AI Model Comparison

Grok 4.5 vs o4-mini

Verdict
Grok 4.5 vs o4-mini: Grok 4.5 scores higher on the Intelligence Index

Head-to-head specifications

MetricGrok 4.5o4-miniDifference
Intelligence Index54.029.0+86.2%
Context window922K tokens256K tokens—
Blended price ($/1M tokens)$0.87$0.64+35.9%
Output speed (tokens/s)118167-29.3%
AccessProprietary APIProprietary API—
  • Grok 4.5 leads overall capability (Intelligence Index 54.0 vs 29.0).
  • o4-mini is the cheaper model to run at $0.64/1M blended tokens — about 1.4× cheaper.
  • Grok 4.5 offers the larger context window (922K tokens), useful for long documents and codebases.

Verdict: Grok 4.5 or o4-mini?

Our recommendation
These two are closely matched — the right pick comes down to which specific strengths you value and the price you actually pay.

Grok 4.5 advantages

  • General intelligence (+46%)
  • Context window (+72%)

o4-mini advantages

  • Affordability (+26%)
  • Output speed (+29%)

Which should you choose?

  • Choose the Grok 4.5 if you need the strongest overall reasoning and accuracy.
  • Choose the o4-mini if you want the lowest cost per token at scale.
  • Choose the Grok 4.5 if you work with long documents or large codebases.

Value for money

Grok 4.5 offers more intelligence per dollar (1.4× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.

Grok 4.5 vs o4-mini: which should you choose?

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.

o4-mini — OpenAI multimodal model with an Intelligence Index of 29, a 256K-token context window and a blended price of $0.64/1M tokens.

Grok 4.5 vs o4-mini: Grok 4.5 scores higher on the Intelligence Index. Grok 4.5 leads overall capability (Intelligence Index 54.0 vs 29.0). o4-mini is the cheaper model to run at $0.64/1M blended tokens — about 1.4× cheaper.

Capability: intelligence, coding and agentic work

On the composite Intelligence Index the Grok 4.5 scores 54.0 versus 29.0. 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. In measured throughput, o4-mini generates faster (167 vs 118 tokens/s), which matters for interactive apps and high-volume pipelines.

Pricing and access

At blended per-token rates, o4-mini is the cheaper model to run ($0.64 vs $0.87 per 1M tokens). Grok 4.5 is proprietary api and o4-mini 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 4.5 better than the o4-mini?

These two are closely matched — the right pick comes down to which specific strengths you value and the price you actually pay. Grok 4.5 leads overall capability (Intelligence Index 54.0 vs 29.0).

What is the main difference between the Grok 4.5 and the o4-mini?

Grok 4.5 leads overall capability (Intelligence Index 54.0 vs 29.0). o4-mini is the cheaper model to run at $0.64/1M blended tokens — about 1.4× cheaper.

Which is better value?

Grok 4.5 offers more intelligence per dollar (1.4× 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. Choose the o4-mini if you want the lowest cost per token at scale.

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.

ER
EquivalentTo Research
Data & Benchmarks Team

We compile published benchmark results (Cinebench 2024, Geekbench 6, AnTuTu v10, 3DMark), manufacturer specifications and market pricing from nine regions into normalized, comparable datasets. Every figure traces to a named public source listed on each page.

Benchmark leaderboard compilationMulti-market pricing normalizationUnit & currency conversion
✓ Reviewed by EquivalentTo Editorial Review, Data Quality & Methodology.
Last updated 2026-07-01
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