Claude 3.7 Sonnet vs DeepSeek R1
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Claude 3.7 Sonnet dari Anthropic dan DeepSeek R1 dari DeepSeek adalah dua model AI unggulan. Claude 3.7 Sonnet menawarkan jendela konteks 200K token dengan harga $3.00/$15.00 per 1 juta token, sedangkan DeepSeek R1 menyediakan konteks 128K token seharga $0.55/$2.19 per 1 juta token. Berikut perbandingan lengkap benchmark, latensi, dan biayanya.
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Claude 3.7 Sonnet
Pemimpin Pemrograman & KodeClaude 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
$3.00 / 1M
$15.00 / 1M
200K tokens
70.3%
DeepSeek R1
Penalaran Bobot TerbukaDeepSeek R1 dari DeepSeek adalah model AI yang dirancang untuk penalaran rantai pemikiran (Chain-of-Thought) berbobot terbuka yang sangat efisien, menghadirkan jendela konteks 128K, kecepatan 45 token/detik, indeks kecerdasan 49/100, serta
$0.55 / 1M
$2.19 / 1M
128K tokens
49.2%
Perbedaan Utama Sekilas
- DeepSeek R1 is 6.1x cheaper for API usage (input + output tokens combined).
- Claude 3.7 Sonnet has a larger context window (200K vs 128K tokens).
- Claude 3.7 Sonnet is faster at 72 tok/s vs 45 tok/s.
- Claude 3.7 Sonnet leads on SWE-bench coding (70.3% vs 49.2%).
| Feature | Claude 3.7 Sonnet | DeepSeek R1 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 48 | 49 |
Provider | Anthropic | DeepSeek |
Input Price Cost per million input tokens | $3.00 / 1M | $0.55 / 1M |
Output Price Cost per million output tokens | $15.00 / 1M | $2.19 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $2.31 / 1M | $0.43 / 1M |
Context Window Maximum input + output tokens | 200K tokens~300 A4 pages of text | 128K tokens~192 A4 pages of text |
Max Output Tokens Per single request | 64K | 8K |
Throughput Speed Tokens generated per second | 72 tok/s | 45 tok/s |
SWE-bench Verified Real-world software engineering | 70.3% | 49.2% |
GPQA Diamond Graduate-level reasoning | 65% | 71.5% |
Cached Input Price Prompt caching discount per 1M tokens | $0.30 / 1M | $0.14 / 1M |
Siapa Unggul di Mana?
At-a-glance decision frameworkSkor Benchmark Terverifikasi
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Research-grade coding problems drawn from real scientific and numerical workloads.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
Latensi & Waktu Respons
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulator Biaya Token Interaktif
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
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
DeepSeek R1 · Strengths & Key Advantages
- Jendela konteks 128K dengan kapasitas output maksimum hingga 8K token (SWE-bench Verified 49.2% · GPQA Diamond 71.5%)
- Kecepatan generasi tinggi 45 token/detik dengan latensi token pertama (TTFT) hanya 950 ms
- Bobot terbuka (671B Total (37B )) yang siap di-hosting mandiri di GPU lokal atau cloud privat melalui vLLM dan Ollama
Considerations & Trade-offs
- Membutuhkan infrastruktur GPU dengan kapasitas VRAM yang memadai untuk eksekusi lokal presisi penuh
- Pada tugas pembuktian ilmiah tingkat ekstrem, model penalaran berat kelas atas memberikan kedalaman lebih tinggi
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Claude 3.7 Sonnet | DeepSeek R1 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $1.42 | $0.65 |
Output Tokens / Task Tokens generated per task | 41K | 45K |
Reasoning Tokens / Task Thinking tokens burned per task | 22K | 25K |
Spesifikasi Teknis
Architecture, release timeline, capabilities, and modalities.
| Feature | Claude 3.7 Sonnet | DeepSeek R1 |
|---|---|---|
| Official API Model ID (SDK) | claude-3-7-sonnet-20250201 | deepseek-reasoner |
| API Protocol | Anthropic Messages API + AWS Bedrock + Vertex AI | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI |
| Release Date | 2025-02 | 2025-01 |
| Knowledge Cutoff | November 2024 | July 2024 |
| Architecture | Hybrid Reasoning MoE | Open-Weights Reasoning MoE |
| Parameters | Confidential | 671B Total (37B Active) |
| Enterprise Rate Limits (RPM / TPM) | 4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 800,000 – 2,000,000 TPM | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud |
| Long-Context Tier (>128K/200K) | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens | Flat rate ($0.55/1M in) across full 128K window |
| Prompt Cache Policy & TTL | $0.3/1M cached read (90% off); 5-min default & 1-hour extended TTL | Automatic prefix caching at $0.14/1M (no extra cache-write fee) |
| Computer Use / GUI Agent | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) |
| MCP & Parallel Tool Calling | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Sandbox | Native Web Search Citations + Code Execution Tool + MCP Connectors | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools |
| Official Fine-Tuning Support | Custom Model Tuning via Amazon Bedrock & Prompt Distillation | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) |
| Multimodal Token Billing | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) | Text BPE (~4 chars/token) |
| Quantization & Min GPU VRAM | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 416 GB VRAM (4-bit Quantized) · 1443 GB VRAM (Native BF16) |
| Safety & Frontier Classification | Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated | Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma) |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control |
| Input Modalities | text, vision | text |
| Output Modalities | text | text |
Claude 3.7 Sonnet vs DeepSeek R1: Jawaban Cepat (FAQ)
Which is more intelligent, Claude 3.7 Sonnet or DeepSeek R1?
DeepSeek R1 is more intelligent. It scores 49 compared with 48 on the composite Intelligence Index.
Which model is faster?
Claude 3.7 Sonnet is faster, generating 72 tokens per second compared with 45 tokens per second.
Which model is cheaper to run?
DeepSeek R1 is cheaper at $0.43 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 0.95s.
Which model has a larger context window?
Claude 3.7 Sonnet has a larger context window, supporting 200K tokens compared with 128K tokens.
Kesimpulan
Baik 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.) maupun DeepSeek R1 (Sangat cocok untuk penalaran rantai pemikiran (Chain-of-Thought) berbobot terbuka yang sangat efisien, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: DeepSeek R1 unggul dalam penalaran dan pemrograman, Claude 3.7 Sonnet memberikan kecepatan generasi token lebih tinggi, dan DeepSeek R1 lebih hemat biaya untuk penggunaan API skala besar.
Pertanyaan Umum (FAQ)
Mana yang lebih baik untuk coding dan penalaran, Claude 3.7 Sonnet atau DeepSeek R1?+
Dalam indeks kecerdasan gabungan dan benchmark coding, DeepSeek R1 memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.
Berapa perbandingan harga API Claude 3.7 Sonnet vs DeepSeek R1?+
Claude 3.7 Sonnet mengenakan biaya $3.00 / $15.00 per 1M token input/output, sedangkan DeepSeek R1 sebesar $0.55 / $2.19. Secara keseluruhan, DeepSeek R1 lebih hemat biaya.
Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+
Claude 3.7 Sonnet mendukung konteks 200K token dibandingkan 128K token pada DeepSeek R1, sementara Claude 3.7 Sonnet unggul dalam kecepatan output token per detik.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
Related reading
- Claude 3.7 Sonnet vs GPT-4o: Perbandingan Benchmark, Harga API & Kecepatan (2026)Bandingkan
- Claude 3.7 Sonnet vs o3-mini: Perbandingan Benchmark, Harga API & Kecepatan (2026)Bandingkan
- Claude Sonnet 4 vs Claude 3.7 Sonnet: Perbandingan Benchmark, Harga API & Kecepatan (2026)Bandingkan
- DeepSeek R1 vs OpenAI o1: Perbandingan Benchmark, Harga API & Kecepatan (2026)Bandingkan
- DeepSeek R1 vs o3-mini: Perbandingan Benchmark, Harga API & Kecepatan (2026)Bandingkan
- Gemini 2.0 Pro vs Claude 3.7 Sonnet: Perbandingan Benchmark, Harga API & Kecepatan (2026)Bandingkan
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 Anthropic & DeepSeek serta evaluasi benchmark independen (2026).