Head-to-Head Model Comparison

DeepSeek V4 vs DeepSeek Reasoner

Benchmarks, API Token Pricing, Context Window & Speed Comparison

GetInfoUs araştırma ekibi tarafından incelendiSon inceleme: October 2026Yayın ilkeleri

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DeepSeek V4Profile

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DeepSeek

DeepSeek V4

Açık Ağırlıklı Temel Model

DeepSeek tarafından geliştirilen DeepSeek V4; özel sunucuda kendi kendine barındırma (self-hosting), ince ayar ve tam veri egemenliği için tasarlanmış olup 1M bağlam penceresi, 78 token/sn hız, 56/100 zeka indeksi ve 1M token başına $0.3/$1

Intelligence Index56 / 100

Input Token:

$0.30 / 1M

Output Token:

$1.20 / 1M

Context Window:

1M tokens

SWE-bench Verified:

62.8%

DeepSeek

DeepSeek Reasoner

Açık Ağırlıklı Akıl Yürütme

DeepSeek tarafından geliştirilen DeepSeek Reasoner; yüksek verimli açık ağırlıklı düşünce zinciri (Chain-of-Thought) akıl yürütme için tasarlanmış olup 1M bağlam penceresi, 52 token/sn hız, 54/100 zeka indeksi ve 1M token başına $0.28/$0.42

Intelligence Index54 / 100

Input Token:

$0.28 / 1M

Output Token:

$0.42 / 1M

Context Window:

1M tokens

SWE-bench Verified:

56.5%

Bir Bakışta Temel Farklar

DeepSeek Reasoner is 1.9x cheaper for API usage (input + output tokens combined).
DeepSeek V4 is faster at 78 tok/s vs 52 tok/s.
DeepSeek V4 leads on SWE-bench coding (62.8% vs 56.5%).

Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →

Feature	DeepSeek V4	DeepSeek Reasoner
Intelligence Index Composite reasoning & knowledge score (0-100)	56	54
Provider	DeepSeek	DeepSeek
Input Price Cost per million input tokens	$0.30 / 1M	$0.28 / 1M
Output Price Cost per million output tokens	$1.20 / 1M	$0.42 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.20 / 1M	$0.12 / 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	66K	33K
Throughput Speed Tokens generated per second	78 tok/s	52 tok/s
SWE-bench Verified Real-world software engineering	62.8%	56.5%
GPQA Diamond Graduate-level reasoning	78.4%	76.5%
Cached Input Price Prompt caching discount per 1M tokens	$0.03 / 1M	$0.03 / 1M

Hangi Alanda Kim Kazanıyor?

At-a-glance decision framework

Coding

DeepSeek V4

+6.3% SWE-bench lead

Cost

DeepSeek Reasoner

1.9x cheaper monthly runtime

Speed

DeepSeek V4

+50% faster generation

Context

Tied

1M tokens window

Doğrulanmış Benchmark Puanları

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

DeepSeek V4DeepSeek Reasoner

SWE-bench Verified (Autonomous Coding)

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

62.8%vs56.5%

GPQA Diamond (Doctorate-Level Science & Math)

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

78.4%vs76.5%

MMLU-Pro (Multi-task Language Understanding)

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

87.5%vs86.2%

LMSYS Chatbot Arena Elo

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

1415ptsvs1368pts

Humanity's Last Exam (Frontier Expert Knowledge)

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

14.5%vs13.5%

Terminal-Bench (Agentic Coding & Terminal Use)

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

42%vs37.5%

SciCode (Scientific Computing)

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

39.5%vs35%

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

65%vs58.5%

AIME (Advanced Math Competition)

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

89%vs87.5%

Long-Context Reasoning

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

88%vs85%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

78 tok/s vs52 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

DeepSeek Reasoner0.82s

Est. End-to-End Response (500 tokens)TTFT + generation time

DeepSeek V47.01s

DeepSeek Reasoner10.44s

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)

DeepSeek V4 Monthly API Bill

$1.57 / month

$0.3/1M in · $1.2/1M out

DeepSeek Reasoner Monthly API Bill

$0.84 / month

$0.28/1M in · $0.42/1M out

DeepSeek Reasoner saves approximately $0.73 / month (47%) under this workload.1.9x Savings

DeepSeek V4 · Strengths & Key Advantages

1M bağlam penceresi ve yanıt başına maksimum 66K çıktı tokenı kapasitesi (SWE-bench Verified 62.8% · GPQA Diamond 78.4%)
Sadece 600 ms ilk token gecikmesi (TTFT) ile saniyede 78 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

DeepSeek Reasoner · Strengths & Key Advantages

1M bağlam penceresi ve yanıt başına maksimum 33K çıktı tokenı kapasitesi (SWE-bench Verified 56.5% · GPQA Diamond 76.5%)
Sadece 820 ms ilk token gecikmesi (TTFT) ile saniyede 52 token yüksek üretim hızı
vLLM, SGLang veya Ollama üzerinden yerel GPU sunucularında barındırılabilen açık ağırlıklı mimari (671B Total (37B ))

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	DeepSeek V4	DeepSeek Reasoner
Cost per Task Estimated USD to finish one task	$0.38	$0.22
Output Tokens / Task Tokens generated per task	48K	45K
Reasoning Tokens / Task Thinking tokens burned per task	22K	26K

Teknik Özellikler

Architecture, release timeline, capabilities, and modalities.

Feature	DeepSeek V4	DeepSeek Reasoner
Official API Model ID (SDK)	deepseek-reasoner	deepseek-reasoner
API Protocol	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date	2026-07	2025-12
Knowledge Cutoff	April 2026	September 2025
Architecture	Next-Gen Sparse MoE with MLA	Reinforcement-Learned Reasoning MoE
Parameters	MoE (Colossal)	671B Total (37B Active)
Enterprise Rate Limits (RPM / TPM)	Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud	Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
Long-Context Tier (>128K/200K)	Flat rate ($0.3/1M in) across full 1000K window	Flat rate ($0.28/1M in) across full 1000K window
Prompt Cache Policy & TTL	Automatic prefix caching at $0.03/1M (no extra cache-write fee)	Automatic prefix caching at $0.028/1M (no extra cache-write fee)
Computer Use / GUI Agent	API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)	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	Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools	Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning Support	Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)	Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)
Multimodal Token Billing	Text BPE (~4 chars/token)	Text BPE (~4 chars/token)
Quantization & Min GPU VRAM	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 43 GB VRAM (4-bit Quantized) · 151 GB VRAM (Native BF16)	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	Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)	Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)
Enterprise Compliance (ZDR/HIPAA/SOC2)	100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control	100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalities	text	text
Output Modalities	text	text

DeepSeek V4 vs DeepSeek Reasoner: Hızlı Yanıtlar (SSS)

Which is more intelligent, DeepSeek V4 or DeepSeek Reasoner?

DeepSeek V4 is more intelligent. It scores 56 compared with 54 on the composite Intelligence Index.

Which model is faster?

DeepSeek V4 is faster, generating 78 tokens per second compared with 52 tokens per second.

Which model is cheaper to run?

DeepSeek Reasoner is cheaper at $0.12 per 1M tokens blended, compared with $0.20 (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 0.82s.

Sonuç

Hem DeepSeek V4 (özel sunucuda kendi kendine barındırma (self-hosting), ince ayar ve tam veri egemenliği, kurumsal RAG mimarileri ve ölçeklenebilir üretim API entegrasyonları için idealdir.) hem de DeepSeek Reasoner (yüksek verimli açık ağırlıklı düşünce zinciri (Chain-of-Thought) akıl yürütme, kurumsal RAG mimarileri ve ölçeklenebilir üretim API entegrasyonları için idealdir.) güçlü üretim seçenekleridir: DeepSeek V4 karmaşık akıl yürütme ve kodlama testlerinde öne çıkarken, DeepSeek V4 daha yüksek üretim hızı sağlar; DeepSeek Reasoner ise yüksek hacimli API kullanımlarında daha ekonomiktir.

Sıkça Sorulan Sorular (SSS)

Kodlama ve akıl yürütme için DeepSeek V4 mi yoksa DeepSeek Reasoner mi daha iyi?+

Bileşik zeka endeksi ve yazılım testlerinde DeepSeek V4 önde yer alıyor. Detaylı karşılaştırma için yukarıdaki SWE-bench ve GPQA tablolarına göz atabilirsiniz.

DeepSeek V4 ve DeepSeek Reasoner API fiyatları nasıl karşılaştırılır?+

DeepSeek V4 1M giriş/çıkış tokeni başına $0.30 / $1.20 ücretlendirilirken, DeepSeek Reasoner $0.28 / $0.42 seviyesindedir. Karma maliyette DeepSeek Reasoner daha avantajlıdır.

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

DeepSeek V4 1M token bağlam penceresi sunarken DeepSeek Reasoner 1M token kapasiteye sahiptir. Saniyedeki token üretim hızında ise DeepSeek V4 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)

DeepSeek V4 vs DeepSeek Reasoner

İstediğiniz Modelleri Seçin ve Karşılaştırın

DeepSeek V4

DeepSeek Reasoner

Hangi Alanda Kim Kazanıyor?

Doğrulanmış Benchmark Puanları

Gecikme Süresi ve Yanıt Hızı

Gerçek Zamanlı Token Maliyet Simülatörü

DeepSeek V4 · Strengths & Key Advantages

Considerations & Trade-offs

DeepSeek Reasoner · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Teknik Özellikler

DeepSeek V4 vs DeepSeek Reasoner: Hızlı Yanıtlar (SSS)

Sonuç

Sıkça Sorulan Sorular (SSS)

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