Samba 3.8B
No estimate
No hardware requirements for this model
The weights for this model have not been published, so it cannot be downloaded or run on your own hardware at any size. It is reachable only through its provider, and no graphics card changes that.
On record
Full specification
Everything on record for this model. Most of it describes how it was trained rather than how it runs — useful context for judging how much work went into it, and how it compares with models built at a different scale.
Origin
Who built this model, where, and when it was published.
- Organisation
- Microsoft,University of Illinois Urbana-Champaign (UIUC)
- Organisation type
- Industry,Academia
- Country
- United States of America
- Published
- 11 June 2024
- Authors
- Liliang Ren, Yang Liu, Yadong Lu, Yelong Shen, Chen Liang, Weizhu Chen
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Language modeling/generation
Size
How large the model is and how much data it was trained on. Parameters are the figure that decides whether it fits on a given graphics card.
- Parameters
- 3.8B
- Training data
- tokens
- Epochs
- 1
3.8B, table 10
3.2T tokens
Training compute
The arithmetic performed to train the model, measured in floating-point operations. It is a measure of what the training run cost, not of how fast the finished model answers you.
- Training compute
- 7.3 × 10²² FLOP
- How it was established
- Operation counting
"We scale SAMBA with 421M, 1.3B, 1.7B and up to 3.8B parameters. In particular, the largest 3.8B base model pre-trained with 3.2T tokens achieves a 71.2 score for MMLU [HBB+21], 54.9 for HumanEval [CTJ+21], and 69.6 for GSM8K" 3.8B * 3.2T * 6 = 7.3e22
Availability
Whether you can obtain the model and run it on your own hardware, which is what decides if any of the graphics-card figures on this page apply.
- Weights
- Closed — provider access only
- Model access
- Unreleased
- Training code
- Open source
training code: https://github.com/microsoft/Samba
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Confident
Sources
Where this record came from and when it was last checked.
- Reference
- Samba: Simple Hybrid State Space Models for Efficient Unlimited Context Language Modeling
- Last updated
- 28 November 2025
What the numbers mean
What this model is
Samba 3.8B was published by Microsoft,University of Illinois Urbana-Champaign (UIUC), in United States of America, in June 2024. It comes out of industry,Academia.
It works in Language, and is recorded as doing language modeling/generation.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
Training and provenance
Training it took roughly 7.3 × 10²² FLOP of computation — a measure of what producing the model cost, not of how fast it answers.
Answers
Samba 3.8B — common questions
Is Samba 3.8B open source?
No. Samba 3.8B has not had its weights published, so it exists only as a service controlled by its owner.
How many parameters does Samba 3.8B have?
Samba 3.8B has 3.8B parameters. 3.8B, table 10. That figure is the total, and it is what decides how much memory the model needs — roughly half a gigabyte per billion at the compression most people use.
Who created Samba 3.8B?
Samba 3.8B was published by Microsoft,University of Illinois Urbana-Champaign (UIUC), based in United States of America, categorised as industry,Academia.
When was Samba 3.8B released?
Samba 3.8B was published in June 2024. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
What is Samba 3.8B used for?
Samba 3.8B works in Language, and is recorded as handling language modeling/generation. These are the areas it was designed around; they describe intent rather than a hard boundary.
How much compute was used to train Samba 3.8B?
Around 7.3 × 10²² FLOP. That measures what producing the model cost and says nothing about how quickly it answers once trained — inference speed comes from memory bandwidth, not from the training budget.
What GPU do I need to run Samba 3.8B?
None. Samba 3.8B is a closed model — its weights were never published, so it cannot be downloaded or run on your own hardware at any price. It is reachable only through its provider.
The other direction
Looking at it from the other side?
This page starts from the model. If you already own a card and want to know everything it will run, start from the hardware instead.