Llama 3.3 70B Instruct
Meta's December 2024 refresh of Llama 3 70B that closes most of the gap with Llama 3.1 405B for chat workloads while remaining tractable on a single H100. Strong instruction following, robust tool-use behaviour, and a 128K context window make it the default choice for production chat at 70B scale.
The 3.3 release was trained on a refreshed instruction-tuning data mix and benefits from Meta's most recent alignment work. It outperforms the much larger 3.1 405B on several reasoning benchmarks at a fraction of inference cost. The licence is the Llama 3 Community License, which permits commercial use unless your service exceeds 700M monthly active users.
Good pick for: production chat at scale, RAG over long documents, agentic workflows where tool use matters, and any 70B-tier replacement for closed proprietary models.
- Parameters
- 70B
- Context length
- 128K
- Modality
- text
- Released
- 2024-12-06
Memory & hardware
- VRAM (fp16)
- 140 GB
- VRAM (Q4)
- 42 GB
- Recommended
- 1× H100 80GB (fp16) or 1× RTX 4090 24GB (Q4)
- Quantizations
- fp16, fp8, q8_0, q5_k_m, q4_k_m, gguf
License: Llama 3 Community License
- SPDX
- —
- Commercial use
- Yes
- Modification
- Yes
- Redistribution
- Yes
Benchmarks
Run it yourself
Drop-in commands for the three most common open-source inference paths. The Ollama tag is a best-effort match against the registry; verify the size variant before pulling.
ollama run llama3.3:70b
vllm serve meta-llama/Llama-3.3-70B-Instruct
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-3.3-70B-Instruct")
model = AutoModelForCausalLM.from_pretrained(
"meta-llama/Llama-3.3-70B-Instruct", device_map="auto", torch_dtype="auto"
)meta-llama/Llama-3.3-70B-Instruct Related models
Same family or similar size — useful when shopping around.
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- Context
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- License
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- License
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