BenchLeader

GPT-5.4 Pro vs Grok 4

Verdict
  • GPT-5.4 Pro leads on quality: 64.3 vs 59.8.
  • GPT-5.4 Pro is stronger in knowledge, multimodal, reasoning.
  • Grok 4 is stronger in instruction following, agents & tools, coding, human preference, long context, maths.
  • Grok 4 is 43× cheaper ($1.56 vs $67.50 per 1M blended).
MetricGPT-5.4 ProGrok 4
BenchLeader Index64.359.8
Instruction following score67.367.7
Knowledge score73.656.0
Multimodal score69.854.5
Reasoning score75.358.3
Agents & tools score53.4
Coding score61.2
Human preference score59.8
Long context score77.7
Maths score58.0
Blended price $/M$67.50$1.56
Output speed1 tok/s
Time to first answer6.3 s
Context window1.1M256k
GPQA Diamond87.0%
OTIS Mock AIME84.0%
Humanity's Last Exam44.3%
Terminal-Bench27.2%
SimpleBench74.1%60.5%
Fiction.LiveBench 120k96.9%
Cybench43.0%
WeirdML45.7%
APEX-Agents15.2%
Epoch Capabilities Index158.9146.4
LMArena Text1411
LMArena Hard Prompts1420
LMArena Coding1435
LMArena Vision1210
AIME (Vals)90.6%
LiveCodeBench83.3%
MMLU-Pro85.3%
LegalBench83.2%
CorpFin66.0%
TaxEval65.1%
MedQA92.5%
MGSM90.9%
SWE-bench (Vals)57.8%
GPQA Diamond (Vals)88.1%
IMO 202521.4%
MathArena Apex2.1%
MultiChallenge69.2%
VISTA53.9%
MultiNRC62.3%
TutorBench56.6%
Kagi LLM Benchmark73.6%
IFEval (HELM)94.9%
Omni-MATH (HELM)60.3%
WildBench (HELM)79.7%
MMLU-Pro (HELM)85.1%
GPQA Diamond (HELM)72.6%
HELM Capabilities mean78.5%
Aider Polyglot79.6%
ARC-AGI-179.6%
ARC-AGI-229.4%
BFCL Overall63.0%

Data as of 2026-09-13. Best configuration of each model; every score links to its source on the model pages.

GPT-5.4 Pro vs Grok 4: questions

Is GPT-5.4 Pro better than Grok 4?
GPT-5.4 Pro leads on quality: 64.3 vs 59.8. The BenchLeader Index combines every independent quality benchmark; GPT-5.4 Pro is ahead overall as of 2026-09-13, but check the category scores for your use.
Which is cheaper, GPT-5.4 Pro or Grok 4?
Grok 4 is cheaper: $1.56 against $67.50 per million tokens, blended at three input tokens per output token.
Which has the larger context window?
GPT-5.4 Pro accepts more context: 1.1M against 256k tokens.