Context Window

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Aion-RP 1.0 (8B) vs Open Mixtral 8x22b

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

Aion-RP 1.0 (8B)

Context window

33K

32,768 tokens · ~25K words

Model page
Mistral

Model

Open Mixtral 8x22b

Tool calling

Context window

65K

65,336 tokens · ~49K 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.

Aion-RP 1.0 (8B)33K
Open Mixtral 8x22b65K

Open Mixtral 8x22b has about 2× the context window of the other in this pair.

Token calculator →Memory savings →

Open Mixtral 8x22b has 99% more context capacity (65K vs 32K tokens). Aion-RP 1.0 (8B) is 60% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Open Mixtral 8x22b. Its 65K context fits entire documents without chunking (vs 32K).

  • RAG / high-volume retrieval

    Use Aion-RP 1.0 (8B). Input tokens are 60% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Aion-RP 1.0 (8B). Its 29K 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.

SpecAion-RP 1.0 (8B)Open Mixtral 8x22b
Context window32,768 tokens (32K)65,336 tokens (65K)
Max output tokens29,491 tokens (29K)8,191 tokens (8K)
Speed tierFastBalanced
VisionNoNo
Function callingNoYes
Extended thinkingNoNo
Prompt cachingNoNo
Batch APINoNo
Release dateFeb 2025N/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.

ProviderAion-RP 1.0 (8B) inAion-RP 1.0 (8B) outOpen Mixtral 8x22b inOpen Mixtral 8x22b out
Mistral——$2.00/M$6.00/M
Openrouter$0.800/M$1.60/M——

Frequently asked questions

Open Mixtral 8x22b has a larger context window: 65K tokens vs 32K. For long documents, large codebases, or extended agent sessions, the larger context window reduces the need to chunk inputs or summarize history.

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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