o3-pro vs DeepSeek R1
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
o3-pro di OpenAI e DeepSeek R1 di DeepSeek sono due modelli di IA di riferimento. o3-pro offre una finestra di contesto di 200K token a $20.00/$80.00 per milione di token, mentre DeepSeek R1 mette a disposizione 128K token di contesto a $0.55/$2.19 per milione di token. Di seguito analizziamo benchmark, latenza e costi.
Cambia e Confronta Qualsiasi Modello
Select any AI models from our verified benchmark database to generate live side-by-side matrices.
o3-pro
Motore di Ragionamento Profondoo3-pro di OpenAI è un modello di IA progettato per il ragionamento logico profondo, la matematica avanzata e l’analisi scientifica, con finestra di contesto da 200K, velocità di 30 token/s, indice di intelligenza di 58/100 e tariffa di $20/
$20.00 / 1M
$80.00 / 1M
200K tokens
71.5%
DeepSeek R1
Ragionamento a Pesi ApertiDeepSeek R1 di DeepSeek è un modello di IA progettato per il ragionamento Chain-of-Thought a pesi aperti ad alta efficienza algoritmica, con finestra di contesto da 128K, velocità di 45 token/s, indice di intelligenza di 49/100 e tariffa di
$0.55 / 1M
$2.19 / 1M
128K tokens
49.2%
Differenze Chiave a Colpo d’Occhio
- DeepSeek R1 is 36.4x cheaper for API usage (input + output tokens combined).
- o3-pro has a larger context window (200K vs 128K tokens).
- DeepSeek R1 is faster at 45 tok/s vs 30 tok/s.
- o3-pro leads on SWE-bench coding (71.5% vs 49.2%).
| Feature | o3-pro | DeepSeek R1 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 58 | 49 |
Provider | OpenAI | DeepSeek |
Input Price Cost per million input tokens | $20.00 / 1M | $0.55 / 1M |
Output Price Cost per million output tokens | $80.00 / 1M | $2.19 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $15.50 / 1M | $0.43 / 1M |
Context Window Maximum input + output tokens | 200K tokens~300 A4 pages of text | 128K tokens~192 A4 pages of text |
Max Output Tokens Per single request | 100K | 8K |
Throughput Speed Tokens generated per second | 30 tok/s | 45 tok/s |
SWE-bench Verified Real-world software engineering | 71.5% | 49.2% |
GPQA Diamond Graduate-level reasoning | 79.5% | 71.5% |
Cached Input Price Prompt caching discount per 1M tokens | $5.00 / 1M | $0.14 / 1M |
Chi vince in ogni categoria?
At-a-glance decision frameworkPunteggi Benchmark Verificati
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Research-grade coding problems drawn from real scientific and numerical workloads.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
Latenza e Tempo di Risposta
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulatore Interattivo dei Costi Token
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
o3-pro · Strengths & Key Advantages
- Finestra di contesto da 200K con capacità massima di output fino a 100K token (SWE-bench Verified 71.5% · GPQA Diamond 79.5%)
- Throughput elevato di 30 token/secondo con latenza al primo token (TTFT) di soli 5200 ms
- Economia API competitiva ($20/$80 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
DeepSeek R1 · Strengths & Key Advantages
- Finestra di contesto da 128K con capacità massima di output fino a 8K token (SWE-bench Verified 49.2% · GPQA Diamond 71.5%)
- Throughput elevato di 45 token/secondo con latenza al primo token (TTFT) di soli 950 ms
- Pesi aperti (671B Total (37B )) 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
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | o3-pro | DeepSeek R1 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $11.68 | $0.65 |
Output Tokens / Task Tokens generated per task | 58K | 45K |
Reasoning Tokens / Task Thinking tokens burned per task | 38K | 25K |
Specifiche Tecniche
Architecture, release timeline, capabilities, and modalities.
| Feature | o3-pro | DeepSeek R1 |
|---|---|---|
| Official API Model ID (SDK) | o3-pro | deepseek-reasoner |
| API Protocol | OpenAI Responses API & Chat Completions v1 | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI |
| Release Date | 2025-06 | 2025-01 |
| Knowledge Cutoff | June 2024 | July 2024 |
| Architecture | High-effort reasoning transformer | Open-Weights Reasoning MoE |
| Parameters | Confidential | 671B Total (37B Active) |
| Enterprise Rate Limits (RPM / TPM) | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud |
| Long-Context Tier (>128K/200K) | Flat rate ($20/1M in) across full 200K window | Flat rate ($0.55/1M in) across full 128K window |
| Prompt Cache Policy & TTL | Automatic prefix caching at $5/1M (no extra cache-write fee) | 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 tool + Hosted Code Interpreter & File Search RAG | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools |
| Official Fine-Tuning Support | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) | 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) · 416 GB VRAM (4-bit Quantized) · 1443 GB VRAM (Native BF16) |
| Safety & Frontier Classification | OpenAI Preparedness Framework Audited & System Card Published | 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 |
o3-pro vs DeepSeek R1: Risposte Rapide (FAQ)
Which is more intelligent, o3-pro or DeepSeek R1?
o3-pro is more intelligent. It scores 58 compared with 49 on the composite Intelligence Index.
Which model is faster?
DeepSeek R1 is faster, generating 45 tokens per second compared with 30 tokens per second.
Which model is cheaper to run?
DeepSeek R1 is cheaper at $0.43 per 1M tokens blended, compared with $15.50 (7:2:1 cache:input:output ratio).
Which model has lower latency?
DeepSeek R1 has lower latency, with a time to first token of 0.95s compared with 5.20s.
Which model has a larger context window?
o3-pro has a larger context window, supporting 200K tokens compared with 128K tokens.
Verdetto
Sia o3-pro (Ideale per il ragionamento logico profondo, la matematica avanzata e l’analisi scientifica, sistemi RAG aziendali e integrazioni API scalabili.) sia DeepSeek R1 (Ideale per il ragionamento Chain-of-Thought a pesi aperti ad alta efficienza algoritmica, sistemi RAG aziendali e integrazioni API scalabili.) eccellono in produzione: o3-pro guida nei benchmark di ragionamento e programmazione, DeepSeek R1 garantisce una generazione più rapida e DeepSeek R1 offre il miglior rapporto qualità-prezzo per carichi API elevati.
Domande Frequenti (FAQ)
Quale modello è migliore per coding e ragionamento, o3-pro o DeepSeek R1?+
Nell’indice di intelligenza composito e nei benchmark di programmazione prevale o3-pro. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.
Qual è la differenza di prezzo API tra o3-pro e DeepSeek R1?+
o3-pro costa $20.00 / $80.00 per milione di token di input/output, mentre DeepSeek R1 costa $0.55 / $2.19. Nel costo combinato, DeepSeek R1 risulta più economico.
Quale modello ha la finestra di contesto più ampia e la velocità maggiore?+
o3-pro supporta 200K token di contesto contro 128K token di DeepSeek R1, mentre DeepSeek R1 offre una velocità di generazione superiore.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
Related reading
- Claude 3.7 Sonnet vs DeepSeek R1: Confronto Benchmark, Prezzi API e Velocità (2026)Confronta
- DeepSeek R1 vs OpenAI o1: Confronto Benchmark, Prezzi API e Velocità (2026)Confronta
- DeepSeek R1 vs o3-mini: Confronto Benchmark, Prezzi API e Velocità (2026)Confronta
- GPT-5 Chat vs o3-pro: Confronto Benchmark, Prezzi API e Velocità (2026)Confronta
- Grok 4.20 (Reasoning) vs DeepSeek R1: Confronto Benchmark, Prezzi API e Velocità (2026)Confronta
- o3-pro vs Claude Opus 5.5: Confronto Benchmark, Prezzi API e Velocità (2026)Confronta
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 OpenAI e DeepSeek, schede di sistema e benchmark indipendenti (2026).