--- title: "Llama 4 Scout 17B-16E Instruct | Aguasto" description: "Research reference for Llama 4 Scout 17B-16E 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-4-scout-17b-16e-instruct" last-updated: "2026-10-13" --- # Llama 4 Scout 17B-16E Instruct | Aguasto Canonical HTML: [Llama 4 Scout 17B-16E Instruct](https://www.aguasto.com/models/llama-4-scout-17b-16e-instruct) > Research reference for Llama 4 Scout 17B-16E 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 4 Scout 17B-16E 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 4 Scout 17B-16E 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-4-Scout-17B-16E-Instruct[Meta Llama4Scout17B16EInstruct official model card (external source)](https://huggingface.co/meta-llama/Llama-4-Scout-17B-16E-Instruct) · [Llama4Community License (external source)](https://github.com/meta-llama/llama-models/blob/main/models/llama4/LICENSE) Architecture Autoregressive mixture-of-experts model with early-fusion native image/text input[Meta Llama4Scout17B16EInstruct official model card (external source)](https://huggingface.co/meta-llama/Llama-4-Scout-17B-16E-Instruct) · [Llama4Community License (external source)](https://github.com/meta-llama/llama-models/blob/main/models/llama4/LICENSE) Total parameters 109 billionPublished rounded counts; total stored weights determine the preliminary footprint, including all MoE experts.[Meta Llama4Scout17B16EInstruct official model card (external source)](https://huggingface.co/meta-llama/Llama-4-Scout-17B-16E-Instruct) · [Llama4Community License (external source)](https://github.com/meta-llama/llama-models/blob/main/models/llama4/LICENSE) Active parameters 17 billion per tokenActive parameters are a compute-related count, not the model's full stored weight count.[Meta Llama4Scout17B16EInstruct official model card (external source)](https://huggingface.co/meta-llama/Llama-4-Scout-17B-16E-Instruct) · [Llama4Community License (external source)](https://github.com/meta-llama/llama-models/blob/main/models/llama4/LICENSE) Modalities text-input, image-input, text-output[Meta Llama4Scout17B16EInstruct official model card (external source)](https://huggingface.co/meta-llama/Llama-4-Scout-17B-16E-Instruct) · [Llama4Community License (external source)](https://github.com/meta-llama/llama-models/blob/main/models/llama4/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 Llama4Scout17B16EInstruct official model card (external source)](https://huggingface.co/meta-llama/Llama-4-Scout-17B-16E-Instruct) · [Llama4Community License (external source)](https://github.com/meta-llama/llama-models/blob/main/models/llama4/LICENSE) Release date 2025-04-05[Meta Llama4Scout17B16EInstruct official model card (external source)](https://huggingface.co/meta-llama/Llama-4-Scout-17B-16E-Instruct) · [Llama4Community License (external source)](https://github.com/meta-llama/llama-models/blob/main/models/llama4/LICENSE) Download access Gated: publisher terms / access acceptance[Meta Llama4Scout17B16EInstruct official model card (external source)](https://huggingface.co/meta-llama/Llama-4-Scout-17B-16E-Instruct) · [Llama4Community License (external source)](https://github.com/meta-llama/llama-models/blob/main/models/llama4/LICENSE) License Llama 4 Community LicenseA custom commercial license governs the checkpoint, with attribution, redistribution, derivative naming and acceptable-use obligations. A release-date monthly-active-user threshold greater than 700 million requires a separate Meta grant. Weight download requires accepting the publisher's access conditions; listing the model does not accept those terms on Aguasto's behalf.[Meta Llama4Scout17B16EInstruct official model card (external source)](https://huggingface.co/meta-llama/Llama-4-Scout-17B-16E-Instruct) · [Llama4Community License (external source)](https://github.com/meta-llama/llama-models/blob/main/models/llama4/LICENSE) ### Theoretical weight-memory footprint Using the publisher's approximately 109 billion total parameters at 16 bits per parameter gives **218 GB** (203.0 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 The model card's Transformers example loads BF16 and discusses quantization as a separate deployment choice. Its conditional hardware example does not establish a full-context or production-fit result. Aguasto has not downloaded or tested gated weights. [Meta Llama4Scout17B16EInstruct official model card (external source)](https://huggingface.co/meta-llama/Llama-4-Scout-17B-16E-Instruct) · [Llama4Community License (external source)](https://github.com/meta-llama/llama-models/blob/main/models/llama4/LICENSE) ### Serving considerations - The publisher distinguishes 109B total from 17B activated parameters. Expert routing reduces activated work per token; it does not make the full checkpoint a 17B weight-storage problem. - The model card advertises 10M context, but the exact numeric checkpoint position limit was not readable without gated access. The numeric context field stays unknown rather than turning the rounded advertisement into an exact config value. - Native early-fusion text/image inputs require the correct processor and chat template. The publisher describes testing image understanding up to five images; additional-image behavior needs a separate evaluation. - The card provides a Transformers implementation path. Model-specific vLLM/SGLang compatibility is not asserted by this record; supported model architecture, version, attention and parallelism must be checked independently. - No Aguasto inference offering, deployment, benchmark, GPU fit or throughput is claimed. The record is a technical research reference for this exact checkpoint. [Meta Llama4Scout17B16EInstruct official model card (external source)](https://huggingface.co/meta-llama/Llama-4-Scout-17B-16E-Instruct) · [Llama4Community License (external source)](https://github.com/meta-llama/llama-models/blob/main/models/llama4/LICENSE) #### Framework documentation These are third-party documentation starting points. Support depends on the exact checkpoint, runtime version and hardware. ### Continue the research [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 The register preserves each source's publication and verification date. Manufacturer claims and documentation are attributed; Aguasto has not run the cited products in production. - [Meta Llama4Scout17B16EInstruct official model card ↗](https://huggingface.co/meta-llama/Llama-4-Scout-17B-16E-Instruct) 109B total17B active publisher counts; April5,2025 release; MoE early-fusion multimodal architecture; 10M rounded advertised context; Gated weight access, BF16 example, up-to-five-images test boundary. Publication: date not stated in the reviewed source. Verified: 2026-10-13. - [Llama4Community License ↗](https://github.com/meta-llama/llama-models/blob/main/models/llama4/LICENSE) Version-effective date; Attribution, redistribution, naming and acceptable-use duties; Greater-than700M release-date MAU threshold. Publication: 2025-04-05. 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