Context Window

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Meta Llama3 1 8b Instruct vs Qwen3.5 Plus 2026-02-15

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 1 8b Instruct

Tool calling

Context window

128K

128,000 tokens · ~96K words

Model page
Alibaba

Model

Qwen3.5 Plus 2026-02-15

Image inputTool 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 1 8b Instruct128K
Qwen3.5 Plus 2026-02-151M

Qwen3.5 Plus 2026-02-15 has about 7.8× the context window of the other in this pair.

Token calculator →Memory savings →

Qwen3.5 Plus 2026-02-15 has 681% more context capacity (1000K vs 128K tokens). Meta Llama3 1 8b Instruct is 45% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Qwen3.5 Plus 2026-02-15. Its 1000K context fits entire documents without chunking (vs 128K).

  • RAG / high-volume retrieval

    Use Meta Llama3 1 8b Instruct. Input tokens are 45% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Qwen3.5 Plus 2026-02-15. Its 65K 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 1 8b InstructQwen3.5 Plus 2026-02-15
Context window128,000 tokens (128K)1,000,000 tokens (1000K)
Max output tokens2,048 tokens (2K)65,536 tokens (65K)
Speed tierFastBalanced
VisionNoYes
Function callingYesYes
Extended thinkingNoYes
Prompt cachingNoNo
Batch APINoNo
Release dateN/AFeb 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.

ProviderMeta Llama3 1 8b Instruct inMeta Llama3 1 8b Instruct outQwen3.5 Plus 2026-02-15 inQwen3.5 Plus 2026-02-15 out
Aws Bedrock$0.220/M$0.220/M——
Openrouter——$0.400/M$2.40/M

Frequently asked questions

Qwen3.5 Plus 2026-02-15 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.
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