Context Window

Compare

GLM 5V Turbo vs Meta Llama 3 70b Instruct

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 5V Turbo

Image inputTool calling

Context window

205K

204,800 tokens · ~154K words

Model page
Meta

Model

Meta Llama 3 70b Instruct

Context window

8K

8,192 tokens · ~6K 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 5V Turbo205K
Meta Llama 3 70b Instruct8K

GLM 5V Turbo has about 25× the context window of the other in this pair.

Token calculator →Memory savings →

GLM 5V Turbo has 2400% more context capacity (204K vs 8K tokens). Meta Llama 3 70b Instruct is 26% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use GLM 5V Turbo. Its 204K context fits entire documents without chunking (vs 8K).

  • RAG / high-volume retrieval

    Use Meta Llama 3 70b Instruct. Input tokens are 26% cheaper — critical when sending large retrieved contexts.

Full specs

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

SpecGLM 5V TurboMeta Llama 3 70b Instruct
Context window204,800 tokens (204K)8,192 tokens (8K)
Max output tokens131,072 tokens (131K)N/A
Speed tierBalancedDeep
VisionYesNo
Function callingYesNo
Extended thinkingYesNo
Prompt cachingYesNo
Batch APINoNo
Release dateApr 2026N/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.

ProviderGLM 5V Turbo inGLM 5V Turbo outMeta Llama 3 70b Instruct inMeta Llama 3 70b Instruct out
Novita$1.20/M$4.00/M——
Openrouter$1.20/M$4.00/M——
Together Ai——$0.880/M$0.880/M

Frequently asked questions

GLM 5V Turbo has a larger context window: 204K tokens vs 8K. 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