GPT-4o Animate | AI Wisdom

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🎞 ANIMATE · Mode 3 of 5 · +100 XP— GPT-4o

📋Model

⚙️Text

🔄Vision

✅Parameters

🎯 Next: Test →

Step 1 / 4

Speed

What's happening

GPT-4o Model

gpt-4o: OpenAI's most capable natively multimodal model (text + vision + audio)

💡 Analogy

Like a Swiss Army knife vs individual tools — one model handles text, images, and audio natively.

GPT-4o ("omni") is natively multimodal — processes text, images, and audio in one model. Faster and cheaper than GPT-4 Turbo for equivalent tasks.

Console Output

> model: "gpt-4o"
> Context: 128k tokens
> max_tokens: 200 (output cap)
> Response mode: message content

●gpt4o.py

GPT-4o ModelL6–9

1from openai import OpenAI

2import base64

4client = OpenAI()

6# Text: multimodal by default, text only here

7response = client.chat.completions.create(

8 model="gpt-4o",

9 messages=[

10 {"role": "system", "content": "You are a helpful assistant."},

11 {"role": "user", "content": "Explain attention in transformers in 2 sentences."},

12 ],

13 max_tokens=200,

14 temperature=0.7,

15)

16print(response.choices[0].message.content)

17print(f"Tokens: {response.usage.total_tokens}")

19# Vision: pass image URL or base64

20with open("diagram.png", "rb") as f:

21 image_b64 = base64.b64encode(f.read()).decode()

23vision_response = client.chat.completions.create(

24 model="gpt-4o",

25 messages=[{

26 "role": "user",

27 "content": [

28 {"type": "text", "text": "What does this architecture diagram show?"},

29 {"type": "image_url", "image_url": {

30 "url": f"data:image/png;base64,{image_b64}",

31 "detail": "high", # high = 4096 tokens for detail

32 }},

33 ],

34 }],

35)

36print(vision_response.choices[0].message.content)

36 lines

Steps · 4

What's happening

GPT-4o Model

gpt-4o: OpenAI's most capable natively multimodal model (text + vision + audio)

💡 Analogy

Like a Swiss Army knife vs individual tools — one model handles text, images, and audio natively.

GPT-4o ("omni") is natively multimodal — processes text, images, and audio in one model. Faster and cheaper than GPT-4 Turbo for equivalent tasks.

Console Output

> model: "gpt-4o"
> Context: 128k tokens
> max_tokens: 200 (output cap)
> Response mode: message content

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← Back to topic

🎞 ANIMATE · Mode 3 of 5 · +100 XP— GPT-4o

📋Model

⚙️Text

🔄Vision

✅Parameters

🎯 Next: Test →

Step 1 / 4

Speed

What's happening

GPT-4o Model

gpt-4o: OpenAI's most capable natively multimodal model (text + vision + audio)

💡 Analogy

Like a Swiss Army knife vs individual tools — one model handles text, images, and audio natively.

GPT-4o ("omni") is natively multimodal — processes text, images, and audio in one model. Faster and cheaper than GPT-4 Turbo for equivalent tasks.

Console Output

> model: "gpt-4o"
> Context: 128k tokens
> max_tokens: 200 (output cap)
> Response mode: message content

●gpt4o.py

GPT-4o ModelL6–9

1from openai import OpenAI

2import base64

4client = OpenAI()

6# Text: multimodal by default, text only here

7response = client.chat.completions.create(

8 model="gpt-4o",

9 messages=[

10 {"role": "system", "content": "You are a helpful assistant."},

11 {"role": "user", "content": "Explain attention in transformers in 2 sentences."},

12 ],

13 max_tokens=200,

14 temperature=0.7,

15)

16print(response.choices[0].message.content)

17print(f"Tokens: {response.usage.total_tokens}")

19# Vision: pass image URL or base64

20with open("diagram.png", "rb") as f:

21 image_b64 = base64.b64encode(f.read()).decode()

23vision_response = client.chat.completions.create(

24 model="gpt-4o",

25 messages=[{

26 "role": "user",

27 "content": [

28 {"type": "text", "text": "What does this architecture diagram show?"},

29 {"type": "image_url", "image_url": {

30 "url": f"data:image/png;base64,{image_b64}",

31 "detail": "high", # high = 4096 tokens for detail

32 }},

33 ],

34 }],

35)

36print(vision_response.choices[0].message.content)

36 lines

Steps · 4

What's happening

GPT-4o Model

gpt-4o: OpenAI's most capable natively multimodal model (text + vision + audio)

💡 Analogy

Like a Swiss Army knife vs individual tools — one model handles text, images, and audio natively.

GPT-4o ("omni") is natively multimodal — processes text, images, and audio in one model. Faster and cheaper than GPT-4 Turbo for equivalent tasks.

Console Output

> model: "gpt-4o"
> Context: 128k tokens
> max_tokens: 200 (output cap)
> Response mode: message content