GPT-5.5 vs GPT-5.4: What Changed and Is It Worth Upgrading?

How does GPT-5.5 compare to GPT-5.4? See the full benchmark breakdown, pricing differences, and whether upgrading is worth it for developers and businesses.

by Framia

GPT-5.5 vs GPT-5.4: What Changed and Is It Worth Upgrading?

Released on April 23, 2026, GPT-5.5 (codename "Spud") is the direct successor to GPT-5.4. OpenAI describes it as their "smartest and most intuitive to use model yet." But how much did things actually improve? Here's the complete GPT-5.5 vs GPT-5.4 comparison across every dimension that matters.

The Core Differences at a Glance

Dimension GPT-5.4 GPT-5.5
Release Date Before April 2026 April 23, 2026
Context Window (API) Large 1,000,000 tokens
Context Window (Codex) 400,000 tokens
Inference Speed Baseline Matches GPT-5.4 latency
Token Efficiency Baseline Fewer tokens for same tasks
API Input Price $5 / 1M tokens
API Output Price $30 / 1M tokens
Agentic Coding Strong Stronger
Computer Use Good Significantly better
Scientific Research Capable Major improvement

Benchmark Comparison: GPT-5.5 vs GPT-5.4

OpenAI ran head-to-head benchmarks. Here are the key results:

Coding

Benchmark GPT-5.5 GPT-5.4 Δ Improvement
Terminal-Bench 2.0 82.7% 75.1% +7.6 pts
Expert-SWE (Internal) 73.1% 68.5% +4.6 pts
SWE-Bench Pro 58.6% 57.7% +0.9 pts

Knowledge Work

Benchmark GPT-5.5 GPT-5.4
GDPval (wins/ties) 84.9% 83.0%
OSWorld-Verified 78.7% 75.0%
Tau2-bench Telecom 98.0% 92.8%
OfficeQA Pro 54.1% 53.2%
Investment Banking (Internal) 88.5% 87.3%

Scientific Research

Benchmark GPT-5.5 GPT-5.4
GeneBench 25.0% 19.0%
BixBench 80.5% 74.0%
FrontierMath Tier 1–3 51.7% 47.6%
FrontierMath Tier 4 35.4% 27.1%

Long Context

Benchmark GPT-5.5 GPT-5.4
MRCR 128K–256K 87.5% 79.3%
MRCR 256K–512K 81.5% 57.5%
MRCR 512K–1M 74.0% 36.6%

The long-context improvements are dramatic — GPT-5.5 scores 74.0% on the 512K–1M range where GPT-5.4 scored only 36.6%.

Abstract Reasoning

Benchmark GPT-5.5 GPT-5.4
ARC-AGI-2 85.0% 73.3%
ARC-AGI-1 95.0% 93.7%

The ARC-AGI-2 improvement (+11.7 points) is one of the most striking results of the release.

What Stayed the Same: Inference Speed

One of GPT-5.5's engineering achievements is matching GPT-5.4's per-token latency despite being a significantly more capable model. Serving GPT-5.5 required co-designing the model for NVIDIA GB200/GB300 NVL72 systems and rethinking inference as an integrated system.

One optimization alone — improved load balancing and partitioning heuristics developed with Codex assistance — increased token generation speeds by over 20%.

Token Efficiency: GPT-5.5 Uses Fewer Tokens

Even though GPT-5.5's output pricing is higher than GPT-5.4, it is more token-efficient: it completes the same tasks with fewer tokens and fewer retries. OpenAI specifically tuned the Codex experience so GPT-5.5 delivers better results with fewer tokens for most workflows.

Practical result: For Codex-heavy teams, GPT-5.5's higher per-token cost may be offset by lower total token consumption.

What GPT-5.5 Does Noticeably Better

1. Long-context reasoning. GPT-5.5 handles 512K–1M token contexts far better than GPT-5.4. This is the biggest practical improvement for large codebase analysis, long legal documents, and multi-document research.

2. Abstract reasoning. The ARC-AGI-2 jump (+11.7 points) reflects genuine improvements in novel problem-solving — not just benchmark optimization.

3. Scientific tasks. GeneBench improved by +6 points (from 19% to 25%). BixBench improved from 74% to 80.5%. GPT-5.5 is now described as a "bona fide co-scientist."

4. Autonomy in agentic tasks. Early testers described GPT-5.5 as "noticeably smarter and more persistent than GPT-5.4, staying on task for significantly longer without stopping early." (Michael Truell, Cursor CEO)

Should You Upgrade from GPT-5.4 to GPT-5.5?

API developers: Yes. Switch gpt-5.4gpt-5.5 in your model string. The long-context improvements alone justify it for most production workloads.

ChatGPT users: You already have access — GPT-5.5 is now the default model on Plus/Pro/Business/Enterprise plans.

Enterprise teams with Codex workflows: Yes — especially if your workflows involve large codebases, long documents, or research synthesis.

Cost-sensitive use cases: Run cost benchmarks on your specific workload. GPT-5.5 is more token-efficient, so the higher per-token price may not translate to higher total bills.

Using GPT-5.5 Through a Platform

If you want GPT-5.5's capabilities without managing API versions manually, Framia.pro provides AI workflows built on the latest OpenAI models. Framia.pro always runs on the current flagship model, so teams get GPT-5.5 performance for content, research, and automation tasks without configuration overhead.

Bottom Line

GPT-5.5 is a meaningful upgrade over GPT-5.4 — especially in long-context handling, abstract reasoning, and scientific research. It delivers these improvements at the same inference speed, with better token efficiency. For most production use cases, upgrading from GPT-5.4 to GPT-5.5 is a low-risk, high-reward decision.