AI Model Comparison

Claude Sonnet 5 vs GPT-5.4

Verdict
Claude Sonnet 5 vs GPT-5.4: Claude Sonnet 5 scores higher on the Intelligence Index

Head-to-head specifications

MetricClaude Sonnet 5GPT-5.4Difference
Intelligence Index53.051.0+3.9%
Coding Index71.571.1+0.6%
Agentic Index46.741.1
Context window1M tokens1M tokens
Blended price ($/1M tokens)$0.90$1.14-21.1%
Output speed (tokens/s)71151-53.0%
AccessProprietary APIProprietary API
  • Claude Sonnet 5 leads overall capability (Intelligence Index 53.0 vs 51.0).
  • Claude Sonnet 5 is the cheaper model to run at $0.90/1M blended tokens — about 1.3× cheaper.

Verdict: Claude Sonnet 5 or GPT-5.4?

Our recommendation
Claude Sonnet 5 takes the overall edge, though GPT-5.4 wins in specific areas worth weighing.

Claude Sonnet 5 advantages

  • Agentic task performance (+12%)
  • Affordability (+21%)

GPT-5.4 advantages

  • Output speed (+53%)

Which should you choose?

  • Choose the Claude Sonnet 5 if you build agents or multi-step tool-use workflows.
  • Choose the GPT-5.4 if low latency and fast generation matter for your application.
  • Choose the Claude Sonnet 5 if you want the lowest cost per token at scale.

Value for money

Claude Sonnet 5 offers more intelligence per dollar (1.3× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.

Claude Sonnet 5 vs GPT-5.4: which should you choose?

Claude Sonnet 5 — Anthropic multimodal model with an Intelligence Index of 53, a 1M-token context window and a blended price of $0.9/1M tokens.

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 Sonnet 5 vs GPT-5.4: Claude Sonnet 5 scores higher on the Intelligence Index. Claude Sonnet 5 leads overall capability (Intelligence Index 53.0 vs 51.0). Claude Sonnet 5 is the cheaper model to run at $0.90/1M blended tokens — about 1.3× cheaper.

Capability: intelligence, coding and agentic work

On the composite Intelligence Index the Claude Sonnet 5 scores 53.0 versus 51.0. For software development, the Coding Index puts Claude Sonnet 5 ahead (71.5 vs 71.1). On agentic, multi-step tool-use tasks, Claude Sonnet 5 measures stronger. Composite indices summarize many evaluations, but always test on your own workload before committing.

Context window and speed

The Claude Sonnet 5 accepts up to 1 million tokens per request, which sets how much documentation, transcript or code it can reason over at once. In measured throughput, GPT-5.4 generates faster (151 vs 71 tokens/s), which matters for interactive apps and high-volume pipelines.

Pricing and access

At blended per-token rates, Claude Sonnet 5 is the cheaper model to run ($0.90 vs $1.14 per 1M tokens). Claude Sonnet 5 is proprietary api and GPT-5.4 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 Claude Sonnet 5 better than the GPT-5.4?

Claude Sonnet 5 takes the overall edge, though GPT-5.4 wins in specific areas worth weighing. Claude Sonnet 5 leads overall capability (Intelligence Index 53.0 vs 51.0).

What is the main difference between the Claude Sonnet 5 and the GPT-5.4?

Claude Sonnet 5 leads overall capability (Intelligence Index 53.0 vs 51.0). Claude Sonnet 5 is the cheaper model to run at $0.90/1M blended tokens — about 1.3× cheaper.

Which is better value?

Claude Sonnet 5 offers more intelligence per dollar (1.3× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.

Which should I choose?

Choose the Claude Sonnet 5 if you build agents or multi-step tool-use workflows. Choose the GPT-5.4 if low latency and fast generation matter for your application.

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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