Head-to-Head Model Comparison

Claude Opus 4 vs Gemini 2.5 Flash-Lite

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Verificato dal team di ricerca di GetInfoUsUltima verifica: October 2026Politica editoriale
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Related topics (12)
AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Claude Opus 4 vs Gemini 2.5 Flash-Lite: Benchmarks, Pricing & Speed Comparison

Claude Opus 4 di Anthropic e Gemini 2.5 Flash-Lite di Google sono due modelli di IA di riferimento. Claude Opus 4 offre una finestra di contesto di 200K token a $15.00/$75.00 per milione di token, mentre Gemini 2.5 Flash-Lite mette a disposizione 1.05M token di contesto a $0.10/$0.40 per milione di token. Di seguito analizziamo benchmark, latenza e costi.

Confronto Diretto (VS)

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Claude Opus 4

Motore di Ragionamento Profondo

Claude Opus 4 di Anthropic è un modello di IA progettato per il ragionamento logico profondo, la matematica avanzata e l’analisi scientifica, con finestra di contesto da 200K, velocità di 42 token/s, indice di intelligenza di 61/100 e tarif

Intelligence Index61 / 100
Input Token:

$15.00 / 1M

Output Token:

$75.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

72.5%

Google

Gemini 2.5 Flash-Lite

Modello Leggero ed Economico

Gemini 2.5 Flash-Lite di Google 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 1.0M, velocità di 220 token/s, indice di intelligenza di 56/100 e ta

Intelligence Index56 / 100
Input Token:

$0.10 / 1M

Output Token:

$0.40 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

N/A

Differenze Chiave a Colpo d’Occhio

  • Gemini 2.5 Flash-Lite is 168.5x cheaper for API usage (input + output tokens combined).
  • Gemini 2.5 Flash-Lite has a larger context window (1M vs 200K tokens).
  • Gemini 2.5 Flash-Lite is faster at 220 tok/s vs 42 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureClaude Opus 4Gemini 2.5 Flash-Lite
Intelligence Index
Composite reasoning & knowledge score (0-100)
6156
Provider
AnthropicGoogle
Input Price
Cost per million input tokens
$15.00 / 1M$0.10 / 1M
Output Price
Cost per million output tokens
$75.00 / 1M$0.40 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$11.55 / 1M$0.08 / 1M
Context Window
Maximum input + output tokens
200K tokens~300 A4 pages of text1.05M tokens~1,573 A4 pages of text
Max Output Tokens
Per single request
32K33K
Throughput Speed
Tokens generated per second
42 tok/s220 tok/s
SWE-bench Verified
Real-world software engineering
72.5%N/A
GPQA Diamond
Graduate-level reasoning
73.8%N/A
Cached Input Price
Prompt caching discount per 1M tokens
$1.50 / 1M$0.03 / 1M

Chi vince in ogni categoria?

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
Gemini 2.5 Flash-Lite
168.5x cheaper monthly runtime
Speed
Gemini 2.5 Flash-Lite
+424% faster generation
Context
Gemini 2.5 Flash-Lite
1.05M tokens window

Punteggi Benchmark Verificati

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

Claude Opus 4Gemini 2.5 Flash-Lite
SWE-bench Verified (Autonomous Coding)

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

72.5%vsN/A
GPQA Diamond (Doctorate-Level Science & Math)

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

73.8%vsN/A
MMLU-Pro (Multi-task Language Understanding)

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

86.1%vs76.5%
LMSYS Chatbot Arena Elo

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

1368ptsvs1330pts
Terminal-Bench (Agentic Coding & Terminal Use)

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

43.2%vsN/A
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

42 tok/s vs220 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 Opus 41.80s
Gemini 2.5 Flash-Lite0.32s
Est. End-to-End Response (500 tokens)TTFT + generation time
Claude Opus 413.70s
Gemini 2.5 Flash-Lite2.59s

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 Opus 4 Monthly API Bill
$92.25 / month
$15/1M in · $75/1M out
Gemini 2.5 Flash-Lite Monthly API Bill
$0.55 / month
$0.1/1M in · $0.4/1M out
Gemini 2.5 Flash-Lite saves approximately $91.70 / month (99%) under this workload.168.5x Savings

Claude Opus 4 · Strengths & Key Advantages

  • Finestra di contesto da 200K con capacità massima di output fino a 32K token (SWE-bench Verified 72.5% · GPQA Diamond 73.8%)
  • Throughput elevato di 42 token/secondo con latenza al primo token (TTFT) di soli 1800 ms
  • Economia API competitiva ($15/$75 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 2.5 Flash-Lite · Strengths & Key Advantages

  • Finestra di contesto da 1.0M con capacità massima di output fino a 33K token (MMLU-Pro 76.5% · Arena Elo 1330)
  • Throughput elevato di 220 token/secondo con latenza al primo token (TTFT) di soli 320 ms
  • Economia API competitiva ($0.1/$0.4 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

Token Use & Task Economics

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

MetricClaude Opus 4Gemini 2.5 Flash-Lite
Cost per Task
Estimated USD to finish one task
$16.46$0.35
Output Tokens / Task
Tokens generated per task
72K12K
Reasoning Tokens / Task
Thinking tokens burned per task
37K4K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

FeatureClaude Opus 4Gemini 2.5 Flash-Lite
Official API Model ID (SDK)claude-opus-4-20250501models/gemini-2-5-flash-lite
API ProtocolAnthropic Messages API + AWS Bedrock + Vertex AIGoogle Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date2025-052025-06
Knowledge CutoffMarch 2025March 2025
ArchitectureDense Frontier Reasoning TransformerCompact multimodal transformer with lightweight thinking
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 800,000 – 2,000,000 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$1.5/1M cached read (90% off); 5-min default & 1-hour extended TTLImplicit + Explicit Context Caching at $0.025/1M 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)
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
Output Modalitiestexttext

Claude Opus 4 vs Gemini 2.5 Flash-Lite: Risposte Rapide (FAQ)

Which is more intelligent, Claude Opus 4 or Gemini 2.5 Flash-Lite?

Claude Opus 4 is more intelligent. It scores 61 compared with 56 on the composite Intelligence Index.

Which model is faster?

Gemini 2.5 Flash-Lite is faster, generating 220 tokens per second compared with 42 tokens per second.

Which model is cheaper to run?

Gemini 2.5 Flash-Lite is cheaper at $0.08 per 1M tokens blended, compared with $11.55 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Gemini 2.5 Flash-Lite has lower latency, with a time to first token of 0.32s compared with 1.80s.

Which model has a larger context window?

Gemini 2.5 Flash-Lite has a larger context window, supporting 1.05M tokens compared with 200K tokens.

Verdetto

Sia Claude Opus 4 (Ideale per il ragionamento logico profondo, la matematica avanzata e l’analisi scientifica, sistemi RAG aziendali e integrazioni API scalabili.) sia Gemini 2.5 Flash-Lite (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: Claude Opus 4 guida nei benchmark di ragionamento e programmazione, Gemini 2.5 Flash-Lite garantisce una generazione più rapida e Gemini 2.5 Flash-Lite offre il miglior rapporto qualità-prezzo per carichi API elevati.

Domande Frequenti (FAQ)

Quale modello è migliore per coding e ragionamento, Claude Opus 4 o Gemini 2.5 Flash-Lite?+

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

Qual è la differenza di prezzo API tra Claude Opus 4 e Gemini 2.5 Flash-Lite?+

Claude Opus 4 costa $15.00 / $75.00 per milione di token di input/output, mentre Gemini 2.5 Flash-Lite costa $0.10 / $0.40. Nel costo combinato, Gemini 2.5 Flash-Lite risulta più economico.

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

Claude Opus 4 supporta 200K token di contesto contro 1.05M token di Gemini 2.5 Flash-Lite, mentre Gemini 2.5 Flash-Lite 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).