Head-to-Head Model Comparison

Claude Sonnet 5.5 vs DeepSeek V4 Pro

Benchmarks, API Token Pricing, Context Window & Speed Comparison

GetInfoUs araştırma ekibi tarafından incelendiSon inceleme: October 2026Yayın ilkeleri

Paylaş

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Claude Sonnet 5.5Profile

DeepSeek V4 ProProfile

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Popular Matchups:

Anthropic

Claude Sonnet 5.5

Amiral Gemisi Öncü Model

Anthropic tarafından geliştirilen Claude Sonnet 5.5; öncü kurumsal akıl yürütme, yazılım geliştirme ve üretim ölçekli AI iş akışları için tasarlanmış olup 1M bağlam penceresi, 105 token/sn hız, 78/100 zeka indeksi ve 1M token başına $2/$10

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

Otonom Ajan ve Araç Modeli

DeepSeek tarafından geliştirilen DeepSeek V4 Pro; otonom ajan iş akışları, araç çağırma (tool calling) ve çok adımlı otomasyon için tasarlanmış olup 1M bağlam penceresi, 80 token/sn hız, 53/100 zeka indeksi ve 1M token başına $1.32/$3.96 fi

Intelligence Index53 / 100

Input Token:

$1.32 / 1M

Output Token:

$3.96 / 1M

Context Window:

1M tokens

SWE-bench Verified:

68.5%

Bir Bakışta Temel Farklar

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 →

Feature	Claude Sonnet 5.5	DeepSeek V4 Pro
Intelligence Index Composite reasoning & knowledge score (0-100)	78	53
Provider	Anthropic	DeepSeek
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 text	1M tokens~1,500 A4 pages of text
Max Output Tokens Per single request	128K	128K
Throughput Speed Tokens generated per second	105 tok/s	80 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

Hangi Alanda Kim Kazanıyor?

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

Doğrulanmış Benchmark Puanları

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

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

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

Gerçek Zamanlı Token Maliyet Simülatörü

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

Daily Input Tokens100K / day

10K500K1M

Daily Output Tokens30K / day

5K150K300K

Prompt Cache Hit Ratio50% 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 bağlam penceresi ve yanıt başına maksimum 128K çıktı tokenı kapasitesi (SWE-bench Verified 82.9% · GPQA Diamond 79.4%)
Sadece 550 ms ilk token gecikmesi (TTFT) ile saniyede 105 token yüksek üretim hızı
İstem önbellekleme (Prompt Caching), araç çağırma ve yapılandırılmış JSON çıktısını destekleyen rekabetçi API ekonomisi (1M token başına $2/$10 fiyatlandırma)

Considerations & Trade-offs

Kapalı ağırlıklı bulut modelidir; çevrimdışı yerel sunuculara indirilerek çalıştırılamaz
Yüksek hacimli üretim trafiğinde maliyetleri optimize etmek için Prompt Caching ve Batch API kullanımı önerilir

DeepSeek V4 Pro · Strengths & Key Advantages

1M bağlam penceresi ve yanıt başına maksimum 128K çıktı tokenı kapasitesi (SWE-bench Verified 68.5% · GPQA Diamond 81.2%)
Sadece 580 ms ilk token gecikmesi (TTFT) ile saniyede 80 token yüksek üretim hızı
vLLM, SGLang veya Ollama üzerinden yerel GPU sunucularında barındırılabilen açık ağırlıklı mimari (MoE (Colossal))

Considerations & Trade-offs

Tam hassasiyette yerel GPU çıkarımı için yeterli VRAM kapasitesine sahip donanım altyapısı gerektirir
Çok karmaşık akademik ve bilimsel çıkarımlarda üst düzey ağır akıl yürütme modelleri daha derin sonuçlar verebilir

Token Use & Task Economics

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

Metric	Claude Sonnet 5.5	DeepSeek V4 Pro
Cost per Task Estimated USD to finish one task	$3.29	$0.67
Output Tokens / Task Tokens generated per task	72K	52K
Reasoning Tokens / Task Thinking tokens burned per task	37K	25K

Teknik Özellikler

Architecture, release timeline, capabilities, and modalities.

Feature	Claude Sonnet 5.5	DeepSeek V4 Pro
Official API Model ID (SDK)	claude-sonnet-5-5-20260901	deepseek-reasoner
API Protocol	Anthropic Messages API + AWS Bedrock + Vertex AI	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date	2026-09	2026-08
Knowledge Cutoff	June 2026	May 2026
Architecture	Adaptive Frontier Multimodal Transformer	Next-Gen Sparse MoE with Agent RL Tuning
Parameters	Confidential	MoE (Colossal)
Enterprise Rate Limits (RPM / TPM)	4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 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 ($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 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) · 43 GB VRAM (4-bit Quantized) · 151 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 Sonnet 5.5 vs DeepSeek V4 Pro: Hızlı Yanıtlar (SSS)

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.

Sonuç

Hem Claude Sonnet 5.5 (öncü kurumsal akıl yürütme, yazılım geliştirme ve üretim ölçekli AI iş akışları, kurumsal RAG mimarileri ve ölçeklenebilir üretim API entegrasyonları için idealdir.) hem de DeepSeek V4 Pro (otonom ajan iş akışları, araç çağırma (tool calling) ve çok adımlı otomasyon, kurumsal RAG mimarileri ve ölçeklenebilir üretim API entegrasyonları için idealdir.) güçlü üretim seçenekleridir: Claude Sonnet 5.5 karmaşık akıl yürütme ve kodlama testlerinde öne çıkarken, Claude Sonnet 5.5 daha yüksek üretim hızı sağlar; DeepSeek V4 Pro ise yüksek hacimli API kullanımlarında daha ekonomiktir.

Sıkça Sorulan Sorular (SSS)

Kodlama ve akıl yürütme için Claude Sonnet 5.5 mi yoksa DeepSeek V4 Pro mi daha iyi?+

Bileşik zeka endeksi ve yazılım testlerinde Claude Sonnet 5.5 önde yer alıyor. Detaylı karşılaştırma için yukarıdaki SWE-bench ve GPQA tablolarına göz atabilirsiniz.

Claude Sonnet 5.5 ve DeepSeek V4 Pro API fiyatları nasıl karşılaştırılır?+

Claude Sonnet 5.5 1M giriş/çıkış tokeni başına $2.00 / $10.00 ücretlendirilirken, DeepSeek V4 Pro $1.32 / $3.96 seviyesindedir. Karma maliyette DeepSeek V4 Pro daha avantajlıdır.

Hangi modelin bağlam penceresi daha geniş ve hızı daha yüksek?+

Claude Sonnet 5.5 1M token bağlam penceresi sunarken DeepSeek V4 Pro 1M token kapasiteye sahiptir. Saniyedeki token üretim hızında ise Claude Sonnet 5.5 öndedir.

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 & Pricing Context Window AI Benchmarks Reasoning Models Tool Calling Model Context Protocol (MCP)

Claude Sonnet 5.5 vs DeepSeek V4 Pro

İstediğiniz Modelleri Seçin ve Karşılaştırın

Claude Sonnet 5.5

DeepSeek V4 Pro

Hangi Alanda Kim Kazanıyor?

Doğrulanmış Benchmark Puanları

Gecikme Süresi ve Yanıt Hızı

Gerçek Zamanlı Token Maliyet Simülatörü

Claude Sonnet 5.5 · Strengths & Key Advantages

Considerations & Trade-offs

DeepSeek V4 Pro · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Teknik Özellikler

Claude Sonnet 5.5 vs DeepSeek V4 Pro: Hızlı Yanıtlar (SSS)

Sonuç

Sıkça Sorulan Sorular (SSS)

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