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SpaceXAI Releases Grok 4.7

AI-assisted summaries and translations. Check original sources for context and performance claims.

CHOI · @choi.openai · Original language: 한국어

SpaceXAI has launched Grok 4.7, featuring a larger base model and enhanced reinforcement learning for complex tasks. While the model shows significant gains in coding and document analysis, its overall intelligence score improvement remains modest compared to top-tier competitors.

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  1. Grok 4.7 Announcement
  2. Model Enhancements
  3. Benchmark Performance
  4. Token Usage and Speed
  5. Knowledge Task Improvements
  6. Coding Agent Gains
  7. Mixed Results in Other Areas
  8. Competitive API Pricing
  9. Cost-Efficiency Analysis
  10. Overall Assessment
  11. Source Information

Grok 4.7 Announcement

SpaceXAI has officially released Grok 4.7, now available across Cursor, Grok Build, and the Grok API.

Grok 4.7 Announcement
@choi.openai · Source post ↗

Model Enhancements

Grok 4.7 introduces a larger base model and focuses reinforcement learning on long-duration tasks. The company reports improved detail in generative tasks, such as the urban game demo.

Benchmark Performance

According to Choi citing Artificial Analysis, Grok 4.7 scored 46 points, a 2-point increase over version 4.6. It remains behind leaders like GPT-6 Astra and Fable 5.1, which scored 53 points.

Benchmark Performance
@choi.openai · Source post ↗
Benchmark Performance
@choi.openai · Source post ↗

Token Usage and Speed

Output tokens per task increased by 125% to 81,000, significantly higher than competitors. However, generation time improved, dropping from 9.5 minutes to 7.1 minutes.

Token Usage and Speed
@choi.openai · Source post ↗

Knowledge Task Improvements

Grok 4.7 showed strong gains in the AA-Briefcase benchmark, particularly in analysis quality. However, performance in output presentation quality saw a slight decline.

Knowledge Task Improvements
@choi.openai · Source post ↗

Coding Agent Gains

Coding agent performance rose from 47 to 56 points, surpassing GPT-5.6 Sol. Notable improvements were seen across DeepSWE and Terminal-Bench metrics.

Coding Agent Gains
@choi.openai · Source post ↗

Mixed Results in Other Areas

Performance in long-context reasoning and automation benchmarks remained stagnant or declined slightly. Hallucination rates decreased, though overall accuracy remained largely unchanged.

Mixed Results in Other Areas
@choi.openai · Source post ↗

Competitive API Pricing

Grok 4.7 maintains the pricing of its predecessor, offering a cost-effective alternative to GPT-5.6 Sol and Opus 5. It supports a 500k token context window.

Competitive API Pricing
@choi.openai · Source post ↗

Cost-Efficiency Analysis

CursorBench data suggests Grok 4.7 offers better cost-efficiency than Fable 5.1 and GPT-5.6 Sol in mid-range performance tasks. However, Fable 5.1 still leads in peak performance settings.

Cost-Efficiency Analysis
@choi.openai · Source post ↗

Overall Assessment

While Grok 4.7 provides valuable improvements in coding and cost-efficiency, its overall intelligence gains are limited. It is not yet a definitive rival to the absolute top-tier models.

Overall Assessment
@choi.openai · Source post ↗
Overall Assessment
@choi.openai · Source post ↗

Source Information

Official release details are available at the x.ai news portal.

Source notes

This is a linked resource, not an independent verification of performance, cost or results. Check the original for current details.

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2026-09-21
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