Compare
Gemini Flash Latest vs Gemma 7b It
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.
Model
Gemini Flash Latest
Context window
1.0M
1,048,576 tokens · ~786K words
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.
Gemini Flash Latest has about 128× the context window of the other in this pair.
Gemini Flash Latest has 12700% more context capacity (1048K vs 8K tokens). Gemma 7b It is 83% cheaper on input.
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use Gemini Flash Latest. Its 1048K context fits entire documents without chunking (vs 8K).
RAG / high-volume retrieval
Use Gemma 7b It. Input tokens are 83% cheaper — critical when sending large retrieved contexts.
Long output (reports, code files)
Use Gemini Flash Latest. Its 65K 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.
| Spec | Gemini Flash Latest | Gemma 7b It |
|---|---|---|
| Context window | 1,048,576 tokens (1048K) | 8,192 tokens (8K) |
| Max output tokens | 65,535 tokens (65K) | 8,192 tokens (8K) |
| Speed tier | Fast | Fast |
| Vision | Yes | No |
| Function calling | Yes | No |
| Extended thinking | Yes | No |
| Prompt caching | Yes | No |
| Batch API | No | No |
| Release date | N/A | N/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.
| Provider | Gemini Flash Latest in | Gemini Flash Latest out | Gemma 7b It in | Gemma 7b It out |
|---|---|---|---|---|
| Anyscale | — | — | $0.150/M | $0.150/M |
| Fireworks | — | — | $0.200/M | $0.200/M |
| $0.300/M | $2.50/M | — | — | |
| Groq | — | — | $0.050/M | $0.080/M |
Frequently asked questions
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
80% less to send — works with any model