Head-to-Head Model Comparison

Gemini 2.0 Pro vs Claude 3.7 Sonnet

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Ditinjau oleh tim riset GetInfoUsPeninjauan terakhir: October 2026Kebijakan editorial
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Gemini 2.0 Pro vs Claude 3.7 Sonnet: Benchmarks, Pricing & Speed Comparison

Gemini 2.0 Pro dari Google dan Claude 3.7 Sonnet dari Anthropic adalah dua model AI unggulan. Gemini 2.0 Pro menawarkan jendela konteks 2M token dengan harga $1.25/$5.00 per 1 juta token, sedangkan Claude 3.7 Sonnet menyediakan konteks 200K token seharga $3.00/$15.00 per 1 juta token. Berikut perbandingan lengkap benchmark, latensi, dan biayanya.

Perbandingan Langsung (VS)

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Gemini 2.0 Pro

Model Unggulan Garis Depan

Gemini 2.0 Pro dari Google adalah model AI yang dirancang untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, menghadirkan jendela konteks 2M, kecepatan 95 token/detik, indeks kecerdasan 52/100, serta tarif

Intelligence Index52 / 100
Input Token:

$1.25 / 1M

Output Token:

$5.00 / 1M

Context Window:

2M tokens

SWE-bench Verified:

63.8%

Anthropic

Claude 3.7 Sonnet

Pemimpin Pemrograman & Kode

Claude 3.7 Sonnet dari Anthropic adalah model AI yang dirancang untuk rekayasa perangkat lunak otonom, refactoring multi-file, dan debugging mendalam, menghadirkan jendela konteks 200K, kecepatan 72 token/detik, indeks kecerdasan 48/100, se

Intelligence Index48 / 100
Input Token:

$3.00 / 1M

Output Token:

$15.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

70.3%

Perbedaan Utama Sekilas

  • Gemini 2.0 Pro is 2.7x cheaper for API usage (input + output tokens combined).
  • Gemini 2.0 Pro has a larger context window (2M vs 200K tokens).
  • Gemini 2.0 Pro is faster at 95 tok/s vs 72 tok/s.
  • Claude 3.7 Sonnet leads on SWE-bench coding (70.3% vs 63.8%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGemini 2.0 ProClaude 3.7 Sonnet
Intelligence Index
Composite reasoning & knowledge score (0-100)
5248
Provider
GoogleAnthropic
Input Price
Cost per million input tokens
$1.25 / 1M$3.00 / 1M
Output Price
Cost per million output tokens
$5.00 / 1M$15.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.97 / 1M$2.31 / 1M
Context Window
Maximum input + output tokens
2M tokens~3,000 A4 pages of text200K tokens~300 A4 pages of text
Max Output Tokens
Per single request
8K64K
Throughput Speed
Tokens generated per second
95 tok/s72 tok/s
SWE-bench Verified
Real-world software engineering
63.8%70.3%
GPQA Diamond
Graduate-level reasoning
71.5%65%
Cached Input Price
Prompt caching discount per 1M tokens
$0.31 / 1M$0.30 / 1M

Siapa Unggul di Mana?

At-a-glance decision framework
Coding
Claude 3.7 Sonnet
+6.5% SWE-bench lead
Cost
Gemini 2.0 Pro
2.7x cheaper monthly runtime
Speed
Gemini 2.0 Pro
+32% faster generation
Context
Gemini 2.0 Pro
2M tokens window

Skor Benchmark Terverifikasi

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

Gemini 2.0 ProClaude 3.7 Sonnet
SWE-bench Verified (Autonomous Coding)

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

63.8%vs70.3%
GPQA Diamond (Doctorate-Level Science & Math)

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

71.5%vs65%
MMLU-Pro (Multi-task Language Understanding)

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

79.8%vs78.2%
LMSYS Chatbot Arena Elo

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

1330ptsvs1335pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

11.4%vs8.9%
Terminal-Bench (Agentic Coding & Terminal Use)

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

42.1%vs35.2%
SciCode (Scientific Computing)

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

38.3%vs40.1%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

65.6%vs64.8%
AIME (Advanced Math Competition)

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

82.2%vs61.3%
Long-Context Reasoning

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

71.8%vs71.5%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

95 tok/s vs72 tok/s

Latensi & Waktu Respons

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 3.7 Sonnet0.52s
Est. End-to-End Response (500 tokens)TTFT + generation time
Gemini 2.0 Pro5.88s
Claude 3.7 Sonnet7.46s

Simulator Biaya Token Interaktif

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 3.7 Sonnet Monthly API Bill
$18.45 / month
$3/1M in · $15/1M out
Gemini 2.0 Pro saves approximately $11.61 / month (63%) under this workload.2.7x Savings

Gemini 2.0 Pro · Strengths & Key Advantages

  • Jendela konteks 2M dengan kapasitas output maksimum hingga 8K token (SWE-bench Verified 63.8% · GPQA Diamond 71.5%)
  • Kecepatan generasi tinggi 95 token/detik dengan latensi token pertama (TTFT) hanya 620 ms
  • Skema harga API kompetitif (tarif $1.25/$5 per 1M token) dengan dukungan cache prompt dan output JSON terstruktur
Considerations & Trade-offs
  • Model cloud proprietari tertutup; bobot model tidak dapat diunduh untuk penggunaan lokal offline
  • Pada tugas pembuktian ilmiah tingkat ekstrem, model penalaran berat kelas atas memberikan kedalaman lebih tinggi

Claude 3.7 Sonnet · Strengths & Key Advantages

  • Jendela konteks 200K dengan kapasitas output maksimum hingga 64K token (SWE-bench Verified 70.3% · GPQA Diamond 65%)
  • Kecepatan generasi tinggi 72 token/detik dengan latensi token pertama (TTFT) hanya 520 ms
  • Skema harga API kompetitif (tarif $3/$15 per 1M token) dengan dukungan cache prompt dan output JSON terstruktur
Considerations & Trade-offs
  • Model cloud proprietari tertutup; bobot model tidak dapat diunduh untuk penggunaan lokal offline
  • Untuk trafik produksi skala besar, disarankan mengaktifkan fitur Prompt Caching dan Batch API guna menghemat biaya

Token Use & Task Economics

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

MetricGemini 2.0 ProClaude 3.7 Sonnet
Cost per Task
Estimated USD to finish one task
$1.59$1.42
Output Tokens / Task
Tokens generated per task
60K41K
Reasoning Tokens / Task
Thinking tokens burned per task
33K22K

Spesifikasi Teknis

Architecture, release timeline, capabilities, and modalities.

FeatureGemini 2.0 ProClaude 3.7 Sonnet
Official API Model ID (SDK)models/gemini-2-proclaude-3-7-sonnet-20250201
API ProtocolGoogle Gemini API (generateContent) + OpenAI-Compatible SDKAnthropic Messages API + AWS Bedrock + Vertex AI
Release Date2025-022025-02
Knowledge CutoffJanuary 2025November 2024
ArchitectureMultimodal Deep Reasoning Sparse MoEHybrid Reasoning MoE
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) · 800,000 – 2,000,000 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$0.3/1M 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 3.7 Sonnet: Jawaban Cepat (FAQ)

Which is more intelligent, Gemini 2.0 Pro or Claude 3.7 Sonnet?

Gemini 2.0 Pro is more intelligent. It scores 52 compared with 48 on the composite Intelligence Index.

Which model is faster?

Gemini 2.0 Pro is faster, generating 95 tokens per second compared with 72 tokens per second.

Which model is cheaper to run?

Gemini 2.0 Pro is cheaper at $0.97 per 1M tokens blended, compared with $2.31 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Claude 3.7 Sonnet has lower latency, with a time to first token of 0.52s compared with 0.62s.

Which model has a larger context window?

Gemini 2.0 Pro has a larger context window, supporting 2M tokens compared with 200K tokens.

Kesimpulan

Baik Gemini 2.0 Pro (Sangat cocok untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun Claude 3.7 Sonnet (Sangat cocok untuk rekayasa perangkat lunak otonom, refactoring multi-file, dan debugging mendalam, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: Gemini 2.0 Pro unggul dalam penalaran dan pemrograman, Gemini 2.0 Pro memberikan kecepatan generasi token lebih tinggi, dan Gemini 2.0 Pro lebih hemat biaya untuk penggunaan API skala besar.

Pertanyaan Umum (FAQ)

Mana yang lebih baik untuk coding dan penalaran, Gemini 2.0 Pro atau Claude 3.7 Sonnet?+

Dalam indeks kecerdasan gabungan dan benchmark coding, Gemini 2.0 Pro memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.

Berapa perbandingan harga API Gemini 2.0 Pro vs Claude 3.7 Sonnet?+

Gemini 2.0 Pro mengenakan biaya $1.25 / $5.00 per 1M token input/output, sedangkan Claude 3.7 Sonnet sebesar $3.00 / $15.00. Secara keseluruhan, Gemini 2.0 Pro lebih hemat biaya.

Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+

Gemini 2.0 Pro mendukung konteks 2M token dibandingkan 200K token pada Claude 3.7 Sonnet, sementara Gemini 2.0 Pro unggul dalam kecepatan output token per detik.

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.

Sumber resmi: Dokumentasi API resmi Google & Anthropic serta evaluasi benchmark independen (2026).