Head-to-Head Model Comparison

Claude Sonnet 5.5 vs Gemini 4 Argon

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
Claude Sonnet 5.5 vs Gemini 4 Argon: Benchmarks, Pricing & Speed Comparison

Claude Sonnet 5.5 di Anthropic e Gemini 4 Argon di Google sono due modelli di IA di riferimento. Claude Sonnet 5.5 offre una finestra di contesto di 1M token a $2.00/$10.00 per milione di token, mentre Gemini 4 Argon mette a disposizione 1M token di contesto a $2.00/$10.00 per milione di token. Di seguito analizziamo benchmark, latenza e costi.

Confronto Diretto (VS)

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Anthropic

Claude Sonnet 5.5

Modello Ammiraglia di Frontiera

Claude Sonnet 5.5 di Anthropic è un modello di IA progettato per il ragionamento aziendale di frontiera, la programmazione avanzata e i carichi di produzione, con finestra di contesto da 1M, velocità di 105 token/s, indice di intelligenza d

Intelligence Index78 / 100
Input Token:

$2.00 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

82.9%

Google

Gemini 4 Argon

IA Multimodale Nativa

Gemini 4 Argon di Google è un modello di IA progettato per la comprensione multimodale nativa di testo e immagini e l’analisi visiva dei documenti, con finestra di contesto da 1M, velocità di 115 token/s, indice di intelligenza di 97/100 e

Intelligence Index97 / 100
Input Token:

$2.00 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

81.9%

Differenze Chiave a Colpo d’Occhio

  • Gemini 4 Argon is 1.0x cheaper for API usage (input + output tokens combined).
  • Gemini 4 Argon is faster at 115 tok/s vs 105 tok/s.
  • Claude Sonnet 5.5 leads on SWE-bench coding (82.9% vs 81.9%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureClaude Sonnet 5.5Gemini 4 Argon
Intelligence Index
Composite reasoning & knowledge score (0-100)
7897
Provider
AnthropicGoogle
Input Price
Cost per million input tokens
$2.00 / 1M$2.00 / 1M
Output Price
Cost per million output tokens
$10.00 / 1M$10.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$1.54 / 1M$1.47 / 1M
Context Window
Maximum input + output tokens
1M tokens~1,500 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
128K1000K
Throughput Speed
Tokens generated per second
105 tok/s115 tok/s
SWE-bench Verified
Real-world software engineering
82.9%81.9%
GPQA Diamond
Graduate-level reasoning
79.4%81.5%
Cached Input Price
Prompt caching discount per 1M tokens
$0.20 / 1M$0.10 / 1M

Chi vince in ogni categoria?

At-a-glance decision framework
Coding
Claude Sonnet 5.5
+1.0% SWE-bench lead
Cost
Gemini 4 Argon
1.0x cheaper monthly runtime
Speed
Gemini 4 Argon
+10% faster generation
Context
Tied
1M tokens window

Punteggi Benchmark Verificati

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

Claude Sonnet 5.5Gemini 4 Argon
SWE-bench Verified (Autonomous Coding)

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

82.9%vs81.9%
GPQA Diamond (Doctorate-Level Science & Math)

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

79.4%vs81.5%
MMLU-Pro (Multi-task Language Understanding)

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

90.1%vs90.8%
LMSYS Chatbot Arena Elo

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

1490ptsvs1525pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

N/Avs18.9%
Terminal-Bench (Agentic Coding & Terminal Use)

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

58.9%vs57.4%
SciCode (Scientific Computing)

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

N/Avs56.4%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs80.5%
AIME (Advanced Math Competition)

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

N/Avs94.8%
Long-Context Reasoning

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

N/Avs96.4%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

105 tok/s vs115 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
Claude Sonnet 5.50.55s
Gemini 4 Argon0.85s
Est. End-to-End Response (500 tokens)TTFT + generation time
Claude Sonnet 5.55.31s
Gemini 4 Argon5.20s

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)
Claude Sonnet 5.5 Monthly API Bill
$12.30 / month
$2/1M in · $10/1M out
Gemini 4 Argon Monthly API Bill
$12.15 / month
$2/1M in · $10/1M out
Gemini 4 Argon saves approximately $0.15 / month (1%) under this workload.1.0x Savings

Claude Sonnet 5.5 · Strengths & Key Advantages

  • Finestra di contesto da 1M con capacità massima di output fino a 128K token (SWE-bench Verified 82.9% · GPQA Diamond 79.4%)
  • Throughput elevato di 105 token/secondo con latenza al primo token (TTFT) di soli 550 ms
  • Economia API competitiva ($2/$10 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
  • Per volumi di traffico elevati in produzione si consiglia di attivare il prompt caching e la Batch API

Gemini 4 Argon · Strengths & Key Advantages

  • Finestra di contesto da 1M con capacità massima di output fino a 1M token (SWE-bench Verified 81.9% · GPQA Diamond 81.5%)
  • Throughput elevato di 115 token/secondo con latenza al primo token (TTFT) di soli 850 ms
  • Economia API competitiva ($2/$10 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
  • Per volumi di traffico elevati in produzione si consiglia di attivare il prompt caching e la Batch API

Token Use & Task Economics

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

MetricClaude Sonnet 5.5Gemini 4 Argon
Cost per Task
Estimated USD to finish one task
$3.29$2.45
Output Tokens / Task
Tokens generated per task
72K75K
Reasoning Tokens / Task
Thinking tokens burned per task
37K36K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

FeatureClaude Sonnet 5.5Gemini 4 Argon
Official API Model ID (SDK)claude-sonnet-5-5-20260901models/gemini-4-argon
API ProtocolAnthropic Messages API + AWS Bedrock + Vertex AIGoogle Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date2026-092026-09
Knowledge CutoffJune 2026June 2026
ArchitectureAdaptive Frontier Multimodal TransformerPathways Multimodal Sparse Mixture-of-Experts
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Standard rate up to 200K tokens; 2x input/output tier above 200K tokensStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTL$0.2/1M cached read (90% off); 5-min default & 1-hour extended TTLImplicit + Explicit Context Caching at $0.1/1M with configurable TTL
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 Citations + Code Execution Tool + MCP ConnectorsBuilt-in Google Search Grounding + Managed Python Code Execution Sandbox
Official Fine-Tuning SupportCustom Model Tuning via Amazon Bedrock & Prompt DistillationVertex AI Supervised Adapter Tuning & Context Distillation
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) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec)
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 ClassificationAnthropic RSP ASL-2 / ASL-3 Constitutional Safety EvaluatedGoogle DeepMind Frontier Safety Framework Verified
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, audio, video
Output Modalitiestexttext

Claude Sonnet 5.5 vs Gemini 4 Argon: Risposte Rapide (FAQ)

Which is more intelligent, Claude Sonnet 5.5 or Gemini 4 Argon?

Gemini 4 Argon is more intelligent. It scores 97 compared with 78 on the composite Intelligence Index.

Which model is faster?

Gemini 4 Argon is faster, generating 115 tokens per second compared with 105 tokens per second.

Which model is cheaper to run?

Gemini 4 Argon is cheaper at $1.47 per 1M tokens blended, compared with $1.54 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Claude Sonnet 5.5 has lower latency, with a time to first token of 0.55s compared with 0.85s.

Verdetto

Sia Claude Sonnet 5.5 (Ideale per il ragionamento aziendale di frontiera, la programmazione avanzata e i carichi di produzione, sistemi RAG aziendali e integrazioni API scalabili.) sia Gemini 4 Argon (Ideale per la comprensione multimodale nativa di testo e immagini e l’analisi visiva dei documenti, sistemi RAG aziendali e integrazioni API scalabili.) eccellono in produzione: Gemini 4 Argon guida nei benchmark di ragionamento e programmazione, Gemini 4 Argon garantisce una generazione più rapida e Gemini 4 Argon offre il miglior rapporto qualità-prezzo per carichi API elevati.

Domande Frequenti (FAQ)

Quale modello è migliore per coding e ragionamento, Claude Sonnet 5.5 o Gemini 4 Argon?+

Nell’indice di intelligenza composito e nei benchmark di programmazione prevale Gemini 4 Argon. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.

Qual è la differenza di prezzo API tra Claude Sonnet 5.5 e Gemini 4 Argon?+

Claude Sonnet 5.5 costa $2.00 / $10.00 per milione di token di input/output, mentre Gemini 4 Argon costa $2.00 / $10.00. Nel costo combinato, Gemini 4 Argon risulta più economico.

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

Claude Sonnet 5.5 supporta 1M token di contesto contro 1M token di Gemini 4 Argon, mentre Gemini 4 Argon 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.

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 Anthropic e Google, schede di sistema e benchmark indipendenti (2026).