Context Window

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Chatdolphin vs Mistral 7b Instruct V0 1

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.

Microsoft

Model

Chatdolphin

Context window

16K

16,384 tokens · ~12K words

Model page
Mistral

Model

Mistral 7b Instruct V0 1

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.

Chatdolphin16K
Mistral 7b Instruct V0 116K

Same context window size for both models.

Token calculator →Memory savings →

Chatdolphin and Mistral 7b Instruct V0 1 have identical context windows (16K tokens). Mistral 7b Instruct V0 1 is 70% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • RAG / high-volume retrieval

    Use Mistral 7b Instruct V0 1. Input tokens are 70% cheaper — critical when sending large retrieved contexts.

Full specs

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

SpecChatdolphinMistral 7b Instruct V0 1
Context window16,384 tokens (16K)16,384 tokens (16K)
Max output tokens16,384 tokens (16K)16,384 tokens (16K)
Speed tierBalancedFast
VisionNoNo
Function callingNoYes
Extended thinkingNoNo
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.

ProviderChatdolphin inChatdolphin outMistral 7b Instruct V0 1 inMistral 7b Instruct V0 1 out
Anyscale——$0.150/M$0.150/M
Cloudflare——$1.92/M$1.92/M
Nlp Cloud$0.500/M$0.500/M——
Together Ai————

Frequently asked questions

Mistral 7b Instruct V0 1 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