xai-models

| Model | Best For | Input $/1M | Output $/1M | Context |

|-------|----------|------------|-------------|---------|

| grok-4-1-fast | Tool calling, agents | $0.20 | $0.50 | 2M |

| grok-4 | Complex reasoning | $3.00 | $15.00 | 256K |

| grok-3-fast | General tasks | $0.20 | $0.50 | 131K |

| grok-3-mini | Lightweight tasks | $0.30 | $0.50 | 131K |

| grok-2-vision | Image analysis | $2.00 | $10.00 | 32K |

```

What's your primary need?

│

├─► Tool calling / Agent workflows

│ └─► grok-4-1-fast ($0.20/$0.50)

│

├─► Complex reasoning / Analysis

│ └─► grok-4 ($3.00/$15.00)

│

├─► General chat / Simple tasks

│ └─► grok-3-fast ($0.20/$0.50)

│

├─► High volume / Cost sensitive

│ └─► grok-3-mini ($0.30/$0.50)

│

└─► Image/Vision tasks

└─► grok-2-vision ($2.00/$10.00)

```

grok-4-1-fast (Recommended for Most Uses)

Best for: Tool calling, agentic workflows, real-time search

```python

# Best choice for X search and sentiment analysis

response = client.chat.completions.create(

model="grok-4-1-fast",

messages=[{"role": "user", "content": "Search X for AAPL sentiment"}]

)

```

Features:

• 2 million token context window
• Optimized for tool calling
• Fast response times
• Best price/performance ratio

Variants:

• grok-4-1-fast-reasoning - Maximum intelligence
• grok-4-1-fast-non-reasoning - Instant responses

grok-4

Best for: Deep analysis, complex reasoning, research

```python

# Use for complex multi-step analysis

response = client.chat.completions.create(

model="grok-4",

messages=[{"role": "user", "content": "Analyze market trends..."}]

)

```

Features:

• Highest reasoning capability
• Best for complex tasks
• 256K context window

grok-3-fast

Best for: General purpose, balanced performance

```python

# Good default choice for most tasks

response = client.chat.completions.create(

model="grok-3-fast",

messages=[{"role": "user", "content": "Summarize this..."}]

)

```

Features:

• Fast responses
• 131K context
• Good balance of speed/quality

grok-3-mini

Best for: High-volume, cost-sensitive applications

```python

# Use for bulk processing

response = client.chat.completions.create(

model="grok-3-mini",

messages=[{"role": "user", "content": "Classify: ..."}]

)

```

Features:

• Lowest latency
• Most cost-effective
• Good for simple tasks

grok-2-vision

Best for: Image analysis, charts, screenshots

```python

import base64

# Encode image

with open("chart.png", "rb") as f:

image_data = base64.b64encode(f.read()).decode()

response = client.chat.completions.create(

model="grok-2-vision",

messages=[{

"role": "user",

"content": [

{"type": "text", "text": "Analyze this chart"},

{"type": "image_url", "image_url": {"url": f"data:image/png;base64,{image_data}"}}

]

}]

)

```

1. Use the Right Model

```python

# For filtering/classification - use mini

filter_response = client.chat.completions.create(

model="grok-3-mini",

messages=[{"role": "user", "content": f"Is this relevant? {text}"}]

)

# For analysis - use fast

if is_relevant:

analysis = client.chat.completions.create(

model="grok-4-1-fast",

messages=[{"role": "user", "content": f"Analyze: {text}"}]

)

```

2. Leverage Caching

Cached input tokens are 75% cheaper:

• Regular: $0.20/1M
• Cached: $0.05/1M

3. Batch Similar Requests

```python

# Instead of 10 separate calls, batch them

texts = ["text1", "text2", "text3"]

batch_prompt = "Analyze these texts:\n" + "\n".join(texts)

response = client.chat.completions.create(

model="grok-3-fast",

messages=[{"role": "user", "content": batch_prompt}]

)

```

| Tool | Cost per 1,000 calls |

|------|---------------------|

| X Search | $5.00 |

| Web Search | $5.00 |

| Code Execution | $5.00 |

| Document Search | $2.50 |

| Model | Context | Pages of Text | Hours of Audio |

|-------|---------|---------------|----------------|

| grok-4-1-fast | 2M | ~6,000 | ~50 |

| grok-4 | 256K | ~800 | ~6 |

| grok-3-fast | 131K | ~400 | ~3 |

| grok-2-vision | 32K | ~100 | ~1 |

| Capability | 4.1 Fast | 4 | 3 Fast | 3 Mini | 2 Vision |

|------------|----------|---|--------|--------|----------|

| Tool Calling | ⭐⭐⭐ | ⭐⭐ | ⭐ | ⭐ | ❌ |

| Reasoning | ⭐⭐ | ⭐⭐⭐ | ⭐⭐ | ⭐ | ⭐⭐ |

| Speed | ⭐⭐⭐ | ⭐ | ⭐⭐⭐ | ⭐⭐⭐ | ⭐⭐ |

| Cost | ⭐⭐⭐ | ⭐ | ⭐⭐⭐ | ⭐⭐⭐ | ⭐⭐ |

| Vision | ❌ | ❌ | ❌ | ❌ | ⭐⭐⭐ |

| X Search | ⭐⭐⭐ | ⭐⭐ | ⭐⭐ | ⭐ | ❌ |

Financial Sentiment Pipeline

```python

MODELS = {

"filter": "grok-3-mini", # Fast filtering

"analyze": "grok-4-1-fast", # Tool calling + analysis

"deep": "grok-4" # Complex reasoning (rare)

}

```

High-Volume Processing

```python

MODELS = {

"bulk": "grok-3-mini",

"quality_check": "grok-3-fast"

}

```

Research & Analysis

```python

MODELS = {

"search": "grok-4-1-fast",

"analyze": "grok-4",

"summarize": "grok-3-fast"

}

```

```python

import os

from openai import OpenAI

client = OpenAI(

api_key=os.getenv("XAI_API_KEY"),

base_url="https://api.x.ai/v1"

)

# List available models

models = client.models.list()

for model in models.data:

print(f"{model.id}")

# Use specific model

response = client.chat.completions.create(

model="grok-4-1-fast",

messages=[{"role": "user", "content": "Hello!"}],

max_tokens=100

)

```

• xai-auth - Authentication setup
• xai-agent-tools - Tool calling
• xai-sentiment - Sentiment analysis

• [xAI Models](https://docs.x.ai/docs/models)
• [Pricing](https://docs.x.ai/docs/models)
• [Grok 4.1 Fast Announcement](https://x.ai/news/grok-4-1-fast/)