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Granite 3 3 8b vs Moonshot V1 8k Vision Preview

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.

Ibm

Model

Granite 3 3 8b

Tool calling

Context window

8K

8,192 tokens · ~6K words

Model page
Moonshot

Model

Moonshot V1 8k Vision Preview

Image inputTool calling

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.

Granite 3 3 8b8K
Moonshot V1 8k Vision Preview8K

Same context window size for both models.

Granite 3 3 8b and Moonshot V1 8k Vision Preview have identical context windows (8K tokens). Moonshot V1 8k Vision Preview is 0% cheaper on input.

Full specs

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

SpecGranite 3 3 8bMoonshot V1 8k Vision Preview
Context window8,192 tokens (8K)8,192 tokens (8K)
Max output tokensN/A8,192 tokens (8K)
Speed tierFastBalanced
VisionNoYes
Function callingYesYes
Extended thinkingNoNo
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.

ProviderGranite 3 3 8b inGranite 3 3 8b outMoonshot V1 8k Vision Preview inMoonshot V1 8k Vision Preview out
Ibm Watsonx$0.200/M$0.200/M
Moonshot$0.200/M$2.00/M
Replicate$0.030/M$0.250/M

Frequently asked questions

Moonshot V1 8k Vision Preview has a larger context window: 8K 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.

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