Grok 4.7
xAI · released Sep 21, 2026
Grok 4.7 is SpaceXAI's flagship model for coding, agentic tasks, and knowledge work, succeeding Grok 4.6. It is particularly strong at long-running software engineering tasks, verifying its own work, and...
Specification
- Context window
- 500K
- Max output
- 450K
- Knowledge cutoff
- Not stated
- Parameters
- Undisclosed
- Licence
- Proprietary
- Serving providers
- 1
- Moderated
- No
- Uptime
- 100.0%
Intelligence
46.4
96th percentile
Coding
—
Coding Index
Agentic
—
Agentic Index
Output speed
71 t/s
Median across providers
Latency
2.33s
Time to first token
Cost per task
$0.58
Estimated
Benchmarks
Where the score comes from
The Intelligence Index is a composite. These are the underlying evaluations this model was actually measured on.
Evaluation scores
Percentage correct · higher is better
- AA-LCR (long context)76.7%
- SciCode57.4%
- Humanity's Last Exam43.1%
An evaluation missing from this list was not run for this model — it is not a zero.
View as table
| Evaluation | Score |
|---|---|
| AA-LCR (long context) | 76.7% |
| SciCode | 57.4% |
| Humanity's Last Exam | 43.1% |
Against its peers
Intelligence Index · this model highlighted, nearest peers in grey
- Muse Spark 1.3Meta48.1
- GPT-6 SolOpenAI47.6
- GPT-5.6 SolOpenAI47.0
- Grok 4.7xAI46.4
- MiMo-V2.6-ProXiaomi46.3
- 45.4
- GLM 5.3Z.ai44.8
- Grok 4.6xAI44.3
Peers are the models sitting closest on the Intelligence Index — the set you would realistically choose between.
View as table
| Model | Intelligence |
|---|---|
| Muse Spark 1.3 | 48.1 |
| GPT-6 Sol | 47.6 |
| GPT-5.6 Sol | 47.0 |
| Grok 4.7 | 46.4 |
| MiMo-V2.6-Pro | 46.3 |
| Qwen3.8 Max (0902) | 45.4 |
| GLM 5.3 | 44.8 |
| Grok 4.6 | 44.3 |
Percentile among all indexed models
Pricing
What it costs to run
List prices per million tokens, plus what one representative task works out to.
List price
- Input / 1M tokens
- $2
- Output / 1M tokens
- $6
- Cached input / 1M
- $0.5
- Blended 3:1
- $3
One task, estimated
$0.58
- Input tokens
- 50,000
- Output tokens
- 80,000
- Profile
- Reasoning
Estimated from list pricing: 50K input tokens plus 80K output tokens for reasoning models (25K for non-reasoning).
Serving providers
Speed and latency figures are medians across these providers, so a widely-served model reports a blend rather than any single endpoint.
Arena
Head-to-head generation quality
Elo from pairwise judgements, broken out by the kind of thing the model was asked to build.
- Overall Elo
- 1,310
- Win rate
- 51.5%
- Strongest at
- Game development
- Tournaments
- 555
Elo by category
Dot position on a 1,225–1,325 scale · Elo has no meaningful zero
- 1,310
- 1,273
- 1,271
- 1,249
- 1,236
Agent categories (full-stack apps, mobile apps) are only scored for models tested in agent harnesses.
View as table
| Category | Elo | Win rate |
|---|---|---|
| Game development | 1310 | 51.5% |
| 3D scenes | 1273 | 48.1% |
| UI components | 1271 | 48.1% |
| Websites | 1249 | 45.1% |
| Data visualisation | 1236 | 45.7% |