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GPT-5.4 benchmarks, pricing and specs

GPT-5.4 is an OpenAI model released on March 5, 2026 that takes text and image input and produces text. It costs $2.50 per 1M input tokens and $15 per 1M output tokens and accepts up to 1,050,000 tokens of context. It scores 1475 Elo on Arena Text, #18 of 39 current models (Arena, measured October 8, 2026).

Per 1M input tokens
$2.50
Per 1M output tokens
$15
Context window
1.05M
Arena Text
1475 Elo · #18/39

Data verified October 12, 2026 · Dataset 2026-10-12

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Key facts

Provider
OpenAI
Model family
GPT-5.4
Release date
March 5, 2026
Status
Current
Access
API only
API model id
Not reported
Context window
1,050,000 tokens
Max output
128,000 tokens
Input
text, image
Output
text
Task families
text, multimodal
Declared capabilities
reasoning

GPT-5.4 pricing

It is the #11 most expensive of 37 current text models priced per 1M input tokens.

UnitPrice (USD)TierAppliesSource
1M input tokens$2.50standardCurrent
1M output tokens$15standardCurrent
1M input tokens$0.25cachedCurrent

Independent benchmark results

Scores come from independent evaluators that ran the model themselves, pinned to a dated snapshot. Rank is among current models in the same snapshot. OpenAI's own launch figures are listed under strengths with the publisher named, because they are not measured the same way.

BenchmarkScoreRankMeasuredSource
Arena Text1475 Elo#18 of 39October 8, 2026Arena · 2026-10-12
GPQA Diamond93.3%#13 of 37October 12, 2026Epoch AI · 2026-10-12
FrontierMath Tiers 1-3 (v2)78.6%#15 of 37October 12, 2026Epoch AI · 2026-10-12
SimpleQA Verified45.1%#23 of 34October 12, 2026Epoch AI · 2026-10-12
LiveBench Overall77.97 points#3 of 5June 25, 2026LiveBench · 2026-06-25

Strengths, cautions and best uses

Strengths

  • GPT-5.4 provides a 1,050,000-token context window and configurable reasoning for complex professional work

Cautions

  • Prompts above the provider long-context threshold use higher token rates; reproduce cost and quality on the target workload

Best for

  • Long-context coding and professional-work evaluations

Alternatives to GPT-5.4

The closest current textmodels by price. The cheapest model that scores as well or better is listed first; failing that, the cheapest one within 3% of the benchmark's scale.

Compare GPT-5.4 with

Articles about GPT-5.4

GPT-5.4 FAQ

How much does GPT-5.4 cost?

GPT-5.4 costs $2.50 per 1M input tokens and $15 per 1M output tokens at the standard tier. It is the #11 most expensive of 37 current text models priced per 1M input tokens. Source: OpenAI, verified August 7, 2026.

What is the context window of GPT-5.4?

GPT-5.4 accepts up to 1,050,000 tokens of context. It can return up to 128,000 tokens in one response. That ranks #1 of 44 current text models by context length.

How does GPT-5.4 score on independent benchmarks?

GPT-5.4 scores 1475 Elo on Arena Text, #18 of 39 current models (Arena, measured October 8, 2026), 93.3% on GPQA Diamond, #13 of 37 current models (Epoch AI, measured October 12, 2026) and 78.6% on FrontierMath Tiers 1-3 (v2), #15 of 37 current models (Epoch AI, measured October 12, 2026). These are independent evaluations, not OpenAI's own launch figures.

Is GPT-5.4 open source or API only?

GPT-5.4 is available through OpenAI's API only; its weights are not published.

What are the best alternatives to GPT-5.4?

The closest current alternatives by price and measured performance are DeepSeek-V4.1-Flash (88% cheaper per 1M input tokens, $0.30 vs $2.50), Kimi K3 (20% more per 1M input tokens, $3 vs $2.50), Claude Sonnet 5 (20% cheaper per 1M input tokens, $2 vs $2.50) and Claude Sonnet 5.5 (20% cheaper per 1M input tokens, $2 vs $2.50).

Sources

Cite this page

Van Data Team. "GPT-5.4 Benchmarks, Pricing and Specs." AI Model Benchmark Dataset 2026-10-12. https://vandatateam.com/ai-model-benchmarks/gpt-5-4

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Production evaluation

Deciding whether GPT-5.4 fits your workload?

Public benchmarks narrow the shortlist. We test the finalists on your own tasks, data and cost limits, then build the routing and review controls to run the winner in production.

  • Evaluation cases and acceptance thresholds tied to real work
  • Model routing, fallbacks and cost controls