Grok 4
No estimate
No hardware requirements for this model
The weights for this model have not been published, so it cannot be downloaded or run on your own hardware at any size. It is reachable only through its provider, and no graphics card changes that.
On record
Full specification
Everything on record for this model. Most of it describes how it was trained rather than how it runs — useful context for judging how much work went into it, and how it compares with models built at a different scale.
Origin
Who built this model, where, and when it was published.
- Organisation
- xAI
- Organisation type
- Industry
- Country
- United States of America
- Published
- 9 July 2025
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language, Multimodal, Vision
- Task
- Language modeling/generation, Question answering, Search, Visual question answering, Character recognition (OCR), Image captioning, Quantitative reasoning
Size
How large the model is and how much data it was trained on. Parameters are the figure that decides whether it fits on a given graphics card.
- Parameters
- 3T
- Training data
- tokens
Rumored to be 2.4T params (https://x.com/kalomaze/status/1942996555088134592)
Training compute
The arithmetic performed to train the model, measured in floating-point operations. It is a measure of what the training run cost, not of how fast the finished model answers you.
- Training compute
- 5 × 10²⁶ FLOP
- How it was established
- Comparison with other models
We think that RL relative to pre-compute is between our estimate for o3 (10% of pre-training) and the 100% implied by this slide in the launch ( https://archive.is/f0vJU ). Assuming the same pre-training as Grok 3 (also implied by that slide, and much more consistent) and that Grok 3 used a tenth as much RL, we get: 2 * (grok3/1.1) in the high case (rl is 10% of grok 3, so grok3/1.1 is grok3 precompute, and in this case twice that is grok 4) 1.1 * (grok3/1.01) in the low case The geometric mean…
The training run
What it physically took to train: which chips, how many, for how long, and what that drew from the wall.
- Chips used
- 200,000
- Compute cost
- $387,842,678
- Data centre
- "we utilized Colossus, our 200,000 GPU cluster, to run reinforcement learning training that refines Grok's reasoning abilities at pretraining scale"
Availability
Whether you can obtain the model and run it on your own hardware, which is what decides if any of the graphics-card figures on this page apply.
- Weights
- Closed — provider access only
- Model access
- API access
- Training code
- Unreleased
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Frontier model
- Yes
- Likely above 10²³ FLOP
- Yes
- Why it is tracked
- Training cost
- Record confidence
- Speculative
Sources
Where this record came from and when it was last checked.
- Reference
- Grok 4
- Last updated
- 11 February 2026
What the numbers mean
Where it came from
Grok 4 was published by xAI, in United States of America, in July 2025. industry is the category the publisher falls under.
It works in Language, Multimodal, Vision, and is recorded as doing language modeling/generation, Question answering, Search, Visual question answering, Character recognition (OCR), Image captioning, Quantitative reasoning.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
How it was trained
Training it took roughly 5 × 10²⁶ FLOP of computation — a measure of what producing the model cost, not of how fast it answers.
The reason it appears in this catalogue at all is training cost.
Answers
Grok 4 — common questions
What GPU do I need to run Grok 4?
None. Grok 4 is a closed model — its weights were never published, so it cannot be downloaded or run on your own hardware at any price. It is reachable only through its provider.
Is Grok 4 open source?
No. Grok 4 has not had its weights published, so it exists only as a service controlled by its owner.
How many parameters does Grok 4 have?
Grok 4 has 3T parameters. Rumored to be 2.4T params (https://x.com/kalomaze/status/1942996555088134592). That figure is the total, and it is what decides how much memory the model needs — roughly half a gigabyte per billion at the compression most people use.
Who created Grok 4?
Grok 4 was published by xAI, based in United States of America, categorised as industry.
When was Grok 4 released?
Grok 4 was published in July 2025.
What is Grok 4 used for?
Grok 4 works in Language, Multimodal, Vision, and is recorded as handling language modeling/generation, Question answering, Search, Visual question answering, Character recognition (OCR), Image captioning, Quantitative reasoning. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
How much compute was used to train Grok 4?
Around 5 × 10²⁶ FLOP. That measures what producing the model cost and says nothing about how quickly it answers once trained — inference speed comes from memory bandwidth, not from the training budget.
The other direction
Looking at it from the other side?
This page starts from the model. If you already own a card and want to know everything it will run, start from the hardware instead.