AI Model Comparison

GPT-5.4 vs Claude 4 Sonnet

Verdict
GPT-5.4 vs Claude 4 Sonnet: GPT-5.4 scores higher on the Intelligence Index

Head-to-head specifications

MetricGPT-5.4Claude 4 SonnetDifference
Intelligence Index51.029.0+75.9%
Coding Index71.137.6+89.1%
Agentic Index41.116.6
Context window1M tokens1M tokens
Blended price ($/1M tokens)$1.14$1.20-5.0%
AccessProprietary APIProprietary API
  • GPT-5.4 leads overall capability (Intelligence Index 51.0 vs 29.0).
  • GPT-5.4 is the cheaper model to run at $1.14/1M blended tokens — about 1.1× cheaper.

Verdict: GPT-5.4 or Claude 4 Sonnet?

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

GPT-5.4 advantages

  • General intelligence (+43%)
  • Coding ability (+47%)
  • Agentic task performance (+60%)
  • Affordability (+5%)

Claude 4 Sonnet advantages

  • No decisive advantage on the tracked metrics.

Which should you choose?

  • Choose the GPT-5.4 if you need the strongest overall reasoning and accuracy.
  • Choose the GPT-5.4 if coding and software development are your main workload.

Value for money

GPT-5.4 offers more intelligence per dollar (1.9× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.

GPT-5.4 vs Claude 4 Sonnet: which should you choose?

GPT-5.4 — OpenAI multimodal model with an Intelligence Index of 51, a 1M-token context window and a blended price of $1.14/1M tokens.

Claude 4 Sonnet — Anthropic multimodal model with an Intelligence Index of 29, a 1M-token context window and a blended price of $1.2/1M tokens.

GPT-5.4 vs Claude 4 Sonnet: GPT-5.4 scores higher on the Intelligence Index. GPT-5.4 leads overall capability (Intelligence Index 51.0 vs 29.0). GPT-5.4 is the cheaper model to run at $1.14/1M blended tokens — about 1.1× cheaper.

Capability: intelligence, coding and agentic work

On the composite Intelligence Index the GPT-5.4 scores 51.0 versus 29.0. For software development, the Coding Index puts GPT-5.4 ahead (71.1 vs 37.6). On agentic, multi-step tool-use tasks, GPT-5.4 measures stronger. Composite indices summarize many evaluations, but always test on your own workload before committing.

Context window and speed

The GPT-5.4 accepts up to 1 million 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, GPT-5.4 is the cheaper model to run ($1.14 vs $1.20 per 1M tokens). GPT-5.4 is proprietary api and Claude 4 Sonnet 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 better than the Claude 4 Sonnet?

GPT-5.4 is the clearly stronger overall choice, winning most of the dimensions that matter. GPT-5.4 leads overall capability (Intelligence Index 51.0 vs 29.0).

What is the main difference between the GPT-5.4 and the Claude 4 Sonnet?

GPT-5.4 leads overall capability (Intelligence Index 51.0 vs 29.0). GPT-5.4 is the cheaper model to run at $1.14/1M blended tokens — about 1.1× cheaper.

Which is better value?

GPT-5.4 offers more intelligence per dollar (1.9× 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 if you need the strongest overall reasoning and accuracy. Choose the GPT-5.4 if coding and software development are your main workload.

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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