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Documentation Index

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Retrieve detailed information about a model including its Modelfile, parameters, template, system prompt, and model architecture details.

​
Request

​
Endpoint

POST /api/show

​
Request Body

​
model
string
required
Name of the model to show information for
​
verbose
boolean
default:"false"
Include tensor information in the response (significantly increases response size)
​
system
string
Override the system prompt for display purposes
​
template
string
Deprecated: This parameter is deprecated
​
options
object
Model options to display

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Response

​
Response Fields

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modelfile
string
Complete Modelfile that can be used to recreate the model
​
parameters
string
Formatted string of model parameters (one per line)
​
template
string
Prompt template used by the model
​
system
string
System prompt configured for the model
​
details
object
Model architecture and metadata
​
model_info
object
Low-level model metadata from GGUF/config (key-value pairs)
​
projector_info
object
Vision projector metadata (for multimodal models)
​
messages
array
Pre-configured messages embedded in the model
​
license
string
License information for the model
​
capabilities
array
Array of capabilities (e.g., [“completion”, “vision”, “tools”])
​
modified_at
string
Timestamp of last modification (ISO 8601)
​
remote_model
string
Upstream model name (for remote models)
​
remote_host
string
Upstream Ollama host URL (for remote models)
​
renderer
string
Template renderer used by the model
​
parser
string
Output parser used by the model
​
requires
string
Minimum Ollama version required
​
tensors
array
Tensor information (only when verbose: true)

​
Examples

​
Basic Model Information

curl http://localhost:11434/api/show -d '{
  "model": "llama3.2"
}'

​
Example Response

{
  "modelfile": "# Modelfile generated by \"ollama show\"\n# To build a new Modelfile based on this, replace FROM with:\n# FROM llama3.2\n\nFROM /path/to/model\nTEMPLATE \"\"\"{{ if .System }}<|start_header_id|>system<|end_header_id|>\n\n{{ .System }}<|eot_id|>{{ end }}{{ if .Prompt }}<|start_header_id|>user<|end_header_id|>\n\n{{ .Prompt }}<|eot_id|>{{ end }}<|start_header_id|>assistant<|end_header_id|>\n\n{{ .Response }}<|eot_id|>\"\"\"\nPARAMETER stop <|start_header_id|>\nPARAMETER stop <|end_header_id|>\nPARAMETER stop <|eot_id|>\n",
  "parameters": "stop                          <|start_header_id|>\nstop                          <|end_header_id|>\nstop                          <|eot_id|>",
  "template": "{{ if .System }}<|start_header_id|>system<|end_header_id|>\n\n{{ .System }}<|eot_id|>{{ end }}{{ if .Prompt }}<|start_header_id|>user<|end_header_id|>\n\n{{ .Prompt }}<|eot_id|>{{ end }}<|start_header_id|>assistant<|end_header_id|>\n\n{{ .Response }}<|eot_id|>",
  "details": {
    "parent_model": "",
    "format": "gguf",
    "family": "llama",
    "families": ["llama"],
    "parameter_size": "3B",
    "quantization_level": "Q4_K_M"
  },
  "capabilities": ["completion"],
  "model_info": {
    "general.architecture": "llama",
    "general.file_type": "Q4_K_M",
    "general.parameter_count": 3213052928,
    "llama.attention.head_count": 32,
    "llama.attention.head_count_kv": 8,
    "llama.block_count": 28,
    "llama.context_length": 131072,
    "llama.embedding_length": 3072
  },
  "modified_at": "2024-02-24T12:34:56.789Z"
}

​
Verbose Mode (Including Tensors)

curl http://localhost:11434/api/show -d '{
  "model": "llama3.2",
  "verbose": true
}'

​
Extract Specific Information (Python)

import requests

def get_model_context_length(model_name):
    response = requests.post(
        'http://localhost:11434/api/show',
        json={'model': model_name}
    )
    info = response.json()
    
    # Try to extract context length from model_info
    model_info = info.get('model_info', {})
    family = info['details']['family']
    
    context_key = f"{family}.context_length"
    return model_info.get(context_key, 'Unknown')

context = get_model_context_length('llama3.2')
print(f"Context length: {context}")

​
Display Modelfile (JavaScript)

const response = await fetch('http://localhost:11434/api/show', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({ model: 'llama3.2' })
});

const info = await response.json();
console.log('=== Modelfile ===');
console.log(info.modelfile);

​
Error Responses

​
error
string
Description of the error

​
Common Errors

  • 400 Bad Request: Invalid model name or request format
  • 404 Not Found: Model not found
  • 500 Internal Server Error: Error reading model information
The modelfile field contains a complete, regenerated Modelfile that can be used with ollama create to recreate the model.
Setting verbose: true will include detailed tensor information, which can make the response very large (hundreds of MB for large models).

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