AI Model Comparison

Grok 4 vs Grok 4.5

Verdict
Grok 4 vs Grok 4.5: Grok 4.5 scores higher on the Intelligence Index

Head-to-head specifications

MetricGrok 4Grok 4.5Difference
Intelligence Index34.054.0-37.0%
Context window400K tokens922K tokens
Blended price ($/1M tokens)$1.68$0.87+93.1%
AccessProprietary APIProprietary API
  • Grok 4.5 leads overall capability (Intelligence Index 54.0 vs 34.0).
  • Grok 4.5 is the cheaper model to run at $0.87/1M blended tokens — about 1.9× cheaper.
  • Grok 4.5 offers the larger context window (922K tokens), useful for long documents and codebases.

Verdict: Grok 4 or Grok 4.5?

Our recommendation
Grok 4.5 is the clearly stronger overall choice, winning most of the dimensions that matter.

Grok 4 advantages

  • No decisive advantage on the tracked metrics.

Grok 4.5 advantages

  • General intelligence (+37%)
  • Context window (+57%)
  • Affordability (+48%)

Which should you choose?

  • Choose the Grok 4.5 if you need the strongest overall reasoning and accuracy.

Value for money

Grok 4.5 offers more intelligence per dollar (3.1× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.

Grok 4 vs Grok 4.5: which should you choose?

Grok 4 — xAI multimodal model with an Intelligence Index of 34, a 400K-token context window and a blended price of $1.68/1M tokens.

Grok 4.5 — xAI multimodal model with an Intelligence Index of 54, a 922K-token context window and a blended price of $0.87/1M tokens.

Grok 4 vs Grok 4.5: Grok 4.5 scores higher on the Intelligence Index. Grok 4.5 leads overall capability (Intelligence Index 54.0 vs 34.0). Grok 4.5 is the cheaper model to run at $0.87/1M blended tokens — about 1.9× cheaper.

Capability: intelligence, coding and agentic work

On the composite Intelligence Index the Grok 4.5 scores 54.0 versus 34.0. Composite indices summarize many evaluations, but always test on your own workload before committing.

Context window and speed

The Grok 4.5 accepts up to 922K tokens per request, which sets how much documentation, transcript or code it can reason over at once.

Pricing and access

At blended per-token rates, Grok 4.5 is the cheaper model to run ($0.87 vs $1.68 per 1M tokens). Grok 4 is proprietary api and Grok 4.5 is proprietary api. Open-weight models can be self-hosted, trading per-call cost for infrastructure you manage; for production also weigh rate limits, throughput and data-residency requirements.

The verdict

Both are credible choices in the ai model comparison space; the specification table above lays out every metric so you can weigh the trade-offs that matter to you. Pick the one whose strengths line up with how you will actually use it.

Frequently asked questions

Is the Grok 4 better than the Grok 4.5?

Grok 4.5 is the clearly stronger overall choice, winning most of the dimensions that matter. Grok 4.5 leads overall capability (Intelligence Index 54.0 vs 34.0).

What is the main difference between the Grok 4 and the Grok 4.5?

Grok 4.5 leads overall capability (Intelligence Index 54.0 vs 34.0). Grok 4.5 is the cheaper model to run at $0.87/1M blended tokens — about 1.9× cheaper.

Which is better value?

Grok 4.5 offers more intelligence per dollar (3.1× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.

Which should I choose?

Choose the Grok 4.5 if you need the strongest overall reasoning and accuracy.

Methodology

Large language models are compared on independent leaderboard metrics: an Intelligence Index (a composite of reasoning and knowledge evaluations), Coding and Agentic indices where measured, community arena Elo, maximum context window, a blended API price per million tokens (weighted across cache-hit, input and output rates), and measured output speed in tokens per second. Where a model ships multiple reasoning-effort variants, we report its strongest variant. Benchmarks capture only part of real-world quality, which also depends on tool use, latency, safety and task fit — and this space moves quickly, so figures reflect the leaderboard snapshot on the page date.

MC
Marcus Chen
Hardware & Product Analyst

Marcus benchmarks processors, GPUs, phones and vehicles and maintains normalized performance databases.

MSc Computer Engineering10+ years review experience
✓ Reviewed by Priya Nair, Data Quality Reviewer.
Last updated 2026-07-01
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