LLM Reference

MT0 Small

Released
2024-01-01
Last refreshed
2026-05-19
Status
Researched 16d ago

MT0 Small has model metadata, but missing tracked provider pricing keeps it from being a default production pick.

Use it for

  • Teams evaluating general LLM work
  • Workloads that can use a 1k context window

Do not use it for

  • Cost-sensitive launches that need sourced token pricing
  • Vision or document-understanding workloads
  • Strict JSON or tool-calling flows
Specifications
Family
MT0
Released
2024-01-01
Context
1k
Parameters
300M
Architecture
Decoder Only
Specialization
general
Training
finetuned
Created by

Pioneering open-source AI collaboration

N/A
Founded 2021
Website
Pricing

No tracked provider token pricing is available yet.

About

The MT0 Small model, part of the BLOOMZ & mT0 family by the BigScience workshop, is a multilingual AI language model with 300 million parameters. Designed for zero-shot cross-lingual generalization, it can understand and follow human instructions in multiple languages without prior training. The model is fine-tuned using the cross-lingual task mixture dataset (xP3) and employs multitask finetuning for efficient multilingual performance. While optimized for English prompts, MT0 Small exhibits robust cross-lingual text generation capabilities, making it suitable for diverse language tasks. Its compact size ensures efficiency in resource-limited settings.

MT0 Small is a model in the MT0 family. The structured metadata tracks a 1k-token context window. No headline benchmark score is tracked for MT0 Small yet.

Top use-case fit

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

Provider price ladder

No tracked provider token pricing is available for this model yet.

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.

Rankings & picks(4)