Grok 4.6

Name: Grok 4.6
Author: xAI

by xAIGrok

APIAvailable through a hosted API — pay per token, no self-hosting required

Released August 2026500K context≈ 375,000 words1500000000000 params

Grok 4.6 is xAI's latest frontier model, released August 7, 2026. Rather than scaling up in parameters, it reuses the same 1.5-trillion-parameter V9 Mixture-of-Experts foundation as Grok 4.5 and delivers gains through improved supervised fine-tuning and reinforcement learning. It is built for long-running agents and ambitious coding, research, and interactive work — handling complex multi-step assignments from codebase navigation to turning product ideas into working applications. The knowledge cutoff is February 2026 and the context window remains at 500K tokens.

Capabilities

Capability scores are AI-generated based on model documentation, benchmarks, and technical specifications. Learn more

Instruction Following

Exceptional

Coding

Grok 4.6

by xAIGrok

APIAvailable through a hosted API — pay per token, no self-hosting required

Released August 2026500K context≈ 375,000 words1500000000000 params

Grok 4.6 is xAI's latest frontier model, released August 7, 2026. Rather than scaling up in parameters, it reuses the same 1.5-trillion-parameter V9 Mixture-of-Experts foundation as Grok 4.5 and delivers gains through improved supervised fine-tuning and reinforcement learning. It is built for long-running agents and ambitious coding, research, and interactive work — handling complex multi-step assignments from codebase navigation to turning product ideas into working applications. The knowledge cutoff is February 2026 and the context window remains at 500K tokens.

Capabilities

Capability scores are AI-generated based on model documentation, benchmarks, and technical specifications. Learn more

Instruction Following

Exceptional

Coding

Benchmark Scores

Benchmark	Score	Type	Recorded
LCR	80.3	accuracy	16d ago
MMLU-Pro	89.4	accuracy	16d ago
Humanity's Last Exam	42.9	accuracy	16d ago
SWE-Bench	95.6	accuracy	16d ago
LiveCodeBench	88.2	accuracy	16d ago
GPQA Diamond	94.9	accuracy	16d ago
SciCode	56.5	accuracy	16d ago

Glossary

Context WindowThe maximum number of tokens a model can process in a single conversation or prompt.Fine-TuningThe process of further training a pre-trained model on new data to adapt it for specific tasks or domains.Frontier ModelA state-of-the-art AI model representing the cutting edge of what's currently possible in terms of capability and performance.Knowledge CutoffThe date up to which a model has been trained on data; it cannot reliably answer questions about events or information after this date.ParametersThe learned numerical values in a model — more parameters generally means more capacity but higher compute cost.Reinforcement LearningA training method where a model learns by receiving rewards or penalties for its outputs, encouraging it to improve its behavior over time.Supervised Fine-tuningTraining a model on labeled examples to adapt it for a specific task or domain.Supervised Fine-tuningAdapting a pre-trained model using labeled examples where the correct outputs are known.TokensThe basic units of text that a language model processes, typically representing words or word fragments.

Capabilities

Capabilities

Benchmark Scores

Use Case Fit

Glossary