Grok 4.3 vs. GPT-5.5: Evaluating Performance and Efficiency

What the benchmarks show

When comparing the intelligence and technical proficiency of these two models, GPT-5.5 (xhigh) consistently outperforms Grok 4.3 (high) across most standardized metrics. GPT-5.5 holds an Intelligence Index of 60.2 compared to Grok 4.3’s 53.2, and it demonstrates a more significant lead in coding proficiency with a score of 59.1 against Grok’s 41. This trend continues in specialized benchmarks; GPT-5.5 achieves higher scores in GPQA (0.935 vs. 0.901), HLE (0.443 vs. 0.35), SciCode (0.561 vs. 0.473), LCR (0.743 vs. 0.643), and TerminalBench Hard (0.606 vs. 0.379).

However, the performance gap is not universal. Grok 4.3 exhibits a stronger performance in instruction following, scoring 0.813 on IFBench compared to GPT-5.5’s 0.759. Furthermore, Grok 4.3 shows a slight edge in the TAU2 benchmark with a score of 0.977, compared to GPT-5.5’s 0.939. These results suggest that while GPT-5.5 is the more capable model for complex reasoning and software development, Grok 4.3 remains highly competitive in tasks requiring strict adherence to instructions and specific procedural execution.

Speed and cost

The operational profiles of these two models are starkly different, presenting a clear trade-off between performance and resource consumption. Grok 4.3 is optimized for speed, delivering an output rate of 123.966 tokens per second with a time-to-first-token of 6.374 seconds. In contrast, GPT-5.5 is significantly slower, producing 68.227 tokens per second and requiring 47.763 seconds to generate the first token. For real-time applications or interactive interfaces, the responsiveness of Grok 4.3 provides a distinct advantage.

Financial considerations further widen the gap. GPT-5.5 is priced at a blended rate of $11.25 per million tokens, with output costs reaching $30.00 per million. Grok 4.3 is substantially more economical, featuring a blended rate of $1.56 per million tokens and an output cost of $2.50 per million. The cost of utilizing GPT-5.5 is nearly seven times higher than that of Grok 4.3, which will be a decisive factor for teams managing high-volume data processing or large-scale automated workflows.

Which model fits which workflow

Selecting the appropriate model requires aligning these performance metrics with your specific workflow needs. GPT-5.5 is best suited for high-complexity tasks where the cost of error is high and the need for deep reasoning or advanced coding is constant. Its superior scores in coding and logic make it an ideal candidate for backend development, complex data analysis, and research-heavy applications where the latency penalty is acceptable in exchange for higher accuracy.

Grok 4.3 is better positioned for high-throughput environments where latency and budget are primary constraints. Its ability to follow instructions effectively, combined with its rapid response time and low cost, makes it a strong candidate for customer-facing chatbots, automated content generation, and high-frequency API interactions. While it may not match GPT-5.5 in raw intelligence, its efficiency allows for broader deployment across a larger volume of tasks without incurring prohibitive costs.