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OpenAI · budget

Is GPT-5.4 Nano good?

GPT-5.4 Nano has been tested across 6 task areas. It's strongest at ai strategy and weakest at executive assistant. It's a budget-friendly option ($1.45/1M tokens).

Top-3 finishes
6/22
Task areas tested
$1.45
Per 1M tokens
Slow
Typical speed

Our take

OpenAI: GPT-5.4 Nano is a budget-tier model that we tested across 6 task areas. It performs best at AI Strategy, and is weakest at Executive Assistant.

Strengths

Specificity Structure Concision Risk detection Risk handling

Weak spots

Reduces heat Timing accuracy Practical sequencing Food quality Judgement Human tone

How GPT-5.4 Nano ranks, task by task

Rank is the position in each field; Rating is the absolute quality bar. A model can be rated "Excellent" yet sit mid-table when the whole field is strong — and vice-versa.

Task area Rank
AI Strategy #31 of 50
Content & Brand #33 of 50
Investor & Pitch #35 of 50
Landing Pages #42 of 56
Chef / Home Cooking #44 of 50
Executive Assistant #50 of 50

Industry benchmarks

Standardized third-party scores, shown for context — these are independent of our real-task tests.

Artificial Analysis indices

38.2
Intelligence
56.1
Coding
27.5
Agentic

Headline vs. real-world

GPT-5.4 Nano looks strong on paper but underperforms on our real-world tasks relative to its Intelligence Index.

Source: Artificial Analysis (artificialanalysis.ai) via OpenRouter (openrouter.ai/rankings). (2026-06-29) · Source: Design Arena (www.designarena.ai) via OpenRouter (openrouter.ai/rankings). (2026-06-29)

Like GPT-5.4 Nano, but…

Cheaper

Smarter

Frequently asked

Is GPT-5.4 Nano any good?

GPT-5.4 Nano places top-3 in 0 of 6 task areas we benchmarked. It performs best at AI Strategy.

What is GPT-5.4 Nano best at?

Its strongest task areas are AI Strategy, Content & Brand, Investor & Pitch.

Is there a cheaper alternative to GPT-5.4 Nano?

DeepSeek V3.2 is 61% cheaper and stays competitive on quality across our benchmarks.

How we test & rank

Each model is scored on real tasks across 6 task areas by an LLM judge with deterministic checks. "Percentile" is this model's standing within each area's field; the cross-area figures are rank-based so quality and Elo scores are never mixed.

This page is Spring Prompt, running

We just did this for every model. Do it for your prompt.

The rankings above come from running real tasks through real models and scoring every output. Spring Prompt is that same engine — pointed at your prompt, your test cases, and your definition of good.

  • Generate test cases from your prompt — no eval set required to start.
  • Compare models side by side with quality, cost and latency in one matrix.
  • Optimise the winner until the scores say it's ready to ship.
Experiment · Cold outreach email

Prompt × model results

12 test cases · 3 evals
Claude Opus
GPT-5
Gemini
v1
7.1
6.8
7.4
v2
8.3
7.9
8.0
v3
9.2
8.6
8.4
Best combo: v3 × Claude Opus
9.2 quality · $0.004/run · 1.8s