HomeLlama4-Scout-17B-16E-Instruct
109B
Model parameter quantity
Meta
Affiliated organization
Open Source
License Type
April 5, 2025
Release time
Model Introduction
The Llama 4 models are auto-regressive language models that use a mixture-of-experts (MoE) architecture and incorporate early fusion for native multimodality
Comprehensive score
Language dialogue
Knowledge reserve
Reasoning association
Mathematical calculation
Code writing
Command following
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Language comprehension ability
Often makes semantic misjudgments, leading to obvious logical disconnects in responses.
5.3
Knowledge coverage scope
Possesses core knowledge of mainstream disciplines, but has limited coverage of cutting-edge interdisciplinary fields.
8.4
Reasoning ability
Can perform logical reasoning with more than three steps, though efficiency drops when handling nonlinear relationships.
7.8
Model comparison
Llama4-Scout-17B-16E-Instruct vs Doubao-Seed-1.6-251015 (Thinking)
The deep reasoning model released by ByteDance, which supports manual switching of deep reasoning, and its performance is significantly improved compared to doubao-1.5.
Llama4-Scout-17B-16E-Instruct vs Doubao-Seed-1.6-thinking-250715
The latest version of the seed series model launched by ByteDance, which supports the thinking mode.
Related model
Llama4-Maverick-17B-128E-Instruct
The Llama 4 models are auto-regressive language models that use a mixture-of-experts (MoE) architecture and incorporate early fusion for native multimodality.
Llama4-Maverick-17B-128E-Instruct
The Llama 4 models are auto-regressive language models that use a mixture-of-experts (MoE) architecture and incorporate early fusion for native multimodality.
Llama3.1-8B-Instruct
Llama3.1 are multilingual and have a significantly longer context length of 128K, state-of-the-art tool use, and overall stronger reasoning capabilities.
Llama3.1-405B-Instruct-FP8
Llama 3.1 405B is the first openly available model that rivals the top AI models when it comes to state-of-the-art capabilities in general knowledge, steerability, math, tool use, and multilingual translation.
Llama3.2-3B-Instruct
The Llama 3.2 3B models support context length of 128K tokens and are state-of-the-art in their class for on-device use cases like summarization, instruction following, and rewriting tasks running locally at the edge.
Relevant documents
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