Context Window

Compare

Llama 3 1 8b Instant vs Qwen Plus 2025 01 25

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

Llama 3 1 8b Instant

Tool calling

Context window

128K

128,000 tokens · ~96K words

Model page
Alibaba

Model

Qwen Plus 2025 01 25

Tool calling

Context window

129K

129,024 tokens · ~97K 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.

Llama 3 1 8b Instant128K
Qwen Plus 2025 01 25129K

Qwen Plus 2025 01 25 has about 1× the context window of the other in this pair.

Token calculator →Memory savings →

Qwen Plus 2025 01 25 has 0% more context capacity (129K vs 128K tokens). Llama 3 1 8b Instant is 87% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Qwen Plus 2025 01 25. Its 129K context fits entire documents without chunking (vs 128K).

  • RAG / high-volume retrieval

    Use Llama 3 1 8b Instant. Input tokens are 87% cheaper — critical when sending large retrieved contexts.

Full specs

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

SpecLlama 3 1 8b InstantQwen Plus 2025 01 25
Context window128,000 tokens (128K)129,024 tokens (129K)
Max output tokens8,192 tokens (8K)8,192 tokens (8K)
Speed tierFastBalanced
VisionNoNo
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.

ProviderLlama 3 1 8b Instant inLlama 3 1 8b Instant outQwen Plus 2025 01 25 inQwen Plus 2025 01 25 out
Alibaba Cloud——$0.400/M$1.20/M
Groq$0.050/M$0.080/M——

Frequently asked questions

Qwen Plus 2025 01 25 has a larger context window: 129K 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