meta/llama-4-scout-instruct 🔢📝 → 📝

⭐ Official ▶️ 3.2M runs 📅 Apr 2025 ⚙️ Cog 0.13.8-dev+g1050bdd3 ⚖️ License
code-generation question-answering text-generation

About

A 17 billion parameter model with 16 experts

Example Output

Prompt:

"Hello, Llama!"

Output

Hello! It's nice to meet you. I'm Llama, a large language model developed by Meta. How can I assist you today?

Performance Metrics

0.55s Prediction Time
0.56s Total Time
All Input Parameters 
{
  "top_p": 1,
  "prompt": "Hello, Llama!",
  "max_tokens": 1024,
  "temperature": 0.6,
  "presence_penalty": 0,
  "frequency_penalty": 0
}
Input Parameters
top_p Type: numberDefault: 1
Top-p (nucleus) sampling
prompt Type: stringDefault:
Prompt
max_tokens Type: integerDefault: 1024Range: 2 - 20480
The maximum number of tokens the model should generate as output.
temperature Type: numberDefault: 0.6
The value used to modulate the next token probabilities.
presence_penalty Type: numberDefault: 0
Presence penalty
frequency_penalty Type: numberDefault: 0
Frequency penalty
Output Schema

Output

Type: array • Items Type: string

Example Execution Logs 
Prompt: Hello, Llama!
Input token count: 5
Output token count: 29
TTFT: 0.23s
Tokens per second: 53.68
Total time: 0.54s
Version Details
Version ID
8137b3975c483beadba5dbb424eb6824248cdc8a6746abbcfafb96886e82965f
Version Created
April 5, 2025
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