Context Window

Compare

Ministral 3 8b 2512 vs Trinity Large Thinking (free)

This page is context-first: how much text each model can take in one request. Full specs adds capabilities and limits; the pricing matrix below is only about $/million tokens from hosts that list both models.

Mistral

Model

Ministral 3 8b 2512

Image inputTool calling

Context window

262K

262,144 tokens · ~197K words

Model page
Arcee Ai

Model

Trinity Large Thinking (free)

Tool calling

Context window

262K

262,144 tokens · ~197K words

Model page

Context window · side by side

Bar length is relative to the larger of the two windows (100% = max of this pair). This is not pricing.

Ministral 3 8b 2512262K
Trinity Large Thinking (free)262K

Same context window size for both models.

Token calculator →Memory savings →

Ministral 3 8b 2512 and Trinity Large Thinking (free) have identical context windows (262K tokens).

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long output (reports, code files)

    Use Ministral 3 8b 2512. Its 262K max output lets you generate complete artifacts in one request.

Full specs

Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.

SpecMinistral 3 8b 2512Trinity Large Thinking (free)
Context window262,144 tokens (262K)262,144 tokens (262K)
Max output tokens262,144 tokens (262K)80,000 tokens (80K)
Speed tierFastDeep
VisionYesNo
Function callingYesYes
Extended thinkingNoYes
Prompt cachingNoNo
Batch APINoNo
Release dateN/AApr 2026

Pricing matrix

Dollar rates only: hosts that list both models, per 1M tokens. For how much text fits, use the context section above — not this table.

ProviderMinistral 3 8b 2512 inMinistral 3 8b 2512 outTrinity Large Thinking (free) inTrinity Large Thinking (free) out
Mistral$0.150/M$0.150/M——

Frequently asked questions

Trinity Large Thinking (free) has a larger context window: 262K tokens vs 262K. For long documents, large codebases, or extended agent sessions, the larger context window reduces the need to chunk inputs or summarize history.

Powered by Mem0

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 savingsLearn 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