Comparison Intermediate · 4 min read

Reasoning models context window comparison

Q: Reasoning models context window comparison

Reasoning models like claude-sonnet-4-5 and gpt-4o offer context windows ranging from 100k to 128k tokens, enabling complex multi-step reasoning over long documents. Specialized models such as deepseek-reasoner typically have smaller windows (~32k tokens) but optimize for logical inference within that scope.

Quick answer

Reasoning models like claude-sonnet-4-5 and gpt-4o offer context windows ranging from 100k to 128k tokens, enabling complex multi-step reasoning over long documents. Specialized models such as deepseek-reasoner typically have smaller windows (~32k tokens) but optimize for logical inference within that scope.

VERDICT

Use claude-sonnet-4-5 for the largest context window in reasoning tasks requiring extensive document understanding; use gpt-4o for balanced reasoning with strong API support.

Model	Context window	Speed	Cost/1M tokens	Best for	Free tier
claude-sonnet-4-5	100k tokens	Moderate	Medium	Long-form reasoning, multi-document analysis	No
gpt-4o	128k tokens	Fast	Medium-high	General reasoning, coding, multi-modal tasks	No
deepseek-reasoner	32k tokens	Moderate	Low	Focused logical reasoning, math-heavy tasks	No
claude-3-5-sonnet-20241022	90k tokens	Moderate	Medium	Conversational reasoning, summarization	No

Key differences

The primary differences between reasoning models lie in their context window sizes, which determine how much text they can process at once. gpt-4o leads with a 128k token window, ideal for very long documents. claude-sonnet-4-5 offers a slightly smaller but still very large 100k token window, optimized for complex reasoning. deepseek-reasoner has a smaller 32k token window but is fine-tuned for logical and mathematical reasoning, trading window size for specialized accuracy.

Side-by-side example

Here is a prompt example for claude-sonnet-4-5 to perform multi-document reasoning within a 100k token context window.

python

import anthropic
import os

client = anthropic.Anthropic(api_key=os.environ["ANTHROPIC_API_KEY"])

prompt = """
You are a reasoning assistant. Given the following documents, answer the question with detailed reasoning.

Document 1: [Very long text up to 50k tokens...]
Document 2: [Another long text up to 50k tokens...]

Question: Summarize the key insights connecting both documents.
"""

response = client.messages.create(
    model="claude-sonnet-4-5",
    max_tokens=1024,
    system="You are a helpful assistant.",
    messages=[{"role": "user", "content": prompt}]
)

print(response.content)

output

Summary connecting insights from both documents with detailed reasoning...

Equivalent approach with gpt-4o

Using gpt-4o with a 128k token window allows even longer context inputs, suitable for multi-modal or code reasoning tasks.

python

from openai import OpenAI
import os

client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])

messages = [
    {"role": "user", "content": """
You are a reasoning assistant. Analyze these documents and answer the question.

Document 1: [Up to 60k tokens...]
Document 2: [Up to 60k tokens...]

Question: Provide a detailed synthesis.
"""}
]

response = client.chat.completions.create(
    model="gpt-4o",
    messages=messages,
    max_tokens=1024
)

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

output

Detailed synthesis connecting both documents with reasoning...

When to use each

Use claude-sonnet-4-5 when your reasoning requires processing very large text corpora or multi-document contexts up to 100k tokens. Choose gpt-4o for the largest context window (128k tokens) and faster response times, especially if you need multi-modal or coding capabilities. Opt for deepseek-reasoner when your task demands focused logical or mathematical reasoning within a smaller 32k token window.

Model	Best use case	Context window	Strength
claude-sonnet-4-5	Long multi-document reasoning	100k tokens	Complex reasoning over large text
gpt-4o	General reasoning & multi-modal	128k tokens	Fast, versatile, largest window
deepseek-reasoner	Focused logical/mathematical tasks	32k tokens	Specialized reasoning accuracy
claude-3-5-sonnet-20241022	Conversational reasoning	90k tokens	Balanced summarization & reasoning

Pricing and access

All these reasoning models require paid API access with no free tier. Pricing varies by provider and usage volume.

Option	Free	Paid	API access
claude-sonnet-4-5	No	Yes	Anthropic API
gpt-4o	No	Yes	OpenAI API
deepseek-reasoner	No	Yes	DeepSeek API
claude-3-5-sonnet-20241022	No	Yes	Anthropic API

✅

Key Takeaways

Choose reasoning models with context windows matching your input size needs to avoid truncation.
gpt-4o offers the largest 128k token window, ideal for very long or multi-modal inputs.
claude-sonnet-4-5 balances large context with strong reasoning for multi-document tasks.
deepseek-reasoner excels at focused logical reasoning within smaller contexts.
All top reasoning models require paid API access; plan accordingly for cost and latency.

Verified 2026-04 · claude-sonnet-4-5, gpt-4o, deepseek-reasoner, claude-3-5-sonnet-20241022

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