Context Window

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Meta Llama3 2 11b Instruct vs Qwen Turbo 2024 11 01

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.

Meta

Model

Meta Llama3 2 11b Instruct

Image inputTool calling

Context window

128K

128,000 tokens · ~96K words

Model page
Alibaba

Model

Qwen Turbo 2024 11 01

Tool calling

Context window

1M

1,000,000 tokens · ~750K 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.

Meta Llama3 2 11b Instruct128K
Qwen Turbo 2024 11 011M

Qwen Turbo 2024 11 01 has about 7.8× the context window of the other in this pair.

Token calculator →Memory savings →

Qwen Turbo 2024 11 01 has 681% more context capacity (1000K vs 128K tokens). Qwen Turbo 2024 11 01 is 85% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Qwen Turbo 2024 11 01. Its 1000K context fits entire documents without chunking (vs 128K).

  • RAG / high-volume retrieval

    Use Qwen Turbo 2024 11 01. Input tokens are 85% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Qwen Turbo 2024 11 01. Its 8K 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.

SpecMeta Llama3 2 11b InstructQwen Turbo 2024 11 01
Context window128,000 tokens (128K)1,000,000 tokens (1000K)
Max output tokens4,096 tokens (4K)8,192 tokens (8K)
Speed tierFastBalanced
VisionYesNo
Function callingYesYes
Extended thinkingNoYes
Prompt cachingNoNo
Batch APINoNo
Release dateN/AN/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.

ProviderMeta Llama3 2 11b Instruct inMeta Llama3 2 11b Instruct outQwen Turbo 2024 11 01 inQwen Turbo 2024 11 01 out
Alibaba Cloud——$0.050/M$0.200/M
Aws Bedrock$0.350/M$0.350/M——

Frequently asked questions

Qwen Turbo 2024 11 01 has a larger context window: 1000K 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.

Powered by Mem0

Use a smaller model.
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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