second-state / Llama-4-Scout-17B-16E-Instruct-GGUF

huggingface.co
Total runs: 463
24-hour runs: 0
7-day runs: 42
30-day runs: 96
Model's Last Updated: April 14 2025
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Introduction of Llama-4-Scout-17B-16E-Instruct-GGUF

Model Details of Llama-4-Scout-17B-16E-Instruct-GGUF


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

ONLY text mode of Llama-4 supported for now!

Original Model

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

Run with LlamaEdge
  • LlamaEdge version: v0.16.15 and above

  • Prompt template

    • Prompt type: llama-4-chat

    • Prompt string

      <|begin_of_text|><|header_start|>system<|header_end|>
      
      {system_prompt}<|eot|><|header_start|>user<|header_end|>
      
      {user_message_1}<|eot|><|header_start|>assistant<|header_end|>
      
      {assistant_message_1}<|eot|><|header_start|>user<|header_end|>
      
      {user_message_2}<|eot|>
      <|header_start|>assistant<|header_end|>
      
  • Context size: 10M

  • Run as LlamaEdge service

    wasmedge --dir .:. --nn-preload default:GGML:AUTO:Llama-4-Scout-17B-16E-Instruct-Q5_K_M.gguf \
      llama-api-server.wasm \
      --prompt-template llama-4-chat \
      --ctx-size 1000000 \
      --model-name Llama-4-Scout
    
  • Run as LlamaEdge command app

    wasmedge --dir .:. --nn-preload default:GGML:AUTO:Llama-4-Scout-17B-16E-Instruct-Q5_K_M.gguf \
      llama-chat.wasm \
      --prompt-template llama-4-chat \
      --ctx-size 1000000
    
Quantized GGUF Models
Name Quant method Bits Size Use case
Llama-4-Scout-17B-16E-Instruct-Q2_K.gguf Q2_K 2 39.6 GB smallest, significant quality loss - not recommended for most purposes
Llama-4-Scout-17B-16E-Instruct-Q3_K_L-00001-of-00002.gguf Q3_K_L 3 29.8 GB small, substantial quality loss
Llama-4-Scout-17B-16E-Instruct-Q3_K_L-00002-of-00002.gguf Q3_K_L 3 26.1 GB small, substantial quality loss
Llama-4-Scout-17B-16E-Instruct-Q3_K_M-00001-of-00002.gguf Q3_K_M 3 29.8 GB very small, high quality loss
Llama-4-Scout-17B-16E-Instruct-Q3_K_M-00002-of-00002.gguf Q3_K_M 3 21.9 GB very small, high quality loss
Llama-4-Scout-17B-16E-Instruct-Q3_K_S-00001-of-00002.gguf Q3_K_S 3 29.7 GB very small, high quality loss
Llama-4-Scout-17B-16E-Instruct-Q3_K_S-00002-of-00002.gguf Q3_K_S 3 17.0 GB very small, high quality loss
Llama-4-Scout-17B-16E-Instruct-Q4_0-00001-of-00003.gguf Q4_0 4 30.0 GB legacy; small, very high quality loss - prefer using Q3_K_M
Llama-4-Scout-17B-16E-Instruct-Q4_0-00002-of-00003.gguf Q4_0 4 29.7 GB legacy; small, very high quality loss - prefer using Q3_K_M
Llama-4-Scout-17B-16E-Instruct-Q4_0-00003-of-00003.gguf Q4_0 4 1.20 GB legacy; small, very high quality loss - prefer using Q3_K_M
Llama-4-Scout-17B-16E-Instruct-Q4_K_M-00001-of-00003.gguf Q4_K_M 4 29.9 GB medium, balanced quality - recommended
Llama-4-Scout-17B-16E-Instruct-Q4_K_M-00002-of-00003.gguf Q4_K_M 4 29.8 GB medium, balanced quality - recommended
Llama-4-Scout-17B-16E-Instruct-Q4_K_M-00003-of-00003.gguf Q4_K_M 4 5.66 GB medium, balanced quality - recommended
Llama-4-Scout-17B-16E-Instruct-Q4_K_S-00001-of-00003.gguf Q4_K_S 4 29.7 GB small, greater quality loss
Llama-4-Scout-17B-16E-Instruct-Q4_K_S-00002-of-00003.gguf Q4_K_S 4 29.7 GB small, greater quality loss
Llama-4-Scout-17B-16E-Instruct-Q4_K_S-00003-of-00003.gguf Q4_K_S 4 2.04 GB small, greater quality loss
Llama-4-Scout-17B-16E-Instruct-Q5_0-00001-of-00003.gguf Q5_0 5 29.9 GB legacy; medium, balanced quality - prefer using Q4_K_M
Llama-4-Scout-17B-16E-Instruct-Q5_0-00002-of-00003.gguf Q5_0 5 29.8 GB legacy; medium, balanced quality - prefer using Q4_K_M
Llama-4-Scout-17B-16E-Instruct-Q5_0-00003-of-00003.gguf Q5_0 5 14.6 GB legacy; medium, balanced quality - prefer using Q4_K_M
Llama-4-Scout-17B-16E-Instruct-Q5_K_M-00001-of-00003.gguf Q5_K_M 5 29.8 GB large, very low quality loss - recommended
Llama-4-Scout-17B-16E-Instruct-Q5_K_M-00002-of-00003.gguf Q5_K_M 5 29.8 GB large, very low quality loss - recommended
Llama-4-Scout-17B-16E-Instruct-Q5_K_M-00003-of-00003.gguf Q5_K_M 5 16.9 GB large, very low quality loss - recommended
Llama-4-Scout-17B-16E-Instruct-Q5_K_S-00001-of-00003.gguf Q5_K_S 5 29.9 GB large, low quality loss - recommended
Llama-4-Scout-17B-16E-Instruct-Q5_K_S-00002-of-00003.gguf Q5_K_S 5 29.8 GB large, low quality loss - recommended
Llama-4-Scout-17B-16E-Instruct-Q5_K_S-00003-of-00003.gguf Q5_K_S 5 14.6 GB large, low quality loss - recommended
Llama-4-Scout-17B-16E-Instruct-Q6_K-00001-of-00003.gguf Q6_K 6 30.0 GB very large, extremely low quality loss
Llama-4-Scout-17B-16E-Instruct-Q6_K-00002-of-00003.gguf Q6_K 6 29.6 GB very large, extremely low quality loss
Llama-4-Scout-17B-16E-Instruct-Q6_K-00003-of-00003.gguf Q6_K 6 28.9 GB very large, extremely low quality loss
Llama-4-Scout-17B-16E-Instruct-Q8_0-00001-of-00004.gguf Q8_0 8 29.5 GB very large, extremely low quality loss - not recommended
Llama-4-Scout-17B-16E-Instruct-Q8_0-00002-of-00004.gguf Q8_0 8 29.7 GB very large, extremely low quality loss - not recommended
Llama-4-Scout-17B-16E-Instruct-Q8_0-00003-of-00004.gguf Q8_0 8 29.7 GB very large, extremely low quality loss - not recommended
Llama-4-Scout-17B-16E-Instruct-Q8_0-00004-of-00004.gguf Q8_0 8 25.7 GB very large, extremely low quality loss - not recommended
Llama-4-Scout-17B-16E-Instruct-f16-00001-of-00008.gguf f16 16 30.0 GB
Llama-4-Scout-17B-16E-Instruct-f16-00002-of-00008.gguf f16 16 29.5 GB
Llama-4-Scout-17B-16E-Instruct-f16-00003-of-00008.gguf f16 16 29.1 GB
Llama-4-Scout-17B-16E-Instruct-f16-00004-of-00008.gguf f16 16 29.5 GB
Llama-4-Scout-17B-16E-Instruct-f16-00005-of-00008.gguf f16 16 29.5 GB
Llama-4-Scout-17B-16E-Instruct-f16-00006-of-00008.gguf f16 16 29.1 GB
Llama-4-Scout-17B-16E-Instruct-f16-00007-of-00008.gguf f16 16 29.5 GB
Llama-4-Scout-17B-16E-Instruct-f16-00008-of-00008.gguf f16 16 9.41 GB

Quantized with llama.cpp b5074.

Runs of second-state Llama-4-Scout-17B-16E-Instruct-GGUF on huggingface.co

463
Total runs
0
24-hour runs
0
3-day runs
42
7-day runs
96
30-day runs

More Information About Llama-4-Scout-17B-16E-Instruct-GGUF huggingface.co Model

More Llama-4-Scout-17B-16E-Instruct-GGUF license Visit here:

https://choosealicense.com/licenses/llama4

Llama-4-Scout-17B-16E-Instruct-GGUF huggingface.co

Llama-4-Scout-17B-16E-Instruct-GGUF huggingface.co is an AI model on huggingface.co that provides Llama-4-Scout-17B-16E-Instruct-GGUF's model effect (), which can be used instantly with this second-state Llama-4-Scout-17B-16E-Instruct-GGUF model. huggingface.co supports a free trial of the Llama-4-Scout-17B-16E-Instruct-GGUF model, and also provides paid use of the Llama-4-Scout-17B-16E-Instruct-GGUF. Support call Llama-4-Scout-17B-16E-Instruct-GGUF model through api, including Node.js, Python, http.

Llama-4-Scout-17B-16E-Instruct-GGUF huggingface.co Url

https://huggingface.co/second-state/Llama-4-Scout-17B-16E-Instruct-GGUF

second-state Llama-4-Scout-17B-16E-Instruct-GGUF online free

Llama-4-Scout-17B-16E-Instruct-GGUF huggingface.co is an online trial and call api platform, which integrates Llama-4-Scout-17B-16E-Instruct-GGUF's modeling effects, including api services, and provides a free online trial of Llama-4-Scout-17B-16E-Instruct-GGUF, you can try Llama-4-Scout-17B-16E-Instruct-GGUF online for free by clicking the link below.

second-state Llama-4-Scout-17B-16E-Instruct-GGUF online free url in huggingface.co:

https://huggingface.co/second-state/Llama-4-Scout-17B-16E-Instruct-GGUF

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

Llama-4-Scout-17B-16E-Instruct-GGUF is an open source model from GitHub that offers a free installation service, and any user can find Llama-4-Scout-17B-16E-Instruct-GGUF on GitHub to install. At the same time, huggingface.co provides the effect of Llama-4-Scout-17B-16E-Instruct-GGUF install, users can directly use Llama-4-Scout-17B-16E-Instruct-GGUF installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

Llama-4-Scout-17B-16E-Instruct-GGUF install url in huggingface.co:

https://huggingface.co/second-state/Llama-4-Scout-17B-16E-Instruct-GGUF

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Llama-4-Scout-17B-16E-Instruct-GGUF huggingface.co Url

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