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Head-to-Head Model Comparison

DeepSeek V3 vs GPT-4o

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Verificato dal team di ricerca di GetInfoUsUltima verifica: October 2026Politica editoriale
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
DeepSeek V3 vs GPT-4o: Benchmarks, Pricing & Speed Comparison

DeepSeek V3 di DeepSeek e GPT-4o di OpenAI sono due modelli di IA di riferimento. DeepSeek V3 offre una finestra di contesto di 128K token a $0.27/$1.10 per milione di token, mentre GPT-4o mette a disposizione 128K token di contesto a $2.50/$10.00 per milione di token. Di seguito analizziamo benchmark, latenza e costi.

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Popular Matchups:DeepSeek V3 vs GPT-4o
DeepSeek

DeepSeek V3

Modello Base a Pesi Aperti

DeepSeek V3 di DeepSeek è un modello di IA progettato per il self-hosting su infrastruttura privata, il fine-tuning e la piena sovranità dei dati, con finestra di contesto da 128K, velocità di 60 token/s, indice di intelligenza di 44/100 e

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

Modello Vocale e Audio Nativo

GPT-4o di OpenAI è un modello di IA progettato per la sintesi vocale naturale, l’elaborazione audio in tempo reale e la trascrizione, con finestra di contesto da 128K, velocità di 105 token/s, indice di intelligenza di 41/100 e tariffa di $

Intelligence Index41 / 100
Input Token:

$2.50 / 1M

Output Token:

$10.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

38.8%

Differenze Chiave a Colpo d’Occhio

  • 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 →
FeatureDeepSeek V3GPT-4o
Intelligence Index
Composite reasoning & knowledge score (0-100)
4441
Provider
DeepSeekOpenAI
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 text128K tokens~192 A4 pages of text
Max Output Tokens
Per single request
8K16K
Throughput Speed
Tokens generated per second
60 tok/s105 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

Chi vince in ogni categoria?

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

Punteggi Benchmark Verificati

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

Latenza e Tempo di Risposta

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

Simulatore Interattivo dei Costi Token

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 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

  • Finestra di contesto da 128K con capacità massima di output fino a 8K token (SWE-bench Verified 49.2% · GPQA Diamond 59.1%)
  • Throughput elevato di 60 token/secondo con latenza al primo token (TTFT) di soli 680 ms
  • Pesi aperti (671B) pronti per il self-hosting locale o su cloud privato tramite vLLM, SGLang o Ollama
Considerations & Trade-offs
  • Richiede server GPU dedicati con sufficiente memoria VRAM per l’esecuzione locale a piena precisione
  • Nelle dimostrazioni scientifiche più estreme, i modelli di ragionamento pesante dedicati offrono maggiore profondità

GPT-4o · Strengths & Key Advantages

  • Finestra di contesto da 128K con capacità massima di output fino a 16K token (SWE-bench Verified 38.8% · GPQA Diamond 53.6%)
  • Throughput elevato di 105 token/secondo con latenza al primo token (TTFT) di soli 410 ms
  • Economia API competitiva ($2.5/$10 per 1M di token) con supporto per prompt caching, tool calling e output JSON strutturati
Considerations & Trade-offs
  • Modello cloud proprietario chiuso; non consente il download locale dei pesi per l’esecuzione offline
  • Per volumi di traffico elevati in produzione si consiglia di attivare il prompt caching e la Batch API

Token Use & Task Economics

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

MetricDeepSeek V3GPT-4o
Cost per Task
Estimated USD to finish one task
$0.14$0.68
Output Tokens / Task
Tokens generated per task
45K24K
Reasoning Tokens / Task
Thinking tokens burned per task
0K0K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

FeatureDeepSeek V3GPT-4o
Official API Model ID (SDK)deepseek-chatgpt-4o
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIOpenAI Responses API & Chat Completions v1
Release Date2024-122024-05
Knowledge CutoffJuly 2024October 2023
Architecture671B Mixture-of-Experts (37B active)Omni-Multimodal Dense
Parameters671BConfidential
Enterprise Rate Limits (RPM / TPM)Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud10,000 – 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 windowFlat rate ($2.5/1M in) across full 128K window
Prompt Cache Policy & TTLAutomatic 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 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 tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning SupportFull Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
Multimodal Token BillingText BPE (~4 chars/token)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec)
Quantization & Min GPU VRAMBF16 / 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 ClassificationOpen-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 ControlSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestexttext, vision, audio
Output Modalitiestexttext, audio

DeepSeek V3 vs GPT-4o: Risposte Rapide (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.

Verdetto

Sia DeepSeek V3 (Ideale per il self-hosting su infrastruttura privata, il fine-tuning e la piena sovranità dei dati, sistemi RAG aziendali e integrazioni API scalabili.) sia GPT-4o (Ideale per la sintesi vocale naturale, l’elaborazione audio in tempo reale e la trascrizione, sistemi RAG aziendali e integrazioni API scalabili.) eccellono in produzione: DeepSeek V3 guida nei benchmark di ragionamento e programmazione, GPT-4o garantisce una generazione più rapida e DeepSeek V3 offre il miglior rapporto qualità-prezzo per carichi API elevati.

Domande Frequenti (FAQ)

Quale modello è migliore per coding e ragionamento, DeepSeek V3 o GPT-4o?+

Nell’indice di intelligenza composito e nei benchmark di programmazione prevale DeepSeek V3. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.

Qual è la differenza di prezzo API tra DeepSeek V3 e GPT-4o?+

DeepSeek V3 costa $0.27 / $1.10 per milione di token di input/output, mentre GPT-4o costa $2.50 / $10.00. Nel costo combinato, DeepSeek V3 risulta più economico.

Quale modello ha la finestra di contesto più ampia e la velocità maggiore?+

DeepSeek V3 supporta 128K token di contesto contro 128K token di GPT-4o, mentre GPT-4o offre una velocità di generazione superiore.

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.

Fonti ufficiali: Documentazione API ufficiale di DeepSeek e OpenAI, schede di sistema e benchmark indipendenti (2026).