Head-to-Head Model Comparison

Gemini 2.0 Pro vs Claude Opus 5.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Vérifié par l’équipe de recherche de GetInfoUsDernière révision : October 2026Politique éditoriale
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Compare Gemini 2.0 Pro by Google against Claude Opus 5.5 by Anthropic across real-world coding, reasoning, token economics, and latency.

Comparaison Face-à-Face (VS)

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Popular Matchups:
Google

Gemini 2.0 Pro

Titan du contexte 2M

de Google de référence modèle de pointe développé pour complexe codage, scientifique discovery, et industry-leading 2-millions-token multimodal document compréhension.

Intelligence Index52 / 100
Input Token:

$1.25 / 1M

Output Token:

$5.00 / 1M

Context Window:

2M tokens

SWE-bench Verified:

63.8%

Anthropic

Claude Opus 5.5

Titan d'intelligence de pointe

d'Anthropic pinnacle modèle de pointe conçu pour à long terme agentic ingénierie logicielle, dense multimodal document synthèse, et autonome recherche flux de travail.

Intelligence Index94 / 100
Input Token:

$4.00 / 1M

Output Token:

$20.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

84.6%

Différences Clés en un Coup d’Œil

  • Gemini 2.0 Pro is 3.6x cheaper for API usage (input + output tokens combined).
  • Gemini 2.0 Pro has a larger context window (2M vs 1M tokens).
  • Gemini 2.0 Pro is faster at 95 tok/s vs 78 tok/s.
  • Claude Opus 5.5 leads on SWE-bench coding (84.6% vs 63.8%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
CaractéristiqueGemini 2.0 ProClaude Opus 5.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
5294
Provider
GoogleAnthropic
Input Price
Cost per million input tokens
$1.25 / 1M$4.00 / 1M
Output Price
Cost per million output tokens
$5.00 / 1M$20.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.97 / 1M$3.08 / 1M
Context Window
Maximum input + output tokens
2M tokens~3,000 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
8K128K
Throughput Speed
Tokens generated per second
95 tok/s78 tok/s
SWE-bench Verified
Real-world software engineering
63.8%84.6%
GPQA Diamond
Graduate-level reasoning
71.5%82.3%
Cached Input Price
Prompt caching discount per 1M tokens
$0.31 / 1M$0.40 / 1M

Qui gagne où ?

At-a-glance decision framework
Code
Claude Opus 5.5
+20.8% SWE-bench lead
Coût
Gemini 2.0 Pro
3.6x cheaper monthly runtime
Vitesse
Gemini 2.0 Pro
+22% faster generation
Contexte
Gemini 2.0 Pro
2M tokens window

Scores de Benchmarks Vérifiés

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

Gemini 2.0 ProClaude Opus 5.5
SWE-bench Verified (Autonomous Coding)

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

63.8%vs84.6%
GPQA Diamond (Doctorate-Level Science & Math)

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

71.5%vs82.3%
MMLU-Pro (Multi-task Language Understanding)

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

79.8%vs91.5%
LMSYS Chatbot Arena Elo

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

1330ptsvs1507pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

11.4%vs19.8%
Terminal-Bench (Agentic Coding & Terminal Use)

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

42.1%vs66.4%
SciCode (Scientific Computing)

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

38.3%vs58.7%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

65.6%vs83.1%
AIME (Advanced Math Competition)

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

82.2%vs95.4%
Long-Context Reasoning

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

71.8%vs92.6%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

95 tok/s vs78 tok/s

Latence et Temps de Réponse

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
Gemini 2.0 Pro0.62s
Claude Opus 5.51.40s
Est. End-to-End Response (500 tokens)TTFT + generation time
Gemini 2.0 Pro5.88s
Claude Opus 5.57.81s

Simulateur Interactif de Coût de Tokens

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)
Gemini 2.0 Pro Monthly API Bill
$6.84 / month
$1.25/1M in · $5/1M out
Claude Opus 5.5 Monthly API Bill
$24.60 / month
$4/1M in · $20/1M out
Gemini 2.0 Pro saves approximately $17.76 / month (72%) under this workload.3.6x Savings

Gemini 2.0 Pro · Strengths & Key Advantages

  • sans égal 2,000,000 token fenêtre de contexte (peut ingest hours de vidéo ou entire codebases)
  • de pointe codage performances (63.8% sur SWE-bench Verified)
  • natif multimodal raisonnement à travers texte, code, élevé-res images, audio, et vidéo
  • 75% discount sur cached tokens avec de Google contexte caching API
Considerations & Trade-offs
  • Maximum sortie tokens currently capped à 8K par response
  • nécessite élevé prompt cache reuse pour optimal coût efficacité sur 1M+ token inputs

Claude Opus 5.5 · Strengths & Key Advantages

  • inégalé autonome multi-étapes codage agentique et refactorisation
  • Flawless multidocument raisonnement sur 1M token contexte avec no long-prompt surcharge
  • le plus élevé Artificial analyse intelligence Index ever measured (58/100), leading SWE-bench Pro à 89.9%
  • Precise outil exécution avec robust error-recovery boucles
Considerations & Trade-offs
  • Premium sortie tarification ($20.00/M) plus heavy raisonnement-token usage (~119K sortie tokens par index tâche) keeps long agentic fonctionne expensive
  • long pensée times à maximum effort peut push un unique hard agentic tâche toward ~$13

Token Use & Task Economics

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

MetricGemini 2.0 ProClaude Opus 5.5
Cost per Task
Estimated USD to finish one task
$1.59$3.85
Output Tokens / Task
Tokens generated per task
60K68K
Reasoning Tokens / Task
Thinking tokens burned per task
33K42K

Spécifications Techniques

Architecture, release timeline, capabilities, and modalities.

CaractéristiqueGemini 2.0 ProClaude Opus 5.5
Official API Model ID (SDK)models/gemini-2-proclaude-opus-5-5-20260901
API ProtocolGoogle Gemini API (generateContent) + OpenAI-Compatible SDKAnthropic Messages API + AWS Bedrock + Vertex AI
Release Date2025-022026-09
Knowledge CutoffJanuary 2025June 2026
ArchitectureMultimodal Deep Reasoning Sparse MoEExtended Autonomous Hybrid Reasoning Transformer
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 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 & TTLImplicit + Explicit Context Caching at $0.31/1M with configurable TTL$0.4/1M cached read (90% off); 5-min default & 1-hour extended 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 & SandboxBuilt-in Google Search Grounding + Managed Python Code Execution SandboxNative Web Search Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning SupportVertex AI Supervised Adapter Tuning & Context DistillationCustom Model Tuning via Amazon Bedrock & Prompt Distillation
Multimodal Token BillingText BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec)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 ClassificationGoogle DeepMind Frontier Safety Framework VerifiedAnthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated
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, vision, audio, videotext, vision
Output Modalitiestexttext

Gemini 2.0 Pro vs Claude Opus 5.5: Réponses Rapides (FAQ)

Which is more intelligent, Gemini 2.0 Pro or Claude Opus 5.5?

Claude Opus 5.5 is more intelligent. It scores 94 compared with 52 on the composite Intelligence Index.

Which model is faster?

Gemini 2.0 Pro is faster, generating 95 tokens per second compared with 78 tokens per second.

Which model is cheaper to run?

Gemini 2.0 Pro is cheaper at $0.97 per 1M tokens blended, compared with $3.08 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Gemini 2.0 Pro has lower latency, with a time to first token of 0.62s compared with 1.40s.

Which model has a larger context window?

Gemini 2.0 Pro has a larger context window, supporting 2M tokens compared with 1M tokens.

Verdict

Choose Gemini 2.0 Pro for monolithic dépôt refactorisation, massif juridique/scientifique document corpora, et vidéo analyse, or choose Claude Opus 5.5 for grand-échelle logiciel development agents, d'entreprise codebases, et mission critique scientifique synthèse.

Questions fréquentes

Which is cheaper: Gemini 2.0 Pro or Claude Opus 5.5?+

Gemini 2.0 Pro costs $1.25/1M input and $5/1M output tokens, while Claude Opus 5.5 costs $4/1M input and $20/1M output tokens.

Which model has a larger context window: Gemini 2.0 Pro or Claude Opus 5.5?+

Gemini 2.0 Pro supports 2M tokens whereas Claude Opus 5.5 supports 1M tokens.

AI Terminology & Guide
Explore Glossary →

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

Les scores de benchmarks, tarifs par token et limites évoluent rapidement. Vérifiez toujours les spécifications actuelles sur la documentation officielle du fournisseur.

Sources: Google & Anthropic Official Documentation