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DeepSeek V4 Flash (free) vs Ministral 3 3b Instruct 2512

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.

Deepseek

Model

DeepSeek V4 Flash (free)

Tool calling

Context window

256K

256,000 tokens · ~192K words

Model page
Mistral

Model

Ministral 3 3b Instruct 2512

Context window

256K

256,000 tokens · ~192K 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.

DeepSeek V4 Flash (free)256K
Ministral 3 3b Instruct 2512256K

Same context window size for both models.

DeepSeek V4 Flash (free) and Ministral 3 3b Instruct 2512 have identical context windows (256K tokens).

Full specs

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

SpecDeepSeek V4 Flash (free)Ministral 3 3b Instruct 2512
Context window256,000 tokens (256K)256,000 tokens (256K)
Max output tokens256,000 tokens (256K)256,000 tokens (256K)
Speed tierFastFast
VisionNoNo
Function callingYesNo
Extended thinkingYesNo
Prompt cachingNoNo
Batch APINoNo
Release dateApr 2026N/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.

ProviderDeepSeek V4 Flash (free) inDeepSeek V4 Flash (free) outMinistral 3 3b Instruct 2512 inMinistral 3 3b Instruct 2512 out
Fireworks$0.100/M$0.100/M

Frequently asked questions

Ministral 3 3b Instruct 2512 has a larger context window: 256K tokens vs 256K. 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