DeepSeek V4 Pro vs GPT-6 Astra
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
DeepSeek V4 Pro di DeepSeek e GPT-6 Astra di OpenAI sono due modelli di IA di riferimento. DeepSeek V4 Pro offre una finestra di contesto di 1M token a $1.32/$3.96 per milione di token, mentre GPT-6 Astra mette a disposizione 272K token di contesto a $10.00/$50.00 per milione di token. Di seguito analizziamo benchmark, latenza e costi.
Cambia e Confronta Qualsiasi Modello
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DeepSeek V4 Pro
IA Agentica e Strumenti AutonomiDeepSeek V4 Pro di DeepSeek è un modello di IA progettato per i workflow agentici autonomi, il tool calling e l’automazione multi-step, con finestra di contesto da 1M, velocità di 80 token/s, indice di intelligenza di 53/100 e tariffa di $1
$1.32 / 1M
$3.96 / 1M
1M tokens
68.5%
GPT-6 Astra
Modello Vocale e Audio NativoGPT-6 Astra 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 272K, velocità di 100 token/s, indice di intelligenza di 96/100 e tariffa
$10.00 / 1M
$50.00 / 1M
272K tokens
82.4%
Differenze Chiave a Colpo d’Occhio
- DeepSeek V4 Pro is 10.7x cheaper for API usage (input + output tokens combined).
- DeepSeek V4 Pro has a larger context window (1M vs 272K tokens).
- GPT-6 Astra is faster at 100 tok/s vs 80 tok/s.
- GPT-6 Astra leads on SWE-bench coding (82.4% vs 68.5%).
| Feature | DeepSeek V4 Pro | GPT-6 Astra |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 53 | 96 |
Provider | DeepSeek | OpenAI |
Input Price Cost per million input tokens | $1.32 / 1M | $10.00 / 1M |
Output Price Cost per million output tokens | $3.96 / 1M | $50.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.76 / 1M | $7.70 / 1M |
Context Window Maximum input + output tokens | 1M tokens~1,500 A4 pages of text | 272K tokens~408 A4 pages of text |
Max Output Tokens Per single request | 128K | 128K |
Throughput Speed Tokens generated per second | 80 tok/s | 100 tok/s |
SWE-bench Verified Real-world software engineering | 68.5% | 82.4% |
GPQA Diamond Graduate-level reasoning | 81.2% | 80.9% |
Cached Input Price Prompt caching discount per 1M tokens | $0.14 / 1M | $1.00 / 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.
DeepSeek V4 Pro · Strengths & Key Advantages
- Finestra di contesto da 1M con capacità massima di output fino a 128K token (SWE-bench Verified 68.5% · GPQA Diamond 81.2%)
- Throughput elevato di 80 token/secondo con latenza al primo token (TTFT) di soli 580 ms
- Pesi aperti (MoE (Colossal)) 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-6 Astra · Strengths & Key Advantages
- Finestra di contesto da 272K con capacità massima di output fino a 128K token (SWE-bench Verified 82.4% · GPQA Diamond 80.9%)
- Throughput elevato di 100 token/secondo con latenza al primo token (TTFT) di soli 950 ms
- Economia API competitiva ($10/$50 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.
| Metric | DeepSeek V4 Pro | GPT-6 Astra |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.67 | $2.15 |
Output Tokens / Task Tokens generated per task | 52K | 58K |
Reasoning Tokens / Task Thinking tokens burned per task | 25K | 32K |
Specifiche Tecniche
Architecture, release timeline, capabilities, and modalities.
| Feature | DeepSeek V4 Pro | GPT-6 Astra |
|---|---|---|
| Official API Model ID (SDK) | deepseek-reasoner | gpt-6-astra |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2026-08 | 2026-09 |
| Knowledge Cutoff | May 2026 | June 2026 |
| Architecture | Next-Gen Sparse MoE with Agent RL Tuning | Omni-Adaptive Autoregressive with Dynamic CoT |
| Parameters | MoE (Colossal) | 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 ($1.32/1M in) across full 1000K window | Flat rate ($10/1M in) across full 272K window |
| Prompt Cache Policy & TTL | Automatic prefix caching at $0.14/1M (no extra cache-write fee) | Automatic prefix caching at $1/1M (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) · 43 GB VRAM (4-bit Quantized) · 151 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 V4 Pro vs GPT-6 Astra: Risposte Rapide (FAQ)
Which is more intelligent, DeepSeek V4 Pro or GPT-6 Astra?
GPT-6 Astra is more intelligent. It scores 96 compared with 53 on the composite Intelligence Index.
Which model is faster?
GPT-6 Astra is faster, generating 100 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 $7.70 (7:2:1 cache:input:output ratio).
Which model has lower latency?
DeepSeek V4 Pro has lower latency, with a time to first token of 0.58s compared with 0.95s.
Which model has a larger context window?
DeepSeek V4 Pro has a larger context window, supporting 1M tokens compared with 272K tokens.
Verdetto
Sia DeepSeek V4 Pro (Ideale per i workflow agentici autonomi, il tool calling e l’automazione multi-step, sistemi RAG aziendali e integrazioni API scalabili.) sia GPT-6 Astra (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: GPT-6 Astra guida nei benchmark di ragionamento e programmazione, GPT-6 Astra garantisce una generazione più rapida e DeepSeek V4 Pro offre il miglior rapporto qualità-prezzo per carichi API elevati.
Domande Frequenti (FAQ)
Quale modello è migliore per coding e ragionamento, DeepSeek V4 Pro o GPT-6 Astra?+
Nell’indice di intelligenza composito e nei benchmark di programmazione prevale GPT-6 Astra. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.
Qual è la differenza di prezzo API tra DeepSeek V4 Pro e GPT-6 Astra?+
DeepSeek V4 Pro costa $1.32 / $3.96 per milione di token di input/output, mentre GPT-6 Astra costa $10.00 / $50.00. Nel costo combinato, DeepSeek V4 Pro risulta più economico.
Quale modello ha la finestra di contesto più ampia e la velocità maggiore?+
DeepSeek V4 Pro supporta 1M token di contesto contro 272K token di GPT-6 Astra, mentre GPT-6 Astra 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
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- GPT-6.1 Sol vs GPT-6 Astra: 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 DeepSeek e OpenAI, schede di sistema e benchmark indipendenti (2026).