Context Window

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Mistral 7b Instruct V0 1 vs Phi 4

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.

Mistral

Model

Mistral 7b Instruct V0 1

Tool calling

Context window

16K

16,384 tokens · ~12K words

Model page
Microsoft

Model

Phi 4

Tool calling

Context window

16K

16,384 tokens · ~12K 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.

Mistral 7b Instruct V0 116K
Phi 416K

Same context window size for both models.

Token calculator →Memory savings →

Mistral 7b Instruct V0 1 and Phi 4 have identical context windows (16K tokens). Phi 4 is 53% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • RAG / high-volume retrieval

    Use Phi 4. Input tokens are 53% cheaper — critical when sending large retrieved contexts.

Full specs

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

SpecMistral 7b Instruct V0 1Phi 4
Context window16,384 tokens (16K)16,384 tokens (16K)
Max output tokens16,384 tokens (16K)16,384 tokens (16K)
Speed tierFastBalanced
VisionNoNo
Function callingYesYes
Extended thinkingNoNo
Prompt cachingNoNo
Batch APINoNo
Release dateN/AJan 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.

ProviderMistral 7b Instruct V0 1 inMistral 7b Instruct V0 1 outPhi 4 inPhi 4 out
Anyscale$0.150/M$0.150/M——
Azure——$0.125/M$0.500/M
Cloudflare$1.92/M$1.92/M——
Deepinfra——$0.070/M$0.140/M
Together Ai————

Frequently asked questions

Phi 4 has a larger context window: 16K tokens vs 16K. 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