AI Model Comparison

GPT-5.4 mini vs Claude 4.1 Opus

Verdict
GPT-5.4 mini vs Claude 4.1 Opus: GPT-5.4 mini scores higher on the Intelligence Index

Head-to-head specifications

MetricGPT-5.4 miniClaude 4.1 OpusDifference
Intelligence Index40.030.0+33.3%
Context window922K tokens262K tokens
Blended price ($/1M tokens)$0.52$1.68-69.0%
Output speed (tokens/s)17030+466.7%
AccessProprietary APIProprietary API
  • GPT-5.4 mini leads overall capability (Intelligence Index 40.0 vs 30.0).
  • GPT-5.4 mini is the cheaper model to run at $0.52/1M blended tokens — about 3.2× cheaper.
  • GPT-5.4 mini offers the larger context window (922K tokens), useful for long documents and codebases.

Verdict: GPT-5.4 mini or Claude 4.1 Opus?

Our recommendation
GPT-5.4 mini is the clearly stronger overall choice, winning most of the dimensions that matter.

GPT-5.4 mini advantages

  • General intelligence (+25%)
  • Context window (+72%)
  • Affordability (+69%)
  • Output speed (+82%)

Claude 4.1 Opus advantages

  • No decisive advantage on the tracked metrics.

Which should you choose?

  • Choose the GPT-5.4 mini if you need the strongest overall reasoning and accuracy.
  • Choose the GPT-5.4 mini if you work with long documents or large codebases.

Value for money

GPT-5.4 mini offers more intelligence per dollar (4.3× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.

GPT-5.4 mini vs Claude 4.1 Opus: which should you choose?

GPT-5.4 mini — OpenAI multimodal model with an Intelligence Index of 40, a 922K-token context window and a blended price of $0.52/1M tokens.

Claude 4.1 Opus — Anthropic multimodal model with an Intelligence Index of 30, a 262K-token context window and a blended price of $1.68/1M tokens.

GPT-5.4 mini vs Claude 4.1 Opus: GPT-5.4 mini scores higher on the Intelligence Index. GPT-5.4 mini leads overall capability (Intelligence Index 40.0 vs 30.0). GPT-5.4 mini is the cheaper model to run at $0.52/1M blended tokens — about 3.2× cheaper.

Capability: intelligence, coding and agentic work

On the composite Intelligence Index the GPT-5.4 mini scores 40.0 versus 30.0. Composite indices summarize many evaluations, but always test on your own workload before committing.

Context window and speed

The GPT-5.4 mini accepts up to 922K tokens per request, which sets how much documentation, transcript or code it can reason over at once. In measured throughput, GPT-5.4 mini generates faster (170 vs 30 tokens/s), which matters for interactive apps and high-volume pipelines.

Pricing and access

At blended per-token rates, GPT-5.4 mini is the cheaper model to run ($0.52 vs $1.68 per 1M tokens). GPT-5.4 mini is proprietary api and Claude 4.1 Opus 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 GPT-5.4 mini better than the Claude 4.1 Opus?

GPT-5.4 mini is the clearly stronger overall choice, winning most of the dimensions that matter. GPT-5.4 mini leads overall capability (Intelligence Index 40.0 vs 30.0).

What is the main difference between the GPT-5.4 mini and the Claude 4.1 Opus?

GPT-5.4 mini leads overall capability (Intelligence Index 40.0 vs 30.0). GPT-5.4 mini is the cheaper model to run at $0.52/1M blended tokens — about 3.2× cheaper.

Which is better value?

GPT-5.4 mini offers more intelligence per dollar (4.3× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.

Which should I choose?

Choose the GPT-5.4 mini if you need the strongest overall reasoning and accuracy. Choose the GPT-5.4 mini if you work with long documents or large codebases.

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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