GPT-5.5 vs GPT-5.5 Instant (May 2026)
Head-to-head specifications
| Metric | GPT-5.5 | GPT-5.5 Instant (May 2026) | Difference |
|---|---|---|---|
| Intelligence Index | 55.0 | 34.0 | +61.8% |
| Context window | 1M tokens | 922K tokens | — |
| Blended price ($/1M tokens) | $1.54 | $1.54 | — |
| Access | Proprietary API | Proprietary API | — |
- GPT-5.5 leads overall capability (Intelligence Index 55.0 vs 34.0).
- Both cost about the same to run (~$1.54/1M blended tokens), so capability and speed should decide.
- GPT-5.5 offers the larger context window (1M tokens), useful for long documents and codebases.
Verdict: GPT-5.5 or GPT-5.5 Instant (May 2026)?
GPT-5.5 advantages
- General intelligence (+38%)
- Context window (+8%)
GPT-5.5 Instant (May 2026) advantages
- No decisive advantage on the tracked metrics.
Which should you choose?
- Choose the GPT-5.5 if you need the strongest overall reasoning and accuracy.
- Choose the GPT-5.5 if you work with long documents or large codebases.
Value for money
GPT-5.5 offers more intelligence per dollar (1.6× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.
GPT-5.5 vs GPT-5.5 Instant (May 2026): which should you choose?
GPT-5.5 — OpenAI multimodal model with an Intelligence Index of 55, a 1M-token context window and a blended price of $1.54/1M tokens.
GPT-5.5 Instant (May 2026) — OpenAI multimodal model with an Intelligence Index of 34, a 922K-token context window and a blended price of $1.54/1M tokens.
GPT-5.5 vs GPT-5.5 Instant (May 2026): GPT-5.5 scores higher on the Intelligence Index. GPT-5.5 leads overall capability (Intelligence Index 55.0 vs 34.0). Both cost about the same to run (~$1.54/1M blended tokens), so capability and speed should decide.
Capability: intelligence, coding and agentic work
On the composite Intelligence Index the GPT-5.5 scores 55.0 versus 34.0. Composite indices summarize many evaluations, but always test on your own workload before committing.
Context window and speed
The GPT-5.5 accepts up to 1 million tokens per request, which sets how much documentation, transcript or code it can reason over at once.
Pricing and access
At blended per-token rates, GPT-5.5 is the cheaper model to run ($1.54 vs $1.54 per 1M tokens). GPT-5.5 is proprietary api and GPT-5.5 Instant (May 2026) is proprietary api. Open-weight models can be self-hosted, trading per-call cost for infrastructure you manage; for production also weigh rate limits, throughput and data-residency requirements.
The verdict
Both are credible choices in the ai model comparison space; the specification table above lays out every metric so you can weigh the trade-offs that matter to you. Pick the one whose strengths line up with how you will actually use it.
Frequently asked questions
Is the GPT-5.5 better than the GPT-5.5 Instant (May 2026)?
GPT-5.5 is the clearly stronger overall choice, winning most of the dimensions that matter. GPT-5.5 leads overall capability (Intelligence Index 55.0 vs 34.0).
What is the main difference between the GPT-5.5 and the GPT-5.5 Instant (May 2026)?
GPT-5.5 leads overall capability (Intelligence Index 55.0 vs 34.0). Both cost about the same to run (~$1.54/1M blended tokens), so capability and speed should decide.
Which is better value?
GPT-5.5 offers more intelligence per dollar (1.6× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.
Which should I choose?
Choose the GPT-5.5 if you need the strongest overall reasoning and accuracy. Choose the GPT-5.5 if you work with long documents or large codebases.
Methodology
Large language models are compared on independent leaderboard metrics: an Intelligence Index (a composite of reasoning and knowledge evaluations), Coding and Agentic indices where measured, community arena Elo, maximum context window, a blended API price per million tokens (weighted across cache-hit, input and output rates), and measured output speed in tokens per second. Where a model ships multiple reasoning-effort variants, we report its strongest variant. Benchmarks capture only part of real-world quality, which also depends on tool use, latency, safety and task fit — and this space moves quickly, so figures reflect the leaderboard snapshot on the page date.