Grok 4.7’s 500K Token Context: What Actually Fits
Grok 4.7 offers 500,000 tokens of context - half what some models advertise. We tested what really fits and when that difference matters.
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Grok 4.7 has a 500,000 token context window - half what models advertising a million offer. We tested what actually fits in those 500,000 tokens and when that difference matters versus when it’s just a number on a slide.
Verdict in One Paragraph
500,000 tokens equals about 1,000 pages of text at once. In practice, this means you can fit an entire medium-sized project’s documentation, a full year of contracts, or a book with room to spare. The difference between 500K and 1M matters in two cases: analyzing very large codebases and working with hundreds of documents at once. Beyond those, it’s a parameter you’ll never touch - and paying more for it makes no sense.
What Fits in 500,000 Tokens
Let’s use a conversion rate that works for English text: one page of typed text is roughly 500 tokens. This is a practical approximation that holds across most standard documents.
| Material | Token Count | What Fits |
|---|---|---|
| 30-page contract | ~15k | 33 such contracts at once |
| 300-page book | ~150k | three books at once |
| Project documentation | ~50-200k | fits with room to spare |
| Year of invoices with descriptions | ~80k | six years at once |
| Codebase, 50k lines | ~600k | DOES NOT fit |
| 20 hours of transcripts | ~900k | DOES NOT fit |
Two Cases Where 500K Isn’t Enough
1. Large Codebase in Its Entirety
A project with fifty thousand lines of code is about 600,000 tokens - it won’t fit. But this is an opinion backed by practice: dumping an entire codebase into context is rarely a good idea anyway. The model gets lost in the noise and answers become generic. Pointing to specific files works better.
2. Hundreds of Documents at Once
When analyzing twenty hours of transcripts or several hundred documents, 500,000 won’t be enough. Here the difference from a million is real.
But there’s a workaround and it’s usually better: you split the material into batches, process each separately, and combine the results. You also pay less, because you’re not running the entire material through with every question.
The Trap Nobody Talks About
The declared context window isn’t the same as the window where the model performs well. These are two different numbers and manufacturers only publish the first one.
In practice, answer quality drops the closer you get to the limit. Information from the middle of very long material is retrieved worse than from the beginning and end - a phenomenon known as lost-in-the-middle. A model with a million-token window that starts losing facts at 700,000 is worse than a model with a 500,000 window that maintains quality to the end.
Grok 4.7’s maker actually declares better long-context management as one of the improvements over its predecessor - suggesting they worked on quality within the window, not on its size.
How to Test This Yourself in Ten Minutes
- Take material you actually work with - your own documentation, not someone else’s test.
- Hide five specific facts in different places: at the beginning, one quarter in, halfway, three quarters in, and at the end.
- Ask the model about each one separately, in separate conversations.
- Count hits by position. If the middle performs worse, you know your real limit.
This test takes fifteen minutes and tells you more about your use case than any benchmark. I ran it on another occasion and the result surprised me - but that’s another story.
What a Full Context Window Costs
Important for budget planning: context means input tokens and you pay for them with every message. And there’s a threshold that changes the rate.
Above 200,000 tokens in a query, pricing switches to the long-context rate - $4 per million input tokens instead of $2. Key point: once you cross the threshold, the higher rate covers all query tokens, not just the excess over the threshold.
| Window Usage | Rate | Cost per Query |
|---|---|---|
| 50k tokens | short context | $0.10 |
| 199k tokens | short context | $0.40 |
| 201k tokens | long context | $0.80 |
| 500k tokens, full window | long context | $2.00 |
The two middle rows differ by two thousand tokens - about four pages - and by one hundred percent in price. Ten queries to a full window costs about $20. In a longer conversation with large material, the bill grows faster than most people expect - because conversation history is appended each time, and after crossing the threshold every subsequent message bills the entire context at double rate. I break down this mechanism along with ways to work around it in a separate article about the 200,000 token threshold.
Three Rules for Working with Large Context
- Include what you need, not everything. Smaller context means better answers and lower bills simultaneously.
- New thread for new topic. Long conversations carry the entire history with every message.
- Important things at the beginning and end of material. The middle is retrieved worst in all models.
Frequently Asked Questions
What is Grok 4.7’s context window?
500,000 tokens, according to official documentation. The same as Grok 4.6 and 4.5.
How many pages is that?
About 1,000 pages of typed text. The exact number varies by language and formatting.
Is 500K small compared to models with a million?
For most use cases it doesn’t matter, because you never hit those limits. The difference is real for very large codebases and hundreds of documents at once.
Does the model use the entire window equally well?
No model does. Information from the middle of very long material is retrieved worse than from the beginning and end. Test it yourself - I described the test above.
What does filling the entire window cost?
About $2.00 per query at the full 500,000 input tokens - at the long-context rate of $4 per million.
At what token count does Grok charge more?
From 200,000 tokens in a query. Once you cross the threshold, the higher rate covers all query tokens, not just the excess.
Sources and Verification Date
- Context window size and prices read September 21
- 2026 from official documentation at docs.x.ai/docs/models and docs.x.ai/docs/pricing. Update from the same day: the first version of the cost table calculated the full window at short-context rates. Detailed pricing shows the long-context threshold at 200,000 tokens
- so amounts in the table were corrected - the full window costs $2.00
- not $1.00. Page-to-token conversions are approximate and depend on language and formatting - treat them as order of magnitude
- not precise measurement. The description of lost-in-the-middle comes from our work with long materials
- not from manufacturer materials
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