support simulation

    Better than 74% of 214 scored models

  • AA-LCR (unversioned)

    38.0%

    Long-context reasoning, earlier grading

    Better than 17% of 309 scored models

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)