Llama-SEA-LION-v2-8B
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.
- Published
- 31 July 2024
- Authors
- Lalita Lowphansirikul, Charin Polpanumas, Nawat Jantrakulchai, Sarana Nutanong
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
- 8B
- Training data
- 48,000,000,000 tokens
Continued pretraining (CPT): 4.8e10 tokens Instruction tuning (v2-8B-IT): 1.5e5 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
- 8.8 × 10²¹ FLOP
172800*64*1.979e15*0.40=8.75e21
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Likely
Sources
Where this record came from and when it was last checked.
- Last updated
- 28 November 2025
What the numbers mean
Where it came from
Llama-SEA-LION-v2-8B was published by its authors, in July 2024.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
What went into building it
The training run consumed about 8.8 × 10²¹ FLOP. That figure describes the cost of creating it and has no bearing on how quickly it generates text.
It was trained on about 48,000,000,000 tokens of text.
Answers
Llama-SEA-LION-v2-8B — common questions
When was Llama-SEA-LION-v2-8B released?
Llama-SEA-LION-v2-8B was published in July 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.
How much compute was used to train Llama-SEA-LION-v2-8B?
Around 8.8 × 10²¹ 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 Llama-SEA-LION-v2-8B?
None. Llama-SEA-LION-v2-8B 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.
Is Llama-SEA-LION-v2-8B open source?
The licensing for Llama-SEA-LION-v2-8B was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
How many parameters does Llama-SEA-LION-v2-8B have?
Llama-SEA-LION-v2-8B has 8B parameters. 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.
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.