Context Window

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Databricks Gemma 3 12b vs Qwen3 8b Fp8

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

Databricks Gemma 3 12b

Context window

128K

128,000 tokens · ~96K words

Model page
Alibaba

Model

Qwen3 8b Fp8

Context window

128K

128,000 tokens · ~96K 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.

Databricks Gemma 3 12b128K
Qwen3 8b Fp8128K

Same context window size for both models.

Token calculator →Memory savings →

Databricks Gemma 3 12b and Qwen3 8b Fp8 have identical context windows (128K tokens). Qwen3 8b Fp8 is 76% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • RAG / high-volume retrieval

    Use Qwen3 8b Fp8. Input tokens are 76% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Databricks Gemma 3 12b. Its 32K 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.

SpecDatabricks Gemma 3 12bQwen3 8b Fp8
Context window128,000 tokens (128K)128,000 tokens (128K)
Max output tokens32,000 tokens (32K)20,000 tokens (20K)
Speed tierBalancedFast
VisionNoNo
Function callingNoNo
Extended thinkingNoYes
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.

ProviderDatabricks Gemma 3 12b inDatabricks Gemma 3 12b outQwen3 8b Fp8 inQwen3 8b Fp8 out
Databricks$0.150/M$0.500/M——
Novita——$0.035/M$0.138/M

Frequently asked questions

Qwen3 8b Fp8 has a larger context window: 128K tokens vs 128K. 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