Models · /models/grok-3-mini
Grok 3 mini
xAI · Closed weights · mid · registry tag 2026 efficient
textcodevision8 aliases2 official receipts
Build / data stamp
Read this before trusting a headline.
Data snapshot May 1, 2026Registry verification passed9 providers · 826 tracked modelsPage refreshed May 7, 2026
Model pages expose the current registry snapshot and page stamp so stale deployments are visible without reading the code.
Score passport by benchmark
Each row keeps the benchmark receipt, source family, raw metric, and percentile inside its exact comparable group.
Thin verified coverageThis model currently reads as thin verified coverage across the resolved evidence surface.
Text Arena
AR · Chat / text · Human
It tests whether the model is actually useful in normal conversational turns, not just on narrow correctness tasks.
63.6% percentile inside its comparable group
1,363Raw benchmark value
Coding
LB · Coding · Objective
It tells you whether the model can generate, repair, and reason over code under evaluator pressure rather than marketing examples.
71% percentile inside its comparable group
54.2%Raw benchmark value
Coding generation
LB · Coding · Objective
It tells you whether the model can generate, repair, and reason over code under evaluator pressure rather than marketing examples.
87.1% percentile inside its comparable group
74.4%Raw benchmark value
Coding completion
LB · Coding · Objective
It tells you whether the model can generate, repair, and reason over code under evaluator pressure rather than marketing examples.
16.1% percentile inside its comparable group
34%Raw benchmark value
Reasoning
LB · Reasoning / math / science · Objective
It is one of the cleaner reads on deliberate reasoning strength rather than style or popularity.
9.7% percentile inside its comparable group
43.9%Raw benchmark value
Language
LB · Chat / text · Objective
It tests whether the model is actually useful in normal conversational turns, not just on narrow correctness tasks.
22.6% percentile inside its comparable group
37.8%Raw benchmark value
Instruction following
LB · Chat / text · Objective
It tests whether the model is actually useful in normal conversational turns, not just on narrow correctness tasks.
3.2% percentile inside its comparable group
62.4%Raw benchmark value