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Google Gemma 4 31b vs Snorkel Mistral 7b Pairrm Dpo

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.

Google

Model

Google Gemma 4 31b

Image inputTool calling

Context window

256K

256,000 tokens · ~192K words

Model page
Mistral

Model

Snorkel Mistral 7b Pairrm Dpo

Context window

33K

32,768 tokens · ~25K 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.

Google Gemma 4 31b256K
Snorkel Mistral 7b Pairrm Dpo33K

Google Gemma 4 31b has about 7.8× the context window of the other in this pair.

Google Gemma 4 31b has 681% more context capacity (256K vs 32K tokens). Google Gemma 4 31b is 30% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Google Gemma 4 31b. Its 256K context fits entire documents without chunking (vs 32K).

  • RAG / high-volume retrieval

    Use Google Gemma 4 31b. Input tokens are 30% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Google Gemma 4 31b. Its 256K 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.

SpecGoogle Gemma 4 31bSnorkel Mistral 7b Pairrm Dpo
Context window256,000 tokens (256K)32,768 tokens (32K)
Max output tokens256,000 tokens (256K)32,768 tokens (32K)
Speed tierFastFast
VisionYesNo
Function callingYesNo
Extended thinkingYesNo
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.

ProviderGoogle Gemma 4 31b inGoogle Gemma 4 31b outSnorkel Mistral 7b Pairrm Dpo inSnorkel Mistral 7b Pairrm Dpo out
Aws Bedrock$0.140/M$0.400/M
Fireworks$0.200/M$0.200/M

Frequently asked questions

Google Gemma 4 31b has a larger context window: 256K 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.

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