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GLM 5.1 vs Llama 3.1 70B Hanami x1

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.

Z Ai

Model

GLM 5.1

Tool calling

Context window

203K

202,752 tokens · ~152K words

Model page
Sao10K

Model

Llama 3.1 70B Hanami x1

Context window

16K

16,000 tokens · ~12K 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.

GLM 5.1203K
Llama 3.1 70B Hanami x116K

GLM 5.1 has about 12.7× the context window of the other in this pair.

GLM 5.1 has 1167% more context capacity (202K vs 16K tokens).

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use GLM 5.1. Its 202K context fits entire documents without chunking (vs 16K).

Full specs

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

SpecGLM 5.1Llama 3.1 70B Hanami x1
Context window202,752 tokens (202K)16,000 tokens (16K)
Max output tokens131,072 tokens (131K)N/A
Speed tierBalancedDeep
VisionNoNo
Function callingYesNo
Extended thinkingYesNo
Prompt cachingYesNo
Batch APINoNo
Release dateApr 2026Jan 2025

Frequently asked questions

GLM 5.1 has a larger context window: 202K tokens vs 16K. 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.

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