What is Grok 3
Grok 3 is the latest large language model from xAI, trained using a breakthrough reinforcement learning framework on a cluster of 200,000 GPUs. It features 27 billion parameters and a context window of 1.28 million tokens with real-time knowledge retrieval.
Through Think mode, Grok 3 can engage in deep reasoning processes lasting from 6 seconds to 6 minutes, demonstrating performance beyond human expert level. It achieved 93.3% accuracy in the AIME 2025 competition and 84.6% in graduate-level GPQA.
As a versatile AI assistant, Grok 3 supports 12 programming languages, can process image and video content, and leverages DeepSearch for real-time information verification.
Core Features Highlights
Discover Revolutionary Breakthroughs in Grok 3
Enhanced Reasoning Engine
- Supports 6s to 6min deep reasoning process
- AIME 2025 competition 93.3% accuracy (64 reasoning iterations)
- GPQA diamond-level problems 84.6% accuracy (exceeding human experts)
- Reinforcement learning framework based on 200k GPU cluster
Mathematics & Science
- AIME 2024/2025 biennial average 94.5% accuracy
- MMLU-Pro benchmark 79.9% accuracy (leading in STEM)
- Complex math problem solving average latency 67ms
Code Generation & Optimization
- LiveCodeBench v5: 79.4% accuracy (real-time programming evaluation)
- Supports million-line codebase analysis
- Supports 12 languages including Python/Java/C++
Multimodal Understanding
- MMMU benchmark 73.2% accuracy
- EgoSchema long video understanding 74.5% accuracy
- Image-text mixed problem solving improved by 42%
Real-time Knowledge Engine
- Covers web-wide real-time data + π platform social data
- Complex query average response time <800ms
- Supports cross-verification from 1,200+ trusted sources
Long Context Processing
- 1M tokens context memory (about 750k characters)
- Single-pass analysis of 3000-page technical documents
- LOFT 128k benchmark 83.3% accuracy
Performance Benchmark Comparison
Competition Math
Graduate-Level Google-Proof Q&A (Diamond)
LiveCodeBench (v5)
Code Generation: 10/1/2024 - 2/1/2025
MMMU
Multimodal Understanding