Context Window

Compare

Qwen3 Next 80B A3B Instruct (free) vs Writer Palmyra X4

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

Qwen3 Next 80B A3B Instruct (free)

Tool calling

Context window

262K

262,144 tokens · ~197K words

Model page
Google

Model

Writer Palmyra X4

Tool calling

Context window

128K

128,000 tokens · ~96K 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.

Qwen3 Next 80B A3B Instruct (free)262K
Writer Palmyra X4128K

Qwen3 Next 80B A3B Instruct (free) has about 2× the context window of the other in this pair.

Token calculator →Memory savings →

Qwen3 Next 80B A3B Instruct (free) has 104% more context capacity (262K vs 128K tokens).

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Qwen3 Next 80B A3B Instruct (free). Its 262K context fits entire documents without chunking (vs 128K).

Full specs

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

SpecQwen3 Next 80B A3B Instruct (free)Writer Palmyra X4
Context window262,144 tokens (262K)128,000 tokens (128K)
Max output tokensN/A8,192 tokens (8K)
Speed tierFastBalanced
VisionNoNo
Function callingYesYes
Extended thinkingNoNo
Prompt cachingNoNo
Batch APINoNo
Release dateSep 2025N/A

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.

ProviderQwen3 Next 80B A3B Instruct (free) inQwen3 Next 80B A3B Instruct (free) outWriter Palmyra X4 inWriter Palmyra X4 out
Aws Bedrock——$2.50/M$10.00/M

Frequently asked questions

Qwen3 Next 80B A3B Instruct (free) has a larger context window: 262K tokens vs 128K. For long documents, large codebases, or extended agent sessions, the larger context window reduces the need to chunk inputs or summarize history.

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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.

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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