Model reference · open weights
llama3-CLA-2 is an open-weight language model from answerdotai. llama3-8b-instruct-CLA-2 (BF16) weighs 16.1 GB; the smallest configuration that runs it is 2× RTX 3060 12 GB.
For self-hosting, compare this build's requirements below with the GPU you plan to rent.
Summary of the answerdotai/llama3-8b-instruct-CLA-2 model card, 2026-10-01
What it is
| Released by | answerdotai |
|---|---|
| Released | 2024-07-18 |
| VRAM | 16.1 GB for the weights |
What it runs on
| Card | Requests at once | Context max | Memory |
|---|---|---|---|
| 8K each | |||
| RTX 3060 12 GB … RTX 4060 Ti 16 GB 2 smaller cards | |||
| RTX 3090 24 GB | 6 | all 8K | 23.4 GB |
| RTX 4090 24 GB | 6 | all 8K | 23.4 GB |
| RTX 5090 32 GB | 13 | all 8K | 31.0 GB |
| L40S 48 GB | 25 | all 8K | 44.0 GB |
| A100 80 GB | 57 | all 8K | 78.2 GB |
| H100 80 GB | 53 | all 8K | 78.1 GB |
| RTX PRO 6000 Blackwell 96 GB | 67 | all 8K | 93.8 GB |
| DGX Spark (GB10) 128 GB unified | 80 | all 8K | 107 GB |
| H200 141 GB | 109 | all 8K | 138 GB |
| B200 180 GB | 143 | all 8K | 176 GB |
| 2× RTX 3060 12 GB tensor parallel | 5 | all 8K | 11.6 GB a card |
| 2× RTX 4060 Ti 16 GB tensor parallel | 12 | all 8K | 15.4 GB a card |
| 2× RTX 4090 24 GB tensor parallel | 27 | all 8K | 23.4 GB a card |
| 2× RTX 3090 24 GB tensor parallel | 27 | all 8K | 23.4 GB a card |
| Requests at once | 8K tokens each |
|---|---|
| 1 | 17.9 GB |
| 5 | 22.2 GB |
| 8 | 25.4 GB |
| 16 | 34.0 GB |
| 32 | 51.2 GB |
| 64 | 85.5 GB |
One card, with vLLM's small-card settings.
From the model card
Transformers : https://github.com/huggingface/transformers/blob/47fedc1665f14a60260b1b8357e682669300093a/src/transformers/models/llama/modeling_llama.py
Training Script: https://github.com/AnswerDotAI/fsdp_qlora/blob/3f7c583e985ff35e37a7b7497a7d4fedb77df695/experiments/cla/train.sh
This model shares KV activations every 2 layers. For example, layer 1 uses layer 0 kv activations, layer 3 uses layer 2 kv activations, etc..
Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.