Apr 24, 2026
1050K context
128,000 tokens output
OpenAI
vs
OpenAI
GPT 5.5 vs GPT 5.4
Compare GPT 5.5 and GPT 5.4 across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for long-context workloads versus long-context workloads.
Mar 05, 2026
1050K context
128,000 tokens output
Overview Comparison
Structured side-by-side differences for the highest-signal model metadata.
GPT 5.5
GPT 5.4
Provider
The entity that currently provides this model.
GPT 5.5
OpenAI
GPT 5.4
OpenAI
Model ID
The routed model identifier exposed by upstream providers.
GPT 5.5
openai/gpt-5.5
GPT 5.4
openai/gpt-5.4
Input Context Window
The number of tokens supported by the input context window.
GPT 5.5
1050K
tokens
GPT 5.4
1050K
tokens
Maximum Output Tokens
The number of tokens that can be generated by the model in a single request.
GPT 5.5
128,000 tokens
tokens
GPT 5.4
128,000 tokens
tokens
Open Source
Whether the model's code is available for public use.
GPT 5.5
No
GPT 5.4
No
Release Date
When the model was first released.
GPT 5.5
Apr 24, 2026
GPT 5.4
Mar 05, 2026
Knowledge Cut-off Date
When the model's knowledge was last updated.
GPT 5.5
2025-12-01
GPT 5.4
March 2026
API Providers
The providers that currently expose the model through an API.
GPT 5.5
OpenRouter
GPT 5.4
OpenRouter
Modalities
Types of data each model can process or return.
GPT 5.5
Text
Image
File
GPT 5.4
Text
Image
File
Pricing Comparison
Compare current token pricing before you choose the cheaper or more scalable API option.
GPT 5.5
OpenAI
Input price
$5.00
Per 1M tokens
Output price
$30.00
Per 1M tokens
GPT 5.4
OpenAI
Input price
$2.50
Per 1M tokens
Output price
$15.00
Per 1M tokens
Capabilities Comparison
See where each model overlaps, where they differ, and which one supports more of the features you care about.
Capability
GPT 5.5
GPT 5.4
1M Token Context
Supports a context window of up to 1 million tokens, enabling processing of extensive documents, large codebases, and long multi-turn sessions in a single request.
GPT 5.5
—
GPT 5.4
Supported
Agentic Workflows
Executes multi-step tasks autonomously using built-in computer use capabilities, including tool orchestration, file access, and data extraction with minimal human oversight.
GPT 5.5
—
GPT 5.4
Supported
Artifact Generation
Produces structured professional outputs including documents, spreadsheets, slide decks, financial models, and legal analyses in a single session.
GPT 5.5
—
GPT 5.4
Supported
Code Generation
Generates, reviews, and debugs code across common programming languages, with support for developer workflows within the full 1M token context.
GPT 5.5
—
GPT 5.4
Supported
Deep Analytical Reasoning
The Pro variant uses multi-path reasoning evaluation to provide greater analytical depth for research, legal analysis, and complex decision-making tasks.
GPT 5.5
—
GPT 5.4
Supported
Extended Reasoning
The Thinking variant applies enhanced logical follow-through across long, complex interactions, maintaining consistency over extended reasoning chains.
GPT 5.5
—
GPT 5.4
Supported
File
GPT 5.5
Supported
GPT 5.4
Supported
Image
GPT 5.5
Supported
GPT 5.4
Supported
Reasoning
GPT 5.5
Supported
GPT 5.4
Supported
Reduced Hallucinations
Delivers 33% fewer factual errors in individual claims compared to GPT-5.2, according to OpenAI's internal benchmarks.
GPT 5.5
—
GPT 5.4
Supported
Structured Output
GPT 5.5
Supported
GPT 5.4
Supported
Text
GPT 5.5
Supported
GPT 5.4
Supported
Token-Efficient Output
Solves problems using fewer tokens than its predecessor, reducing latency and cost for high-volume production workloads.
GPT 5.5
—
GPT 5.4
Supported
Tools
GPT 5.5
Supported
GPT 5.4
Supported
Benchmark Comparison
Shared benchmark rows make it easier to compare performance where both models have published scores.
| Benchmark | GPT 5.5 | GPT 5.4 |
|---|---|---|
|
ARC-AGI-2
Novel abstract reasoning and pattern recognition
|
||
|
BrowseComp
Complex web browsing and information retrieval
|
||
|
GPQA Diamond
PhD-level science questions (biology, physics, chemistry)
|
||
|
HLE
Questions that challenge frontier models across many domains
|
||
|
OSWorld-Verified
Autonomous computer use and desktop tasks
|
||
|
SciCode
Scientific research coding and numerical methods
|
||
|
SWE-bench Pro
Challenging real-world software engineering tasks
|
||
|
Terminal-Bench 2.0
Agentic coding and terminal command tasks
|
Community discussion
What Reddit discussions say about GPT 5.5 vs GPT 5.4
GPT 5.5 and GPT 5.4 are both surfacing live Reddit discussions, giving this comparison a community layer beyond specs and benchmarks. The most visible threads right now are clustered in r/singularity, r/OpenAI, r/codex.
The feed below mixes discussion threads surfaced for each model so you can quickly spot where community sentiment overlaps or diverges.
Just came across something interesting and wanted to see what people here think
apparently a 23-year-old used ChatGPT 5.4 Pro to solve one of the Erdős problems that had been open for around 60 years. what’s surprising is that it was done in basically one go, and the model took about 1 hour 20 minutes to work through it
from what I understood, the solution used a known formula that just hadn’t been applied to this specific problem before, which is kind of fascinating if true.
not sure how verified this is yet, but the chat is public if anyone wants to take a look:
https://chatgpt.com/share/69dd1c83-b164-8385-bf2e-8533e9baba9c
Problem:
https://www.erdosproblems.com/1176
X post:
https://x.com/i/status/2048421286091604187
For years, the AI/ LLM critics had the same reasoning: LLMs don't reason and they just predict the next token
Recently, it reasoned better than 50 years of mathematicians on an open erdos problems by applying a basic phd level formula
Chat gpt conversation: https://chatgpt.com/share/69dd1c83-b164-8385-bf2e-8533e9baba9c
Here is the problem where TAO also commented on it: https://www.erdosproblems.com/1196
Thoughts?
I thought it was mildly funny, GPT slightly changed its stance after I asked about sources regarding a translation nuance but still pretty much stood its ground. Of course it's a complete delusion, i guess the reward function makes it try to come up with an anwser even if it lacks context.
Always make sure to double check the facts.
People are apparently burning 100M+ tokens a day for like $1 and vibecoding nonstop.
[](https://x.com/adxtyahq/status/2055710603482988998/photo/1)
Which model should you choose?
Use the summary below to decide which model better fits your workflow, budget, and feature requirements.
GPT 5.5
GPT 5.5 is a stronger fit for long-context workloads, reasoning-heavy tasks, tool-augmented workflows.
GPT 5.4
GPT 5.4 is a stronger fit for long-context workloads, reasoning-heavy tasks, tool-augmented workflows.
Verdict
Choose GPT 5.5 if you prioritize long-context workloads, reasoning-heavy tasks, tool-augmented workflows. Choose GPT 5.4 if your workflow depends more on long-context workloads, reasoning-heavy tasks, tool-augmented workflows.
FAQ
Common questions about GPT 5.5 vs GPT 5.4
What is the main difference between GPT 5.5 and GPT 5.4?
GPT 5.5 leans toward long-context workloads, reasoning-heavy tasks, tool-augmented workflows, while GPT 5.4 is better suited to long-context workloads, reasoning-heavy tasks, tool-augmented workflows.
Which model is cheaper: GPT 5.5 or GPT 5.4?
GPT 5.4 starts lower on input pricing at $2.5000 per 1M input tokens, compared with $5.0000 for GPT 5.5.
Which model has the larger context window: GPT 5.5 or GPT 5.4?
GPT 5.5 is listed with a context window of 1050K, while GPT 5.4 is listed with 1050K.
How should I evaluate GPT 5.5 vs GPT 5.4 for my use case?
This comparison currently includes 8 shared benchmark rows, helping you compare practical performance across overlapping evaluations.