LLM Reference

MPT 7B

Released
2023-03-16
Last refreshed
2026-05-19
Status
Researched 105d ago
Open sourceCommercial use: permitted

MPT 7B is worth evaluating for general LLM work when its provider route and context window match the workload.

Use it for

  • Teams evaluating general LLM work
  • Workloads that can use a 2k context window
  • Buyers comparing 2 tracked provider routes

Do not use it for

  • Vision or document-understanding workloads
  • Strict JSON or tool-calling flows
Specifications
Family
MPT
Released
2023-03-16
Context
2k
Parameters
7B
Architecture
Decoder Only
Knowledge cutoff
2023
Specialization
general
Openness
Open source
License
Apache 2.0OSI-approvedCommercial use: permitted
Weights
Unknown
Code
Unknown
Training
Fine-tuned
Created by
Databricks MosaicDatabricks Mosaic

Advancing AI research and model development.

San Francisco, California, United States
Founded 2023
Website
Pricing
Output / 1M
$0.500
Input / 1M
$0.500

Cheapest of 2 routes · Databricks Foundation Model Serving

Providers(2)
Databricks Foundation Model ServingScale AI GenAI Platform
View 2 provider routes

About

MPT 7B is Databricks Mosaic's MPT model. Its knowledge cutoff is 2023.

Top use-case fit

No primary decision-task fit is mapped for this model yet.

Provider price ladder

Compare all 2

Compare API pricing across 2 providers for input and output tokens, batch, and cached reads when available.

ProviderInput / 1MOutput / 1MRoute
Databricks Foundation Model Serving$0.500$0.500
Serverless
Scale AI GenAI Platform--
ServerlessPartial

Capabilities

No model capability flags are currently sourced.

Benchmark peer barsfor Coding

No task-mapped benchmark peers are available for this model yet.

Migration checks

No linked migration route is available for this model yet.