Llama-4-Scout-17B-16E-Instruct

multimodal

Llama 4 Scout is the lightest model in the next generation of the Llama 4 family, released on April 5, 2025. Llama 4 scout has a MoE architecture of 16 experts, 109 billion of which only 17 billion are permanently active. The model supports native multimodality. It is capable of simultaneously processing text and up to 5 images as input, allowing it to be used effectively in computer vision tasks such as object recognition, image description, and image-based question answering. Creative text generation, step-by-step reasoning, and programming are also among the model's strengths

That said, Llama scout can run efficiently on just a single H100 GPU, making it attractive for local deployment, and with more parameters, Llama scout outperforms lighter weight models in the segment on benchmarks.

But perhaps the most important feature of the model is its record-breaking context window support of up to 10 million tokens! which makes it ideal for working with large documents, code, multi-page queries and lengthy dialog sessions.


Announce Date: 05.04.2025
Parameters: 109B
Experts: 16
Activated at inference: 17B
Context: 10486K
Layers: 48, using full attention: 12
Attention Type: Chunked Attention
Developer: Meta AI
Transformers Version: 4.51.0
vLLM Version: 0.8.3
License: LLAMA 4

Public endpoint

Use our pre-built public endpoints for free to test inference and explore Llama-4-Scout-17B-16E-Instruct capabilities. You can obtain an API access token on the token management page after registration and verification.
Model Name Context Type GPU Status Link

API access to Llama-4-Scout-17B-16E-Instruct endpoints

There are no public endpoints for this model yet.

Private endpoint

An endpoint is a server with pre-installed software that automatically downloads neural network weights and launches an OpenAI-compatible API to handle incoming requests.

A private endpoint is created within the user's project, belongs exclusively to the user, and is billed per server configuration in accordance with the infrastructure pricing.

We recommend creating private endpoints when you need to:

  • achieve maximum endpoint performance,
  • access the full context window for processing large requests and conversations,
  • ensure maximum security by processing data in a dedicated, isolated environment.

Recommended server configurations for creating a private inference endpoint Llama-4-Scout-17B-16E-Instruct

Prices:
Name GPU Price, hour TPS Max Concurrency
h200-1.16.128.240
250,000.0
1 $4.74 2.774 Launch
teslaa100-2.24.256.240
250,000.0
tensor
2 $4.93 54.27 4.170 Launch
teslaa100-2.24.256.320.nvlink
250,000.0
tensor
2 $4.94 4.170 Launch
rtx5090-4.16.128.320
250,000.0
tensor
4 $5.76 1.308 Launch
rtx4090-6.44.256.240
250,000.0
pipeline
6 $5.84 30.03 1.721 Launch
dedicated-rtx3090-8.64.128.960-1
250,000.0
tensor
8 $6.04 4.642 Launch
rtx4090-8.44.256.240
250,000.0
tensor
8 $7.52 4.619 Launch
h100-2.24.256.240
250,000.0
tensor
2 $7.85 61.60 4.836 Launch
h100nvl-2.24.192.240
250,000.0
tensor
2 $8.17 5.413 Launch
h200-2.24.256.240.nvlink
250,000.0
tensor
2 $9.41 11.213 Launch
h200-6.52.896.640
10,485,760.0
pipeline
6 $28.36 1.366 Launch
h200-8.52.1024.640
10,485,760.0
tensor
8 $37.34 1.896 Launch
h200-8.52.1024.640.nvlink
10,485,760.0
tensor
8 $37.34 1.896 Launch
Prices:
Name GPU Price, hour TPS Max Concurrency
h200-1.16.128.240
250,000.0
1 $4.74 2.871 Launch
rtx4090-8.44.256.240
250,000.0
tensor
8 $7.52 49.91 6.370 Launch
h100-2.24.256.240
250,000.0
tensor
2 $7.85 68.07 4.714 Launch
h100nvl-2.24.192.240
250,000.0
tensor
2 $8.17 8.168 Launch
rtx5090-6.44.256.240
250,000.0
pipeline
6 $8.86 6.819 Launch
h200-2.24.256.240.nvlink
250,000.0
tensor
2 $9.41 113.64 19.767 Launch
rtx5090-8.44.256.240
250,000.0
tensor
8 $11.55 15.147 Launch
h200-6.52.896.640
10,485,760.0
pipeline
6 $28.36 2.653 Launch
h200-8.52.1024.640
10,485,760.0
tensor
8 $37.34 3.714 Launch
h200-8.52.1024.640.nvlink
10,485,760.0
tensor
8 $37.34 3.714 Launch
Prices:
Name GPU Price, hour TPS Max Concurrency
teslaa100-4.16.256.480
250,000.0
tensor
4 $9.17 5.757 Launch
h200-2.24.256.320
250,000.0
tensor
2 $9.42 3.241 Launch
h200-2.24.256.320.nvlink
250,000.0
tensor
2 $9.42 3.241 Launch
teslaa100-4.32.384.320.nvlink
250,000.0
tensor
4 $9.50 5.757 Launch
h100nvl-3.24.384.480
250,000.0
pipeline
3 $12.38 2.779 Launch
h100-4.16.256.320
250,000.0
tensor
4 $14.97 5.084 Launch
h100nvl-4.32.384.320
250,000.0
tensor
4 $16.22 8.538 Launch
h200-6.52.896.640
10,485,760.0
pipeline
6 $28.36 1.125 Launch
h200-8.52.1024.640
10,485,760.0
tensor
8 $37.34 1.653 Launch
h200-8.52.1024.640.nvlink
10,485,760.0
tensor
8 $37.34 1.653 Launch

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