Llama 3.2 1B Instruct
Model Overview¶
The Llama 3.2 collection of multilingual large language models (LLMs) is a collection of pretrained and instruction-tuned generative models in 1B and 3B sizes (text in/text out). The Llama 3.2 instruction-tuned text only models are optimized for multilingual dialogue use cases, including agentic retrieval and summarization tasks.
- Model Architecture: Llama 3.2 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety.
- Model Release Date: Sept 25, 2024.
- Model Source: meta-llama/Llama-3.2-1B-Instruct
- License: llama3.2
- Supported languages: English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai
QPC Configurations¶
| Precision | SoCs / Tensor slicing | NSP-Cores (per SoC) | Full Batch Size | Chunking Prompt Length | Context Length (CL) | Generated URL | Download | Generation Date |
|---|---|---|---|---|---|---|---|---|
| MXFP6 | 2 | 16 | 1 | 128 | 8192 | https://dc00tk1pxen80.cloudfront.net/SDK1.20.4/meta-llama/Llama-3.2-1B-Instruct/Llama-3.2-1B-Instruct_qpc_16cores_128pl_8192cl_1fbs_2devices_mxfp6_mxint8.tar.gz | Download | 16-Jan-2026 |
Run This Model¶
# Download QPC
mkdir -p meta-llama/Llama-3.2-1B-Instruct
cd meta-llama/Llama-3.2-1B-Instruct
wget <Download URL>
tar xzvf <downloaded filename.tar.gz>
# Run QPC
python3 -m QEfficient.cloud.execute --model_name meta-llama/Llama-3.2-1B-Instruct --qpc_path <path/to/qpc> --prompt "# shortest path algorithm\n" --generation_len 128
API Endpoint¶
# Start REST endpoint with vLLM
VLLM_QAIC_MAX_CPU_THREADS=8 VLLM_QAIC_QPC_PATH=/path/to/qpc python3 -m vllm.entrypoints.openai.api_server \
--host 0.0.0.0 \
--port 8000 \
--model meta-llama/Llama-3.2-1B-Instruct \
--max-model-len <Context Length> \
--max-num-seq <Full Batch Size> \
--max-seq_len-to-capture <Chunking Prompt Length> \
--device qaic \
--block-size 32