Head-to-Head Model Comparison

DeepSeek V3 vs GPT-4o

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Ditinjau oleh tim riset GetInfoUsPeninjauan terakhir: October 2026Kebijakan editorial

Ganti & Bandingkan Model Apa Saja

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

DeepSeek V3Profile

GPT-4oProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:DeepSeek V3 vs GPT-4o

DeepSeek

DeepSeek V3

Model Dasar Bobot Terbuka

DeepSeek V3 dari DeepSeek adalah model AI yang dirancang untuk self-hosting di server pribadi, fine-tuning, dan kedaulatan data penuh, menghadirkan jendela konteks 128K, kecepatan 60 token/detik, indeks kecerdasan 44/100, serta tarif $0.27/

Intelligence Index44 / 100

Input Token:

$0.27 / 1M

Output Token:

$1.10 / 1M

Context Window:

128K tokens

SWE-bench Verified:

49.2%

OpenAI

GPT-4o

Model Suara & Audio Asli

GPT-4o dari OpenAI adalah model AI yang dirancang untuk sintesis suara alami, pemrosesan audio real-time, dan transkripsi ucapan, menghadirkan jendela konteks 128K, kecepatan 105 token/detik, indeks kecerdasan 41/100, serta tarif $2.5/$10 p

Intelligence Index41 / 100

Input Token:

$2.50 / 1M

Output Token:

$10.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

38.8%

Perbedaan Utama Sekilas

DeepSeek V3 is 9.8x cheaper for API usage (input + output tokens combined).
GPT-4o is faster at 105 tok/s vs 60 tok/s.
DeepSeek V3 leads on SWE-bench coding (49.2% vs 38.8%).

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

Feature	DeepSeek V3	GPT-4o
Intelligence Index Composite reasoning & knowledge score (0-100)	44	41
Provider	DeepSeek	OpenAI
Input Price Cost per million input tokens	$0.27 / 1M	$2.50 / 1M
Output Price Cost per million output tokens	$1.10 / 1M	$10.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.21 / 1M	$2.38 / 1M
Context Window Maximum input + output tokens	128K tokens~192 A4 pages of text	128K tokens~192 A4 pages of text
Max Output Tokens Per single request	8K	16K
Throughput Speed Tokens generated per second	60 tok/s	105 tok/s
SWE-bench Verified Real-world software engineering	49.2%	38.8%
GPQA Diamond Graduate-level reasoning	59.1%	53.6%
Cached Input Price Prompt caching discount per 1M tokens	$0.07 / 1M	$1.25 / 1M

Siapa Unggul di Mana?

At-a-glance decision framework

Coding

DeepSeek V3

+10.4% SWE-bench lead

Cost

DeepSeek V3

9.8x cheaper monthly runtime

Speed

GPT-4o

+75% faster generation

Context

Tied

128K tokens window

Skor Benchmark Terverifikasi

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

DeepSeek V3GPT-4o

SWE-bench Verified (Autonomous Coding)

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

49.2%vs38.8%

GPQA Diamond (Doctorate-Level Science & Math)

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

59.1%vs53.6%

MMLU-Pro (Multi-task Language Understanding)

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

75.9%vs72.6%

LMSYS Chatbot Arena Elo

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

1300ptsvs1286pts

Humanity's Last Exam (Frontier Expert Knowledge)

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

9.5%vs4.1%

Terminal-Bench (Agentic Coding & Terminal Use)

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

32.5%vs18.5%

SciCode (Scientific Computing)

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

29.5%vs27.3%

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

51.7%vs43.9%

AIME (Advanced Math Competition)

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

68%vs29.7%

Long-Context Reasoning

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

68.3%vs58.2%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

60 tok/s vs105 tok/s

Latensi & Waktu Respons

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 V30.68s

GPT-4o0.41s

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

DeepSeek V39.01s

GPT-4o5.17s

Simulator Biaya Token Interaktif

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 V3 Monthly API Bill

$1.50 / month

$0.27/1M in · $1.1/1M out

GPT-4o Monthly API Bill

$14.63 / month

$2.5/1M in · $10/1M out

DeepSeek V3 saves approximately $13.13 / month (90%) under this workload.9.8x Savings

DeepSeek V3 · Strengths & Key Advantages

Jendela konteks 128K dengan kapasitas output maksimum hingga 8K token (SWE-bench Verified 49.2% · GPQA Diamond 59.1%)
Kecepatan generasi tinggi 60 token/detik dengan latensi token pertama (TTFT) hanya 680 ms
Bobot terbuka (671B) 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

GPT-4o · Strengths & Key Advantages

Jendela konteks 128K dengan kapasitas output maksimum hingga 16K token (SWE-bench Verified 38.8% · GPQA Diamond 53.6%)
Kecepatan generasi tinggi 105 token/detik dengan latensi token pertama (TTFT) hanya 410 ms
Skema harga API kompetitif (tarif $2.5/$10 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

Token Use & Task Economics

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

Metric	DeepSeek V3	GPT-4o
Cost per Task Estimated USD to finish one task	$0.14	$0.68
Output Tokens / Task Tokens generated per task	45K	24K
Reasoning Tokens / Task Thinking tokens burned per task	0K	0K

Spesifikasi Teknis

Architecture, release timeline, capabilities, and modalities.

Feature	DeepSeek V3	GPT-4o
Official API Model ID (SDK)	deepseek-chat	gpt-4o
API Protocol	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI	OpenAI Responses API & Chat Completions v1
Release Date	2024-12	2024-05
Knowledge Cutoff	July 2024	October 2023
Architecture	671B Mixture-of-Experts (37B active)	Omni-Multimodal Dense
Parameters	671B	Confidential
Enterprise Rate Limits (RPM / TPM)	Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud	10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)	Flat rate ($0.27/1M in) across full 128K window	Flat rate ($2.5/1M in) across full 128K window
Prompt Cache Policy & TTL	Automatic prefix caching at $0.07/1M (no extra cache-write fee)	Automatic prefix caching at $1.25/1M (no extra cache-write fee)
Computer Use / GUI Agent	API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)	Supported (Screen coordinate grounding, browser & desktop GUI action loops)
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	Native Web Search tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning Support	Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)	Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
Multimodal Token Billing	Text BPE (~4 chars/token)	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec)
Quantization & Min GPU VRAM	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 416 GB VRAM (4-bit Quantized) · 1443 GB VRAM (Native BF16)	Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier Classification	Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)	OpenAI Preparedness Framework Audited & System Card Published
Enterprise Compliance (ZDR/HIPAA/SOC2)	100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control	SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalities	text	text, vision, audio
Output Modalities	text	text, audio

DeepSeek V3 vs GPT-4o: Jawaban Cepat (FAQ)

Which is more intelligent, DeepSeek V3 or GPT-4o?

DeepSeek V3 is more intelligent. It scores 44 compared with 41 on the composite Intelligence Index.

Which model is faster?

GPT-4o is faster, generating 105 tokens per second compared with 60 tokens per second.

Which model is cheaper to run?

DeepSeek V3 is cheaper at $0.21 per 1M tokens blended, compared with $2.38 (7:2:1 cache:input:output ratio).

Which model has lower latency?

GPT-4o has lower latency, with a time to first token of 0.41s compared with 0.68s.

Kesimpulan

Baik DeepSeek V3 (Sangat cocok untuk self-hosting di server pribadi, fine-tuning, dan kedaulatan data penuh, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun GPT-4o (Sangat cocok untuk sintesis suara alami, pemrosesan audio real-time, dan transkripsi ucapan, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: DeepSeek V3 unggul dalam penalaran dan pemrograman, GPT-4o memberikan kecepatan generasi token lebih tinggi, dan DeepSeek V3 lebih hemat biaya untuk penggunaan API skala besar.

Pertanyaan Umum (FAQ)

Mana yang lebih baik untuk coding dan penalaran, DeepSeek V3 atau GPT-4o?+

Dalam indeks kecerdasan gabungan dan benchmark coding, DeepSeek V3 memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.

Berapa perbandingan harga API DeepSeek V3 vs GPT-4o?+

DeepSeek V3 mengenakan biaya $0.27 / $1.10 per 1M token input/output, sedangkan GPT-4o sebesar $2.50 / $10.00. Secara keseluruhan, DeepSeek V3 lebih hemat biaya.

Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+

DeepSeek V3 mendukung konteks 128K token dibandingkan 128K token pada GPT-4o, sementara GPT-4o unggul dalam kecepatan output token per detik.

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 V3 vs GPT-4o

Ganti & Bandingkan Model Apa Saja

DeepSeek V3

GPT-4o

Siapa Unggul di Mana?

Skor Benchmark Terverifikasi

Latensi & Waktu Respons

Simulator Biaya Token Interaktif

DeepSeek V3 · Strengths & Key Advantages

Considerations & Trade-offs

GPT-4o · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Spesifikasi Teknis

DeepSeek V3 vs GPT-4o: Jawaban Cepat (FAQ)

Kesimpulan

Pertanyaan Umum (FAQ)

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