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GPT-5.5 vs GPT-5.5 Pro

GPT-5.5 (2026) and GPT-5.5 Pro (2026) are frontier-tier reasoning models from OpenAI. GPT-5.5 ships a 1.1M-token context window, while GPT-5.5 Pro ships a 1.1M-token context window. On SWE-bench Verified, GPT-5.5 leads by a hair. On pricing, GPT-5.5 costs $5/1M input tokens versus $30/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.

GPT-5.5 is ~500% cheaper at $5/1M; pay for GPT-5.5 Pro only for coding workflow support.

Decision scorecard

Local evidence first
SignalGPT-5.5GPT-5.5 Pro
Decision fitCoding, RAG, and AgentsCoding, RAG, and Agents
Context window1.1M1.1M
Cheapest output$30/1M tokens$180/1M tokens
Provider routes2 tracked2 tracked
Shared benchmarksSWE-bench Verified leader3 rows

Decision tradeoffs

Choose GPT-5.5 when...
  • GPT-5.5 leads the largest shared benchmark signal on SWE-bench Verified by 0 points.
  • GPT-5.5 has the lower cheapest tracked output price at $30/1M tokens.
  • Local decision data tags GPT-5.5 for Coding, RAG, and Agents.
Choose GPT-5.5 Pro when...
  • Local decision data tags GPT-5.5 Pro for Coding, RAG, and Agents.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output prices on this page.

Lower estimate GPT-5.5

GPT-5.5

$11,500

Cheapest tracked route: OpenAI API

GPT-5.5 Pro

$69,000

Cheapest tracked route: OpenAI API

Estimated monthly gap: $57,500. Batch, cache, and negotiated pricing are excluded from this local estimate.

Switch friction

GPT-5.5 -> GPT-5.5 Pro
  • Provider overlap exists on OpenAI API and OpenRouter; start route-level A/B tests there.
  • GPT-5.5 Pro is $150/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
GPT-5.5 Pro -> GPT-5.5
  • Provider overlap exists on OpenAI API and OpenRouter; start route-level A/B tests there.
  • GPT-5.5 is $150/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.

Specs

Specification
Released2026-04-232026-04-23
Context window1.1M1.1M
Parameters
Architecturedecoder onlydecoder only
LicenseProprietaryProprietary
Knowledge cutoff2025-122025-12

Pricing and availability

Pricing attributeGPT-5.5GPT-5.5 Pro
Input price$5/1M tokens$30/1M tokens
Output price$30/1M tokens$180/1M tokens
Providers

Capabilities

CapabilityGPT-5.5GPT-5.5 Pro
VisionYesYes
MultimodalYesYes
ReasoningYesYes
Function callingYesYes
Tool useYesYes
Structured outputsYesYes
Code executionYesYes

Benchmarks

BenchmarkGPT-5.5GPT-5.5 Pro
SWE-bench Verified88.788.7
Google-Proof Q&A93.693.6
SWE-bench Pro58.658.6

Deep dive

On shared benchmark coverage, SWE-bench Verified has GPT-5.5 at 88.7 and GPT-5.5 Pro at 88.7, with GPT-5.5 ahead by 0 points; Google-Proof Q&A has GPT-5.5 at 93.6 and GPT-5.5 Pro at 93.6, with GPT-5.5 ahead by 0 points; SWE-bench Pro has GPT-5.5 at 58.6 and GPT-5.5 Pro at 58.6, with GPT-5.5 ahead by 0 points. The largest visible gap is 0 points on SWE-bench Verified, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.

The capability footprint is close: both models cover vision, multimodal input, reasoning mode, function calling, and tool use. That makes context budget, benchmark fit, and provider maturity more important than a simple checklist. If your application depends on one integration detail, verify it against the provider route you plan to use, not just the base model listing.

For cost, GPT-5.5 lists $5/1M input and $30/1M output tokens, while GPT-5.5 Pro lists $30/1M input and $180/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts GPT-5.5 lower by about $62.50 per million blended tokens. Availability is 2 providers versus 2, so concentration risk also matters.

Choose GPT-5.5 when coding workflow support and lower input-token cost are central to the workload. Choose GPT-5.5 Pro when coding workflow support are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.

FAQ

Which has a larger context window, GPT-5.5 or GPT-5.5 Pro?

GPT-5.5 supports 1.1M tokens, while GPT-5.5 Pro supports 1.1M tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Which is cheaper, GPT-5.5 or GPT-5.5 Pro?

GPT-5.5 is cheaper on tracked token pricing. GPT-5.5 costs $5/1M input and $30/1M output tokens. GPT-5.5 Pro costs $30/1M input and $180/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is GPT-5.5 or GPT-5.5 Pro open source?

GPT-5.5 is listed under Proprietary. GPT-5.5 Pro is listed under Proprietary. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.

Which is better for vision, GPT-5.5 or GPT-5.5 Pro?

Both GPT-5.5 and GPT-5.5 Pro expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Which is better for multimodal input, GPT-5.5 or GPT-5.5 Pro?

Both GPT-5.5 and GPT-5.5 Pro expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Where can I run GPT-5.5 and GPT-5.5 Pro?

GPT-5.5 is available on OpenAI API and OpenRouter. GPT-5.5 Pro is available on OpenAI API and OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Continue comparing

Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.