DeepInfra
DeepInfra
Efficient

Mistral 7B (DI)

Nano

The 7B Mistral that put open-weights chat models on the map. v0.3 added function calling and an extended vocabulary.

Mistral 7B (DI) is a efficient AI model from DeepInfra. It costs $0.070 per million input tokens and $0.070 per million output tokens (blended $0.070/M), with a 32,000-token context window.

Profile inherited from upstream Mistral 7B ↗ — this is a hosted variant of the same open-weights model.

INPUT
$0.070/M
per million input tokens
OUTPUT
$0.070/M
per million output tokens
BLENDED 70/30
$0.070/M
unchanged since 3 May
CONTEXT
32,000
tokens
What it is good at
  • Open weights (Apache 2.0)
  • Single-GPU
  • Function calling
  • Wide ecosystem
Typical use cases
  • Self-hosted small chat
  • Fine-tune base
  • Edge deployments

Benchmarks

vs. best public score
Scores inherited from Mistral 7B — this is a hosted variant of the same open-weights model, so the underlying benchmark scores are identical.
MMLU62%
Multitask academic knowledge across 57 subjects.
Python function synthesis from docstrings.
LMArena Elo1072 Elo
Crowd-sourced head-to-head preference Elo rating.
Hand-curated from each provider's published reports and public leaderboards. Methodology varies across sources, treat as directional rather than authoritative.

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Frequently asked questions

How much does Mistral 7B (DI) cost?

Mistral 7B (DI) costs $0.070 per million input tokens and $0.070 per million output tokens, for a blended reference rate of $0.070 per million tokens.

What is Mistral 7B (DI)'s context window?

Mistral 7B (DI) supports up to 32,000 tokens of context in a single request.

What is Mistral 7B (DI) best for?

Mistral 7B (DI) is well suited to Open weights (Apache 2.0), Single-GPU and Function calling.

Who makes Mistral 7B (DI)?

Mistral 7B (DI) is developed and served by DeepInfra. It was released in May 2024.

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