Arcee AifastTool use

Trinity Mini (free)

Trinity Mini is a 26B-parameter (3B active) sparse mixture-of-experts language model featuring 128 experts with 8 active per token. Engineered for efficient reasoning over long contexts (131k) with robust function...

131K context·~98K words·

View context details Compare with Amazon Titan Text Express

Context window131Ktokens

Context window

This model accepts 131K tokens in one request (~98K words of text).

Context window size131K tokens

4K32K128K1M10M

What fits in one request

Short document
About 1,500 words of text
Fits
Long document
About 37K words of text
Fits
Small codebase
About 150K words of text
Won't fit
Full novel
About 375K words of text
Won't fit

Specifications

Context size, pricing, and release info in one place.

Context window: 131,072 tokens (131K)
Speed tier: fast
Provider: Arcee Ai
Release date: Dec 2025

Capabilities

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Supported (4)

Tool use: Can call external tools and APIs; Supported
Function calling: Structured function call interface; Supported
Extended thinking: Shows its chain-of-thought reasoning; Supported
Streaming: Returns tokens as they are generated; Supported

Not supported (4)

Vision: Accepts image inputs alongside text; Not supported
Web search: Can browse the web during a request; Not supported
Batch API: Process many requests asynchronously; Not supported
Prompt caching: Reuse repeated prompt prefixes cheaply; Not supported

Best for

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Reasoning AI agents Long documents RAG Chatbots

Compare Trinity Mini (free)

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Frequently asked questions

Short answers about context size and how this model behaves.

Trinity Mini (free) has a context window of 131K tokens (131,072 tokens). This covers most professional use cases including large code files, lengthy reports, and long conversation histories.

More from Arcee Ai

Other models by Arcee Ai in our catalog.

Trinity Large Thinking

262Kdeep

Trinity Large Thinking (free)

Use a smaller model.
Get better results.

Mem0 gives your AI long-term memory so you stop re-sending context on every call. That means you can use a smaller, faster, cheaper model — and still get better answers.

Calculate your savings Learn about Mem0

Example: a multi-turn chat session

Without Mem0~128K tokens sent

Full history

Repeated info

Old context

With Mem0~20K tokens sent

Key memories

Current turn

80% less to send — works with any model