Context Window

Compare

Qwen Qwen3 Coder 30b A3b 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.

Alibaba

Model

Qwen Qwen3 Coder 30b A3b

Tool 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.

Qwen Qwen3 Coder 30b A3b262K
Trinity Large Thinking (free)262K

Same context window size for both models.

Token calculator →Memory savings →

Qwen Qwen3 Coder 30b A3b 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 Qwen Qwen3 Coder 30b A3b. Its 131K 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.

SpecQwen Qwen3 Coder 30b A3bTrinity Large Thinking (free)
Context window262,144 tokens (262K)262,144 tokens (262K)
Max output tokens131,072 tokens (131K)80,000 tokens (80K)
Speed tierFastDeep
VisionNoNo
Function callingYesYes
Extended thinkingYesYes
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.

ProviderQwen Qwen3 Coder 30b A3b inQwen Qwen3 Coder 30b A3b outTrinity Large Thinking (free) inTrinity Large Thinking (free) out
Aws Bedrock$0.150/M$0.600/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