--- title: "Llama 3.3 70B Instruct | Aguasto" description: "Research reference for Llama 3.3 70B Instruct: official checkpoint, license and memory considerations. Documented in Aguasto Research; no Aguasto deployment or API availability is represented." canonical: "https://www.aguasto.com/models/llama-3-3-70b-instruct" last-updated: "2026-10-12" --- # Llama 3.3 70B Instruct | Aguasto Canonical HTML: [Llama 3.3 70B Instruct](https://www.aguasto.com/models/llama-3-3-70b-instruct) > Research reference for Llama 3.3 70B Instruct: official checkpoint, license and memory considerations. Documented in Aguasto Research; no Aguasto deployment or API availability is represented. [Aguasto](https://www.aguasto.com/) [Model Index](https://www.aguasto.com/models) Llama 3.3 70B Instruct [Resources](https://www.aguasto.com/resources) [GPU Library](https://www.aguasto.com/gpus) [Model Index](https://www.aguasto.com/models) [Inference Stack](https://www.aguasto.com/inference-stack) [Learn](https://www.aguasto.com/learn) [Insights](https://www.aguasto.com/insights) [Research](https://www.aguasto.com/research) [Engineering tools](https://www.aguasto.com/tools) Meta / Open-weight checkpoint reference ## Llama 3.3 70B Instruct Documented in Aguasto Research. This checkpoint has not been evaluated or deployed by Aguasto and is not available through an Aguasto API. Original Aguasto conceptual illustration. Not manufacturer geometry, an operating Aguasto asset, or a measured benchmark. Aguasto Research documents third-party hardware, models and software. References do not represent Aguasto inventory, evaluated deployments or available inference services. ### Checkpoint identity Official identifier meta-llama/Llama-3.3-70B-Instruct[Meta Llama 3.3 70B Instruct model card and access conditions (external source)](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct) · [Llama 3.3 Community License (external source)](https://github.com/meta-llama/llama-models/blob/main/models/llama3_3/LICENSE) Architecture Dense autoregressive transformer with grouped-query attention[Meta Llama 3.3 70B Instruct model card and access conditions (external source)](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct) · [Llama 3.3 Community License (external source)](https://github.com/meta-llama/llama-models/blob/main/models/llama3_3/LICENSE) Total parameters 70 billionPublished rounded counts; total stored weights determine the preliminary footprint, including all MoE experts.[Meta Llama 3.3 70B Instruct model card and access conditions (external source)](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct) · [Llama 3.3 Community License (external source)](https://github.com/meta-llama/llama-models/blob/main/models/llama3_3/LICENSE) Active parameters Not verified for this recordActive parameters are a compute-related count, not the model's full stored weight count.[Meta Llama 3.3 70B Instruct model card and access conditions (external source)](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct) · [Llama 3.3 Community License (external source)](https://github.com/meta-llama/llama-models/blob/main/models/llama3_3/LICENSE) Modalities text-input, text-output[Meta Llama 3.3 70B Instruct model card and access conditions (external source)](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct) · [Llama 3.3 Community License (external source)](https://github.com/meta-llama/llama-models/blob/main/models/llama3_3/LICENSE) Context Not verified for this recordNative configuration where directly verified. Extensions, advertised K-labels and configuration differences are preserved in the notes below.[Meta Llama 3.3 70B Instruct model card and access conditions (external source)](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct) · [Llama 3.3 Community License (external source)](https://github.com/meta-llama/llama-models/blob/main/models/llama3_3/LICENSE) Release date 2024-12-06[Meta Llama 3.3 70B Instruct model card and access conditions (external source)](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct) · [Llama 3.3 Community License (external source)](https://github.com/meta-llama/llama-models/blob/main/models/llama3_3/LICENSE) Download access Gated: publisher terms / access acceptance[Meta Llama 3.3 70B Instruct model card and access conditions (external source)](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct) · [Llama 3.3 Community License (external source)](https://github.com/meta-llama/llama-models/blob/main/models/llama3_3/LICENSE) License Llama 3.3 Community LicenseCustom terms include the acceptable-use policy, redistribution notices and Built with Llama attribution, plus naming conditions for distributed models trained using Llama materials or outputs. The release-date 700M monthly-active-user threshold requires a separate Meta license. Review the full terms for a specific use.[Meta Llama 3.3 70B Instruct model card and access conditions (external source)](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct) · [Llama 3.3 Community License (external source)](https://github.com/meta-llama/llama-models/blob/main/models/llama3_3/LICENSE) ### Theoretical weight-memory footprint Using the publisher's approximately 70 billion total parameters at 16 bits per parameter gives **140 GB** (130.4 GiB) of nominal weights. weight GB = total parameters in billions × bits per weight / 8 This estimate excludes KV cache, activations, quantization metadata, non-weight buffers and serving overhead. It is not a tested GPU fit. MoE routing activates only part of the network per token while the complete expert weights still need storage. [Explore the memory estimator](https://www.aguasto.com/tools) #### Quantization Meta documents BF16 and example 8-bit/4-bit loading. Precision reductions require quality and runtime validation; these are not Aguasto benchmark results. [Meta Llama 3.3 70B Instruct model card and access conditions (external source)](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct) · [Llama 3.3 Community License (external source)](https://github.com/meta-llama/llama-models/blob/main/models/llama3_3/LICENSE) ### Serving considerations - 70B is the publisher's approximate total. A separate activated-parameter figure is not stated for this dense model and is left null. - The card specifies 128k context. This record preserves that published unit without inferring an exact integer from the abbreviated value. - The selected checkpoint is text only. Hugging Face requires agreeing to the access conditions and sharing contact information. Aguasto has not downloaded, accepted terms, evaluated or deployed it. [Meta Llama 3.3 70B Instruct model card and access conditions (external source)](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct) · [Llama 3.3 Community License (external source)](https://github.com/meta-llama/llama-models/blob/main/models/llama3_3/LICENSE) #### Framework documentation These are third-party documentation starting points. Support depends on the exact checkpoint, runtime version and hardware. ### Continue the research [vLLM](https://www.aguasto.com/inference-stack/vllm) [SGLang](https://www.aguasto.com/inference-stack/sglang) [Compare model references](https://www.aguasto.com/models/compare) [GPU specification library](https://www.aguasto.com/gpus) [Weights, cache and serving overhead](https://www.aguasto.com/learn/model-weights-and-runtime-memory) ### Sources & verification Reference revision 1 · Reviewed October 12, 2026. Manufacturer claims and documentation are attributed; Aguasto has not run the cited products in production. - [Meta Llama 3.3 70B Instruct model card and access conditions ↗](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct) 70B approximate total; text-only dense transformer / GQA; 128k advertised context; December 6 2024 release; gated download; quantized-loading examples; vLLM / SGLang references. Publication: date not stated in the reviewed source. Verified: 2026-10-12. - [Llama 3.3 Community License ↗](https://github.com/meta-llama/llama-models/blob/main/models/llama3_3/LICENSE) Custom commercial terms; 700M release-date monthly-active-user threshold; attribution, redistribution, naming and acceptable-use conditions. Publication: 2024-12-06. 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