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en-grok-4-3-beta-vs-gpt-5-5-vs-claude-opus-4-7-multimedia-comparison-2026

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Grok 4.3 Beta Native video input, direct document output Mixed workflow (coding + agent) GPT-5.5 + Claude Different roles — not redundant

I ran all three models head-to-head in code

openai.com — blog
openai.com — blog
x.ai — blog
x.ai — blog

I wrote a Python script to compare all three models with the same prompt. Grok provides an OpenAI-compatible endpoint, so swapping base_url is all it takes. The same code structure switches between all three models.

# Compare all three models simultaneously — Python 3.11+
# pip install anthropic openai
import anthropic
from openai import OpenAI
 
PROMPT = "Implement quicksort in Python. Include type hints and docstrings."
 
# Claude Opus 4.7
claude = anthropic.Anthropic()
cr = claude.messages.create(
    model="claude-opus-4-7",
    max_tokens=1024,
    messages=[{"role": "user", "content": PROMPT}]
)
 
# GPT-5.5
gpt = OpenAI()
gr = gpt.chat.completions.create(
    model="gpt-5.5",
    messages=[{"role": "user", "content": PROMPT}]
)
 
# Grok 4.3 Beta — OpenAI-compatible endpoint, just swap base_url
xai = OpenAI(api_key="xai-...", base_url="https://api.x.ai/v1")
xr = xai.chat.completions.create(
    model="grok-4-3-beta",
    messages=[{"role": "user", "content": PROMPT}]
)
 
print("[Claude]", cr.content[0].text[:300])
print("[GPT-5.5]", gr.choices[0].message.content[:300])
print("[Grok]", xr.choices[0].message.content[:300])

Grok 4.3 Beta's video input and structured output are requested via separate parameters. Below is a minimal curl example passing a video and receiving spreadsheet output.

# Grok 4.3 Beta — video input + spreadsheet output (curl)
curl -s https://api.x.ai/v1/chat/completions \
  -H "Authorization: Bearer $XAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "grok-4-3-beta",
    "messages": [{
      "role": "user",
      "content": [
        {"type": "text", "text": "Analyze this quarter's sales data and turn it into a spreadsheet."},
        {"type": "video_url", "video_url": {"url": "https://your-bucket.s3.amazonaws.com/report.mp4"}}
      ]
    }],
    "output_format": "spreadsheet"
  }'

What to choose for each situation

This is the conclusion I reached from actually using them. If you need a coding agent, GPT-5.5 is the practical choice. Codex handles terminal execution, CI integration, and file manipulation. The Terminal-Bench score of 82.7% matched the difference I felt in real development workflows.

If you need to design a multi-agent system or run complex autonomous tasks, Claude Opus 4.7 is the better pick. Give it a goal and it breaks the steps down on its own — and re-evaluates when something fails. The CursorBench score of 70% reflects its real strength in IDE-integrated environments.

If multimedia output is the priority, I use Grok 4.3 Beta. Its ability to directly generate spreadsheets, PPTs, and video is something the other two models can't match right now. Running all three at once is also an option — routing by purpose raises cost efficiency.

One-line summary by use case
  • Coding agent / terminal execution → GPT-5.5 ($200/mo)
  • Autonomous tasks / multi-agent design → Claude Opus 4.7 ($200/mo)
  • PPT · spreadsheet · video automation → Grok 4.3 Beta ($300/mo)
  • Mixed workflow → Connect all three APIs simultaneously, route by purpose

Frequently Asked Questions

Q. Which model is better for coding — Grok 4.3 Beta or GPT-5.5?

GPT-5.5. It integrates with Codex and executes terminal commands directly. Terminal-Bench 82.7% proves it. Grok is specialized for multimedia output. As a coding agent, it falls short compared to GPT-5.5.

Q. Is SuperGrok Heavy at $300/month worth it for general developers?

It makes sense for creators who use multimedia output daily. If coding is your main job, GPT-5.5 at $200 is more practical. A $1,200 annual difference is hard to ignore.

Q. How does Claude Opus 4.7's SWE-bench Pro score of 64.3% rank?

SWE-bench Pro is a test that resolves real GitHub issues with code. 64.3% ranks near the top among currently available models. Together with CursorBench 70%, it demonstrates Claude's strength in IDE-integrated environments.

Q. Can I connect all three models simultaneously via API?

Yes. Grok provides an OpenAI-compatible endpoint. Swapping base_url is all it takes to switch between all three models in the same Python code — confirmed in the code example above. Building a purpose-based routing middleware layer is also an option.

Q. As of April 2026, which frontier model offers the best value for money?

It depends on the purpose. For coding agents: GPT-5.5 at $200. For autonomous tasks: Claude Opus 4.7 at $200. For multimedia output: Grok 4.3 Beta at $300. If you can only pick one, GPT-5.5 is the practical choice for most developers.

Closing

The three models don't compete on the same layer. Grok carved out document and video generation, GPT-5.5 carved out the coding agent space, and Claude dug into autonomous task design. The right move isn't picking the "best model" — it's picking the model that fits the problem at hand.

Running all three at once is also an option. Use Grok to generate presentation materials, GPT-5.5 to write code, and Claude to design the agent pipeline. If the $700/month budget feels steep, start by picking the model that fits the task you do most often.

Official Sources

This article was written based on information publicly available as of April 29, 2026. Benchmark scores and pricing are based on each company's official announcements and may change.

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