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Head-to-Head Model Comparison

Claude Sonnet 5.5 vs DeepSeek V4 Pro

Benchmarks, API Token Pricing, Context Window & Speed Comparison

GetInfoUs 연구팀 검토 완료최종 검토일: October 2026편집 정책
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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 DeepSeek V4 Pro: Benchmarks, Pricing & Speed Comparison

Anthropic의 Claude Sonnet 5.5와 DeepSeek의 DeepSeek V4 Pro는 현재 가장 주목받는 AI 모델입니다. Claude Sonnet 5.5는 1M 토큰 컨텍스트 윈도우와 100만 토큰당 $2.00/$10.00(입력/출력)의 요금을 제공하며, DeepSeek V4 Pro는 1M 토큰 컨텍스트와 $1.32/$3.96의 요금을 제공합니다. 아래에서 벤치마크, 지연 시간 및 비용을 상세히 비교해 보세요.

1:1 모델 맞대결 비교 (VS)

원하는 AI 모델 선택 및 실시간 비교

Select any AI models from our verified benchmark database to generate live side-by-side matrices.

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Anthropic

Claude Sonnet 5.5

플래그십 프론티어 모델

Anthropic의 Claude Sonnet 5.5 모델은 최첨단 엔터프라이즈 추론, 소프트웨어 개발 및 핵심 프로덕션 워크로드에 최적화된 AI 모델로, 1M 컨텍스트 윈도우, 초당 105 토큰의 생성 속도, 종합 지능 지수 78/100점(1M 토큰당 입력 $2 / 출력 $10)을 제공합니다.

Intelligence Index78 / 100
Input Token:

$2.00 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

82.9%

DeepSeek

DeepSeek V4 Pro

자율 에이전트 및 도구 호출 특화

DeepSeek의 DeepSeek V4 Pro 모델은 자율 에이전트 워크플로우, 도구 호출(Tool Calling) 및 다단계 업무 자동화에 최적화된 AI 모델로, 1M 컨텍스트 윈도우, 초당 80 토큰의 생성 속도, 종합 지능 지수 53/100점(1M 토큰당 입력 $1.32 / 출력 $3.96)을 제공합니다.

Intelligence Index53 / 100
Input Token:

$1.32 / 1M

Output Token:

$3.96 / 1M

Context Window:

1M tokens

SWE-bench Verified:

68.5%

한눈에 보는 핵심 차이점

  • DeepSeek V4 Pro is 2.1x cheaper for API usage (input + output tokens combined).
  • Claude Sonnet 5.5 is faster at 105 tok/s vs 80 tok/s.
  • Claude Sonnet 5.5 leads on SWE-bench coding (82.9% vs 68.5%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureClaude Sonnet 5.5DeepSeek V4 Pro
Intelligence Index
Composite reasoning & knowledge score (0-100)
7853
Provider
AnthropicDeepSeek
Input Price
Cost per million input tokens
$2.00 / 1M$1.32 / 1M
Output Price
Cost per million output tokens
$10.00 / 1M$3.96 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$1.54 / 1M$0.76 / 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
128K128K
Throughput Speed
Tokens generated per second
105 tok/s80 tok/s
SWE-bench Verified
Real-world software engineering
82.9%68.5%
GPQA Diamond
Graduate-level reasoning
79.4%81.2%
Cached Input Price
Prompt caching discount per 1M tokens
$0.20 / 1M$0.14 / 1M

부문별 우위 모델

At-a-glance decision framework
Coding
Claude Sonnet 5.5
+14.4% SWE-bench lead
Cost
DeepSeek V4 Pro
2.1x cheaper monthly runtime
Speed
Claude Sonnet 5.5
+31% faster generation
Context
Tied
1M tokens window

검증된 벤치마크 점수 비교

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

Claude Sonnet 5.5DeepSeek V4 Pro
SWE-bench Verified (Autonomous Coding)

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

82.9%vs68.5%
GPQA Diamond (Doctorate-Level Science & Math)

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

79.4%vs81.2%
MMLU-Pro (Multi-task Language Understanding)

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

90.1%vs88.9%
LMSYS Chatbot Arena Elo

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

1490ptsvs1438pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

N/Avs15.6%
Terminal-Bench (Agentic Coding & Terminal Use)

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

58.9%vs46.5%
SciCode (Scientific Computing)

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

N/Avs43%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs70.2%
AIME (Advanced Math Competition)

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

N/Avs91%
Long-Context Reasoning

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

N/Avs90%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

105 tok/s vs80 tok/s

지연 시간(Latency) 및 응답 속도

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
DeepSeek V4 Pro0.58s
Est. End-to-End Response (500 tokens)TTFT + generation time
Claude Sonnet 5.55.31s
DeepSeek V4 Pro6.83s

실시간 API 토큰 비용 시뮬레이터

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
DeepSeek V4 Pro Monthly API Bill
$5.75 / month
$1.32/1M in · $3.96/1M out
DeepSeek V4 Pro saves approximately $6.55 / month (53%) under this workload.2.1x Savings

Claude Sonnet 5.5 · Strengths & Key Advantages

  • 1M 컨텍스트 윈도우 및 최대 128K 출력 토큰 생성 지원 (SWE-bench Verified 82.9% · GPQA Diamond 79.4%)
  • 초당 105 토큰의 빠른 처리 속도와 550ms에 불과한 첫 토큰 지연 시간(TTFT)
  • 합리적인 API 요금 체계(1M 토큰당 입력 $2 / 출력 $10)와 프롬프트 캐싱, 함수 호출 및 정형화된 JSON 출력 완벽 지원
Considerations & Trade-offs
  • 독점 클라우드 전용 모델로 로컬 오프라인 서버에 가중치를 다운로드하여 실행할 수 없습니다
  • 대규모 프로덕션 호출 환경에서는 비용 절감을 위해 프롬프트 캐싱과 배치 API(Batch API) 활용이 권장됩니다

DeepSeek V4 Pro · Strengths & Key Advantages

  • 1M 컨텍스트 윈도우 및 최대 128K 출력 토큰 생성 지원 (SWE-bench Verified 68.5% · GPQA Diamond 81.2%)
  • 초당 80 토큰의 빠른 처리 속도와 580ms에 불과한 첫 토큰 지연 시간(TTFT)
  • 오픈 웨이트 아키텍처 (MoE (Colossal))를 통해 vLLM, SGLang, Ollama 기반 자체 GPU 서버 구축 및 파인튜닝 가능
Considerations & Trade-offs
  • 비양자화 전체 정밀도로 로컬 서버에서 구동하려면 충분한 GPU VRAM 용량이 필요합니다
  • 초고난도 학술 연구 및 수학 증명 과제에서는 상위 대형 추론 특화 모델이 더 깊은 분석을 제공할 수 있습니다

Token Use & Task Economics

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

MetricClaude Sonnet 5.5DeepSeek V4 Pro
Cost per Task
Estimated USD to finish one task
$3.29$0.67
Output Tokens / Task
Tokens generated per task
72K52K
Reasoning Tokens / Task
Thinking tokens burned per task
37K25K

기술 사양 (Specifications)

Architecture, release timeline, capabilities, and modalities.

FeatureClaude Sonnet 5.5DeepSeek V4 Pro
Official API Model ID (SDK)claude-sonnet-5-5-20260901deepseek-reasoner
API ProtocolAnthropic Messages API + AWS Bedrock + Vertex AIOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date2026-092026-08
Knowledge CutoffJune 2026May 2026
ArchitectureAdaptive Frontier Multimodal TransformerNext-Gen Sparse MoE with Agent RL Tuning
ParametersConfidentialMoE (Colossal)
Enterprise Rate Limits (RPM / TPM)4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPMUnlimited (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 tokensFlat rate ($1.32/1M in) across full 1000K window
Prompt Cache Policy & TTL$0.2/1M cached read (90% off); 5-min default & 1-hour extended TTLAutomatic prefix caching at $0.14/1M (no extra cache-write fee)
Computer Use / GUI AgentSupported (Screen coordinate grounding, browser & desktop GUI action loops)API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)
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 ConnectorsSupported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning SupportCustom Model Tuning via Amazon Bedrock & Prompt DistillationFull Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)
Multimodal Token BillingText BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)Text BPE (~4 chars/token)
Quantization & Min GPU VRAMCloud-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) · 43 GB VRAM (4-bit Quantized) · 151 GB VRAM (Native BF16)
Safety & Frontier ClassificationAnthropic RSP ASL-2 / ASL-3 Constitutional Safety EvaluatedOpen-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 Tier100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalitiestext, visiontext
Output Modalitiestexttext

Claude Sonnet 5.5 vs DeepSeek V4 Pro: 핵심 요약 문답 (FAQ)

Which is more intelligent, Claude Sonnet 5.5 or DeepSeek V4 Pro?

Claude Sonnet 5.5 is more intelligent. It scores 78 compared with 53 on the composite Intelligence Index.

Which model is faster?

Claude Sonnet 5.5 is faster, generating 105 tokens per second compared with 80 tokens per second.

Which model is cheaper to run?

DeepSeek V4 Pro is cheaper at $0.76 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 0.58s.

종합 평가

Claude Sonnet 5.5(최첨단 엔터프라이즈 추론, 소프트웨어 개발 및 핵심 프로덕션 워크로드, 엔터프라이즈 RAG 지식베이스 및 대규모 프로덕션 API 연동에 최적.)와 DeepSeek V4 Pro(자율 에이전트 워크플로우, 도구 호출(Tool Calling) 및 다단계 업무 자동화, 엔터프라이즈 RAG 지식베이스 및 대규모 프로덕션 API 연동에 최적.) 모두 뛰어난 성능을 자랑합니다. 고난도 추론과 코딩 벤치마크에서는 Claude Sonnet 5.5가 앞서며, 토큰 생성 속도에서는 Claude Sonnet 5.5가 빠르고, 대규모 API 운영 비용 면에서는 DeepSeek V4 Pro가 더 경제적입니다.

자주 묻는 질문 (FAQ)

코딩과 복잡한 추론에는 Claude Sonnet 5.5와 DeepSeek V4 Pro 중 어느 모델이 더 나은가요?+

종합 지능 지수 및 코딩 벤치마크에서는 Claude Sonnet 5.5가 우위를 보입니다. 상단의 SWE-bench 및 GPQA 점수를 함께 확인해 보세요.

Claude Sonnet 5.5와 DeepSeek V4 Pro의 API 요금 차이는 얼마인가요?+

Claude Sonnet 5.5는 100만 토큰당 입력 $2.00 / 출력 $10.00이며, DeepSeek V4 Pro는 입력 $1.32 / 출력 $3.96입니다. 혼합 비용 기준으로는 DeepSeek V4 Pro가 더 저렴합니다.

어느 모델이 더 큰 컨텍스트 윈도우와 빠른 속도를 제공하나요?+

컨텍스트 길이는 Claude Sonnet 5.5가 1M 토큰, DeepSeek V4 Pro가 1M 토큰를 지원하며, 출력 속도 면에서는 Claude Sonnet 5.5가 더 빠릅니다.

AI Terminology & Guide
Explore Glossary →

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

Tokens & PricingContext WindowAI BenchmarksReasoning ModelsTool CallingModel Context Protocol (MCP)

Related reading

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.

공식 출처: Anthropic 및 DeepSeek 공식 API 문서, 시스템 카드 및 독립 벤치마크 평가 (2026).