Context Window

Compare

Databricks Gemini 4 Argon vs DeepSeek V3.2

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 Gemini 4 Argon

Image inputTool calling

Context window

1.0M

1,048,576 tokens · ~786K words

Model page
Deepseek

Model

DeepSeek V3.2

Tool calling

Context window

164K

163,840 tokens · ~123K 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 Gemini 4 Argon1.0M
DeepSeek V3.2164K

Databricks Gemini 4 Argon has about 6.4× the context window of the other in this pair.

Token calculator →Memory savings →

Databricks Gemini 4 Argon has 540% more context capacity (1048K vs 163K tokens). DeepSeek V3.2 is 88% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Databricks Gemini 4 Argon. Its 1048K context fits entire documents without chunking (vs 163K).

  • RAG / high-volume retrieval

    Use DeepSeek V3.2. Input tokens are 88% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Databricks Gemini 4 Argon. Its 1048K 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 Gemini 4 ArgonDeepSeek V3.2
Context window1,048,576 tokens (1048K)163,840 tokens (163K)
Max output tokens1,048,576 tokens (1048K)163,840 tokens (163K)
Speed tierFastBalanced
VisionYesNo
Function callingYesYes
Extended thinkingYesYes
Prompt cachingYesYes
Batch APINoNo
Release dateN/ADec 2025

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 Gemini 4 Argon inDatabricks Gemini 4 Argon outDeepSeek V3.2 inDeepSeek V3.2 out
Aws Bedrock——$0.740/M$2.22/M
Azure——$0.580/M$1.68/M
Databricks$2.50/M$12.50/M——
Deepinfra——$0.260/M$0.380/M
Deepseek——$0.280/M$0.400/M
Friendliai——$0.500/M$1.50/M
Gmi——$0.280/M$0.400/M
Novita——$0.269/M$0.400/M
Openrouter——$0.259/M$0.420/M
Sambanova——$3.00/M$4.50/M

Frequently asked questions

Databricks Gemini 4 Argon has a larger context window: 1048K tokens vs 163K. 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