Model reference · open weights

vicuna-delta

LLMs lmsys Text gen 1 build Licence not stated 522 dl/mo

vicuna-delta is an open-weight language model from lmsys. vicuna-13b-delta-v0 (BF16) weighs 26.0 GB; the smallest configuration that runs it is 2× RTX 4060 Ti 16 GB.

For self-hosting, compare this build's requirements below with the GPU you plan to rent.

  • vicuna-delta is a text-generation model developed by lmsys that serves as a delta update for the LLaMA architecture.
  • It is designed for research on large language models and chatbots, intended for researchers and hobbyists in natural language processing.
  • The model has a context length of 2048 tokens and is distributed under a non-commercial license.

Summary of the lmsys/vicuna-13b-delta-v0 model card, 2026-10-01

What it is

Released bylmsys
Released2023-04-03
VRAM26.0 GB for the weights

What it runs on

Memory and cards for vicuna-13b-delta-v0 (BF16)

26.0 GBweights, file size
819 MBcache per 1K tokens
659 MBruntime overhead, at least
2,048 tokenscontext max
CardRequests at onceContext maxMemory
2K each
RTX 3060 12 GB … RTX 4090 24 GB
4 smaller cards
RTX 5090 32 GB2all 2K31.0 GB
L40S 48 GB10all 2K44.0 GB
A100 80 GB30all 2K78.2 GB
H100 80 GB28all 2K78.1 GB
RTX PRO 6000 Blackwell 96 GB38all 2K93.8 GB
DGX Spark (GB10) 128 GB unified46all 2K107 GB
H200 141 GB64all 2K138 GB
B200 180 GB86all 2K176 GB
2× RTX 4060 Ti 16 GB
tensor parallel
2all 2K15.4 GB a card
2× RTX 4090 24 GB
tensor parallel
11all 2K23.4 GB a card
2× RTX 3090 24 GB
tensor parallel
11all 2K23.4 GB a card
2× RTX 5090 32 GB
tensor parallel
20all 2K31.0 GB a card
Memory needed at each load
Requests at once2K tokens each
128.4 GB
535.1 GB
840.1 GB
1653.5 GB
3280.4 GB
64134 GB

One card, with vLLM's small-card settings.

From the model card

What lmsys says about vicuna-delta

Read the model card

NOTE: New version available Please check out a newer version of the weights here.

NOTE: This "delta model" cannot be used directly. Users have to apply it on top of the original LLaMA weights to get actual Vicuna weights. See instructions.

Vicuna Model Card

Model Details

Vicuna is a chat assistant trained by fine-tuning LLaMA on user-shared conversations collected from ShareGPT.

  • Developed by: LMSYS
  • Model type: An auto-regressive language model based on the transformer architecture.
  • License: Non-commercial license
  • Finetuned from model: LLaMA.

Model Sources

  • Repository: https://github.com/lm-sys/FastChat
  • Blog: https://lmsys.org/blog/2023-03-30-vicuna/
  • Paper: https://arxiv.org/abs/2306.05685
  • Demo: https://chat.lmsys.org/

Uses

The primary use of Vicuna is research on large language models and chatbots. The primary intended users of the model are researchers and hobbyists in natural language processing, machine learning, and artificial intelligence.

How to Get Started with the Model

Command line interface: https://github.com/lm-sys/FastChat#vicuna-weights. APIs (OpenAI API, Huggingface API): https://github.com/lm-sys/FastChat/tree/main#api.

Training Details

Vicuna v0 is fine-tuned from LLaMA with supervised instruction fine-tuning. The training data is around 70K conversations collected from ShareGPT.com. See more details in the "Training Details of Vicuna Models" section in the appendix of this paper.

Evaluation

Vicuna is evaluated with standard benchmarks, human preference, and LLM-as-a-judge. See more details in this paper and leaderboard.

Difference between different versions of Vicuna

See vicuna_weights_version.md

Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.

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