GPT-5.5 Pro vs Grok 4.3
GPT-5.5 Pro (2026) and Grok 4.3 (2026) are frontier-tier reasoning models from OpenAI and xAI. GPT-5.5 Pro ships a 1.1M-token context window, while Grok 4.3 ships a 1M-token context window. On pricing, Grok 4.3 costs $1.25/1M 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.
Grok 4.3 is ~2300% cheaper at $1.25/1M; pay for GPT-5.5 Pro only for coding workflow support.
Decision scorecard
Local evidence first| Signal | GPT-5.5 Pro | Grok 4.3 |
|---|---|---|
| Decision fit | Coding, RAG, and Agents | RAG, Agents, and Long context |
| Context window | 1.1M | 1M |
| Cheapest output | $180/1M tokens | $2.5/1M tokens |
| Provider routes | 2 tracked | 2 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- GPT-5.5 Pro has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GPT-5.5 Pro uniquely exposes Code execution in local model data.
- Local decision data tags GPT-5.5 Pro for Coding, RAG, and Agents.
- Grok 4.3 has the lower cheapest tracked output price at $2.5/1M tokens.
- Local decision data tags Grok 4.3 for RAG, Agents, and Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
GPT-5.5 Pro
$69,000
Cheapest tracked route: OpenAI API
Grok 4.3
$1,625
Cheapest tracked route: xAI Console
Estimated monthly gap: $67,375. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Grok 4.3 is $178/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Code execution before moving production traffic.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- GPT-5.5 Pro is $178/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- GPT-5.5 Pro adds Code execution in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-04-23 | 2026-05-05 |
| Context window | 1.1M | 1M |
| Parameters | — | ~0.5T |
| Architecture | decoder only | - |
| License | Proprietary | Proprietary |
| Knowledge cutoff | 2025-12 | - |
Pricing and availability
| Pricing attribute | GPT-5.5 Pro | Grok 4.3 |
|---|---|---|
| Input price | $30/1M tokens | $1.25/1M tokens |
| Output price | $180/1M tokens | $2.5/1M tokens |
| Providers |
Capabilities
| Capability | GPT-5.5 Pro | Grok 4.3 |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | Yes | Yes |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | Yes |
| Code execution | Yes | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on code execution: GPT-5.5 Pro. Both models share vision, multimodal input, reasoning mode, and function calling, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, GPT-5.5 Pro lists $30/1M input and $180/1M output tokens, while Grok 4.3 lists $1.25/1M input and $2.5/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Grok 4.3 lower by about $73.38 per million blended tokens. Availability is 2 providers versus 2, so concentration risk also matters.
Choose GPT-5.5 Pro when coding workflow support and larger context windows are central to the workload. Choose Grok 4.3 when vision-heavy evaluation and lower input-token cost are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.
FAQ
Which has a larger context window, GPT-5.5 Pro or Grok 4.3?
GPT-5.5 Pro supports 1.1M tokens, while Grok 4.3 supports 1M tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, GPT-5.5 Pro or Grok 4.3?
Grok 4.3 is cheaper on tracked token pricing. GPT-5.5 Pro costs $30/1M input and $180/1M output tokens. Grok 4.3 costs $1.25/1M input and $2.5/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GPT-5.5 Pro or Grok 4.3 open source?
GPT-5.5 Pro is listed under Proprietary. Grok 4.3 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 Pro or Grok 4.3?
Both GPT-5.5 Pro and Grok 4.3 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 Pro or Grok 4.3?
Both GPT-5.5 Pro and Grok 4.3 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 Pro and Grok 4.3?
GPT-5.5 Pro is available on OpenAI API and OpenRouter. Grok 4.3 is available on xAI Console and OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-14. Data sourced from public model cards and provider documentation.