Head-to-Head Model Comparison

DeepSeek V4 vs Claude Opus 5.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

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DeepSeekAnthropicopen-sourceflagship

Compare DeepSeek V4 by DeepSeek against Claude Opus 5.5 by Anthropic across real-world coding, reasoning, token economics, and latency.

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DeepSeek

DeepSeek V4

Açık Ağırlıklı Model

DeepSeek tarafından geliştirilen DeepSeek V4, 1M token bağlam penceresi ve 1M girdi başına $0.3, 1M çıktı başına $1.2 API fiyatlandırmasıyla yazılım geliştirme, analiz ve kurumsal otomasyon için tasarlanmıştır.

Intelligence Index56 / 100
Input Token:

$0.30 / 1M

Output Token:

$1.20 / 1M

Context Window:

1M tokens

SWE-bench Verified:

62.8%

Anthropic

Claude Opus 5.5

Derin Akıl Yürütme Modeli

Anthropic tarafından geliştirilen Claude Opus 5.5, 1M token bağlam penceresi ve 1M girdi başına $4.0, 1M çıktı başına $20.0 API fiyatlandırmasıyla yazılım geliştirme, analiz ve kurumsal otomasyon için tasarlanmıştır.

Intelligence Index94 / 100
Input Token:

$4.00 / 1M

Output Token:

$20.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

84.6%

Bir Bakışta Temel Farklar

  • DeepSeek V4 is 15.6x cheaper for API usage (input + output tokens combined).
  • Claude Opus 5.5 is faster at 78 tok/s vs 78 tok/s.
  • Claude Opus 5.5 leads on SWE-bench coding (84.6% vs 62.8%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureDeepSeek V4Claude Opus 5.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
5694
Provider
DeepSeekAnthropic
Input Price
Cost per million input tokens
$0.30 / 1M$4.00 / 1M
Output Price
Cost per million output tokens
$1.20 / 1M$20.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.20 / 1M$3.08 / 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
66K128K
Throughput Speed
Tokens generated per second
78 tok/s78 tok/s
SWE-bench Verified
Real-world software engineering
62.8%84.6%
GPQA Diamond
Graduate-level reasoning
78.4%82.3%
Cached Input Price
Prompt caching discount per 1M tokens
$0.03 / 1M$0.40 / 1M

Hangi Alanda Kim Kazanıyor?

At-a-glance decision framework
Coding
Claude Opus 5.5
+21.8% SWE-bench lead
Cost
DeepSeek V4
15.6x cheaper monthly runtime
Speed
Claude Opus 5.5
+0% faster generation
Context
Tied
1M tokens window

Doğrulanmış Benchmark Puanları

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

DeepSeek V4Claude Opus 5.5
SWE-bench Verified (Autonomous Coding)

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

62.8%vs84.6%
GPQA Diamond (Doctorate-Level Science & Math)

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

78.4%vs82.3%
MMLU-Pro (Multi-task Language Understanding)

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

87.5%vs91.5%
LMSYS Chatbot Arena Elo

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

1415ptsvs1507pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

14.5%vs19.8%
Terminal-Bench (Agentic Coding & Terminal Use)

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

42%vs66.4%
SciCode (Scientific Computing)

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

39.5%vs58.7%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

65%vs83.1%
AIME (Advanced Math Competition)

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

89%vs95.4%
Long-Context Reasoning

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

88%vs92.6%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

78 tok/s vs78 tok/s

Gecikme Süresi ve Yanıt Hızı

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
DeepSeek V40.60s
Claude Opus 5.51.40s
Est. End-to-End Response (500 tokens)TTFT + generation time
DeepSeek V47.01s
Claude Opus 5.57.81s

Gerçek Zamanlı Token Maliyet Simülatörü

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)
DeepSeek V4 Monthly API Bill
$1.57 / month
$0.3/1M in · $1.2/1M out
Claude Opus 5.5 Monthly API Bill
$24.60 / month
$4/1M in · $20/1M out
DeepSeek V4 saves approximately $23.03 / month (94%) under this workload.15.6x Savings

DeepSeek V4 · Strengths & Key Advantages

  • DeepSeek imzalı gelişmiş Next-Gen Sparse MoE with MLA mimarisi ve 1M token bağlam kapasitesi
  • Dengeli API maliyeti ($0.3/1M girdi, $1.2/1M çıktı) ve yüksek yanıt hızı
  • Kod üretimi, mantıksal çıkarım ve çok dilli görevlerde güçlü kıyaslama (benchmark) sonuçları
Considerations & Trade-offs
  • Çok uzun bağlamlı sorgularda token maliyetlerinin dikkatli yönetilmesi gerekir
  • Alan bazlı özel iş akışlarında en yüksek verim için doğru istem (prompt) tasarımı önerilir

Claude Opus 5.5 · Strengths & Key Advantages

  • Anthropic imzalı gelişmiş Extended Autonomous Hybrid Reasoning Transformer mimarisi ve 1M token bağlam kapasitesi
  • Dengeli API maliyeti ($4.0/1M girdi, $20.0/1M çıktı) ve yüksek yanıt hızı
  • Kod üretimi, mantıksal çıkarım ve çok dilli görevlerde güçlü kıyaslama (benchmark) sonuçları
Considerations & Trade-offs
  • Çok uzun bağlamlı sorgularda token maliyetlerinin dikkatli yönetilmesi gerekir
  • Alan bazlı özel iş akışlarında en yüksek verim için doğru istem (prompt) tasarımı önerilir

Token Use & Task Economics

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

MetricDeepSeek V4Claude Opus 5.5
Cost per Task
Estimated USD to finish one task
$0.38$3.85
Output Tokens / Task
Tokens generated per task
48K68K
Reasoning Tokens / Task
Thinking tokens burned per task
22K42K

Teknik Özellikler

Architecture, release timeline, capabilities, and modalities.

FeatureDeepSeek V4Claude Opus 5.5
Official API Model ID (SDK)deepseek-reasonerclaude-opus-5-5-20260901
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIAnthropic Messages API + AWS Bedrock + Vertex AI
Release Date2026-072026-09
Knowledge CutoffApril 2026June 2026
ArchitectureNext-Gen Sparse MoE with MLAExtended Autonomous Hybrid Reasoning Transformer
ParametersMoE (Colossal)Confidential
Enterprise Rate Limits (RPM / TPM)Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($0.3/1M in) across full 1000K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLAutomatic prefix caching at $0.03/1M (no extra cache-write fee)$0.4/1M cached read (90% off); 5-min default & 1-hour extended TTL
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)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 & SandboxSupported via external Tavily/Exa Search & E2B/Docker Sandbox toolsNative Web Search Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning SupportFull Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)Custom Model Tuning via Amazon Bedrock & Prompt Distillation
Multimodal Token BillingText BPE (~4 chars/token)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)
Quantization & Min GPU VRAMBF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 43 GB VRAM (4-bit Quantized) · 151 GB VRAM (Native BF16)Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier ClassificationOpen-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated
Enterprise Compliance (ZDR/HIPAA/SOC2)100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 ControlSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestexttext, vision
Output Modalitiestexttext

DeepSeek V4 vs Claude Opus 5.5: Hızlı Yanıtlar (SSS)

Which is more intelligent, DeepSeek V4 or Claude Opus 5.5?

Claude Opus 5.5 is more intelligent. It scores 94 compared with 56 on the composite Intelligence Index.

Which model is cheaper to run?

DeepSeek V4 is cheaper at $0.20 per 1M tokens blended, compared with $3.08 (7:2:1 cache:input:output ratio).

Which model has lower latency?

DeepSeek V4 has lower latency, with a time to first token of 0.60s compared with 1.40s.

Sonuç

Choose DeepSeek V4 for kurumsal otomasyon, yazılım mühendisliği, otonom yz ajanları ve deepseek tabanlı üretim sistemleri, or choose Claude Opus 5.5 for kurumsal otomasyon, yazılım mühendisliği, otonom yz ajanları ve anthropic tabanlı üretim sistemleri.

Sıkça Sorulan Sorular (SSS)

Which is cheaper: DeepSeek V4 or Claude Opus 5.5?+

DeepSeek V4 costs $0.3/1M input and $1.2/1M output tokens, while Claude Opus 5.5 costs $4/1M input and $20/1M output tokens.

Which model has a larger context window: DeepSeek V4 or Claude Opus 5.5?+

DeepSeek V4 supports 1M 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.

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.

Resmi kaynaklar: DeepSeek & Anthropic Official Documentation