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Head-to-Head Model Comparison

GPT-5.4 mini vs GPT-5.4 nano

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Verificato dal team di ricerca di GetInfoUsUltima verifica: October 2026Politica editoriale
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
GPT-5.4 mini vs GPT-5.4 nano: Benchmarks, Pricing & Speed Comparison

GPT-5.4 mini di OpenAI e GPT-5.4 nano di OpenAI sono due modelli di IA di riferimento. GPT-5.4 mini offre una finestra di contesto di 400K token a $0.50/$4.00 per milione di token, mentre GPT-5.4 nano mette a disposizione 400K token di contesto a $0.10/$0.80 per milione di token. Di seguito analizziamo benchmark, latenza e costi.

Confronto Diretto (VS)

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OpenAI

GPT-5.4 mini

Modello Leggero ed Economico

GPT-5.4 mini di OpenAI è un modello di IA progettato per la massima efficienza dei costi per token e l’inferenza rapida in produzione, con finestra di contesto da 400K, velocità di 175 token/s, indice di intelligenza di 59/100 e tariffa di

Intelligence Index59 / 100
Input Token:

$0.50 / 1M

Output Token:

$4.00 / 1M

Context Window:

400K tokens

SWE-bench Verified:

68.5%

OpenAI

GPT-5.4 nano

Modello Leggero ed Economico

GPT-5.4 nano di OpenAI è un modello di IA progettato per la massima efficienza dei costi per token e l’inferenza rapida in produzione, con finestra di contesto da 400K, velocità di 235 token/s, indice di intelligenza di 45/100 e tariffa di

Intelligence Index45 / 100
Input Token:

$0.10 / 1M

Output Token:

$0.80 / 1M

Context Window:

400K tokens

SWE-bench Verified:

48%

Differenze Chiave a Colpo d’Occhio

  • GPT-5.4 nano is 5.0x cheaper for API usage (input + output tokens combined).
  • GPT-5.4 nano is faster at 235 tok/s vs 175 tok/s.
  • GPT-5.4 mini leads on SWE-bench coding (68.5% vs 48.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGPT-5.4 miniGPT-5.4 nano
Intelligence Index
Composite reasoning & knowledge score (0-100)
5945
Provider
OpenAIOpenAI
Input Price
Cost per million input tokens
$0.50 / 1M$0.10 / 1M
Output Price
Cost per million output tokens
$4.00 / 1M$0.80 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.53 / 1M$0.11 / 1M
Context Window
Maximum input + output tokens
400K tokens~600 A4 pages of text400K tokens~600 A4 pages of text
Max Output Tokens
Per single request
128K128K
Throughput Speed
Tokens generated per second
175 tok/s235 tok/s
SWE-bench Verified
Real-world software engineering
68.5%48%
GPQA Diamond
Graduate-level reasoning
72.5%61.5%
Cached Input Price
Prompt caching discount per 1M tokens
$0.05 / 1M$0.01 / 1M

Chi vince in ogni categoria?

At-a-glance decision framework
Coding
GPT-5.4 mini
+20.5% SWE-bench lead
Cost
GPT-5.4 nano
5.0x cheaper monthly runtime
Speed
GPT-5.4 nano
+34% faster generation
Context
Tied
400K tokens window

Punteggi Benchmark Verificati

Official evaluation metrics verified by independent third-party research labs.

GPT-5.4 miniGPT-5.4 nano
SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

68.5%vs48%
GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

72.5%vs61.5%
MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

84.8%vs75.8%
LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1375ptsvs1310pts
Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

12.2%vs8.6%
Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

41.5%vs26%
SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

40%vs28%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

67%vs51.5%
AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

89.6%vs78%
Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

78%vs66.5%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

175 tok/s vs235 tok/s

Latenza e Tempo di Risposta

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better
GPT-5.4 mini0.76s
GPT-5.4 nano0.40s
Est. End-to-End Response (500 tokens)TTFT + generation time
GPT-5.4 mini3.62s
GPT-5.4 nano2.53s

Simulatore Interattivo dei Costi Token

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
GPT-5.4 mini Monthly API Bill
$4.42 / month
$0.5/1M in · $4/1M out
GPT-5.4 nano Monthly API Bill
$0.89 / month
$0.1/1M in · $0.8/1M out
GPT-5.4 nano saves approximately $3.54 / month (80%) under this workload.5.0x Savings

GPT-5.4 mini · Strengths & Key Advantages

  • Finestra di contesto da 400K con capacità massima di output fino a 128K token (SWE-bench Verified 68.5% · GPQA Diamond 72.5%)
  • Throughput elevato di 175 token/secondo con latenza al primo token (TTFT) di soli 760 ms
  • Economia API competitiva ($0.5/$4 per 1M di token) con supporto per prompt caching, tool calling e output JSON strutturati
Considerations & Trade-offs
  • Modello cloud proprietario chiuso; non consente il download locale dei pesi per l’esecuzione offline
  • Nelle dimostrazioni scientifiche più estreme, i modelli di ragionamento pesante dedicati offrono maggiore profondità

GPT-5.4 nano · Strengths & Key Advantages

  • Finestra di contesto da 400K con capacità massima di output fino a 128K token (SWE-bench Verified 48% · GPQA Diamond 61.5%)
  • Throughput elevato di 235 token/secondo con latenza al primo token (TTFT) di soli 400 ms
  • Economia API competitiva ($0.1/$0.8 per 1M di token) con supporto per prompt caching, tool calling e output JSON strutturati
Considerations & Trade-offs
  • Modello cloud proprietario chiuso; non consente il download locale dei pesi per l’esecuzione offline
  • Nelle dimostrazioni scientifiche più estreme, i modelli di ragionamento pesante dedicati offrono maggiore profondità

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

MetricGPT-5.4 miniGPT-5.4 nano
Cost per Task
Estimated USD to finish one task
$0.62$0.11
Output Tokens / Task
Tokens generated per task
52K44K
Reasoning Tokens / Task
Thinking tokens burned per task
27K19K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

FeatureGPT-5.4 miniGPT-5.4 nano
Official API Model ID (SDK)gpt-5-4-minigpt-5-4-nano
API ProtocolOpenAI Responses API & Chat Completions v1OpenAI Responses API & Chat Completions v1
Release Date2026-032026-03
Knowledge CutoffAugust 2025August 2025
ArchitectureCompact agent-ready reasoning modelNano agent-ready reasoning model
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($0.5/1M in) across full 400K windowFlat rate ($0.1/1M in) across full 400K window
Prompt Cache Policy & TTLAutomatic prefix caching at $0.05/1M (no extra cache-write fee)Automatic prefix caching at $0.01/1M (no extra cache-write fee)
Computer Use / GUI AgentSupported (Screen coordinate grounding, browser & desktop GUI action loops)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxNative Web Search tool + Hosted Code Interpreter & File Search RAGNative Web Search tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning SupportSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
Multimodal Token BillingText BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)
Quantization & Min GPU VRAMCloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier ClassificationOpenAI Preparedness Framework Audited & System Card PublishedOpenAI Preparedness Framework Audited & System Card Published
Enterprise Compliance (ZDR/HIPAA/SOC2)SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestext, visiontext, vision
Output Modalitiestexttext

GPT-5.4 mini vs GPT-5.4 nano: Risposte Rapide (FAQ)

Which is more intelligent, GPT-5.4 mini or GPT-5.4 nano?

GPT-5.4 mini is more intelligent. It scores 59 compared with 45 on the composite Intelligence Index.

Which model is faster?

GPT-5.4 nano is faster, generating 235 tokens per second compared with 175 tokens per second.

Which model is cheaper to run?

GPT-5.4 nano is cheaper at $0.11 per 1M tokens blended, compared with $0.53 (7:2:1 cache:input:output ratio).

Which model has lower latency?

GPT-5.4 nano has lower latency, with a time to first token of 0.40s compared with 0.76s.

Verdetto

Sia GPT-5.4 mini (Ideale per la massima efficienza dei costi per token e l’inferenza rapida in produzione, sistemi RAG aziendali e integrazioni API scalabili.) sia GPT-5.4 nano (Ideale per la massima efficienza dei costi per token e l’inferenza rapida in produzione, sistemi RAG aziendali e integrazioni API scalabili.) eccellono in produzione: GPT-5.4 mini guida nei benchmark di ragionamento e programmazione, GPT-5.4 nano garantisce una generazione più rapida e GPT-5.4 nano offre il miglior rapporto qualità-prezzo per carichi API elevati.

Domande Frequenti (FAQ)

Quale modello è migliore per coding e ragionamento, GPT-5.4 mini o GPT-5.4 nano?+

Nell’indice di intelligenza composito e nei benchmark di programmazione prevale GPT-5.4 mini. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.

Qual è la differenza di prezzo API tra GPT-5.4 mini e GPT-5.4 nano?+

GPT-5.4 mini costa $0.50 / $4.00 per milione di token di input/output, mentre GPT-5.4 nano costa $0.10 / $0.80. Nel costo combinato, GPT-5.4 nano risulta più economico.

Quale modello ha la finestra di contesto più ampia e la velocità maggiore?+

GPT-5.4 mini supporta 400K token di contesto contro 400K token di GPT-5.4 nano, mentre GPT-5.4 nano offre una velocità di generazione superiore.

AI Terminology & Guide
Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

Tokens & PricingContext WindowAI BenchmarksReasoning ModelsTool CallingModel Context Protocol (MCP)

Related reading

Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.

Fonti ufficiali: Documentazione API ufficiale di OpenAI e OpenAI, schede di sistema e benchmark indipendenti (2026).