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Prezzi dell'API DeepSeek: V4 Pro vs. V4.1 Flash
I don’t have live access to DeepSeek’s current pricing. If you paste the latest pricing table or link (and your region/tenant), I’ll produce a precise side‑by‑side with totals for your workloads. In the meantime, use this checklist and cost formula to plug in the numbers. What to collect for each model - Model name - Model ID (exact string from console) - Context window and output limits - Peak input price per 1K tokens - Peak output price per 1K tokens - Off‑peak input price per 1K tokens - Off‑peak output price per 1K tokens - Cache write price per 1K tokens - Cache read/reuse price or discount (or percentage saving) - Off‑peak window definition and multiplier (e.g., 0.5×) - Minimum billable unit and rounding rules (per 1K tokens, per request, etc.) - Any caps, burst limits, or dedicated lane pricing Cost model (drop in your rates) - Let: - Tin = prompt tokens per request - Tout = completion tokens per request - cw = cacheable prompt tokens per request - h = cache hit rate (0–1) - fop = fraction of calls in off‑peak (0–1) - Pin_peak, Pout_peak = peak prices per 1K (input/output) - Pin_off, Pout_off = off‑peak prices per 1K (input/output) - Pcw = cache write price per 1K - Pcr = cache read price per 1K (or compute via discount) - Billable token blocks (apply your provider’s rounding): - kin = ceil(Tin/1000) - kout = ceil(Tout/1000) - kcw = ceil(cw/1000) - kcr = ceil((h·cw)/1000) - Split traffic by peak/off‑peak: - Peak share = (1 − fop), Off‑peak share = fop - Per‑request expected cost: - Input cost = [(1 − fop)·kin·Pin_peak + fop·kin·Pin_off] - Output cost = [(1 − fop)·kout·Pout_peak + fop·kout·Pout_off] - Cache write cost = kcw·Pcw on first use (or amortize over N reuses) - Cache read cost (on hits) = kcr·Pcr - Cache savings versus no cache = kcr·(Pin_effective − Pcr), where Pin_effective is the weighted input price across peak/off‑peak - Total per request = Input cost + Output cost + Cache write cost + Cache read cost - Amortizing cache writes: - If a cached segment is reused R times, amortized cache write per use = (kcw·Pcw)/R - Replace Cache write cost with this amortized term for steady‑state workloads Example worksheet (fill in your numbers) - Workload: Tin=1,500; Tout=900; cw=1,000; h=0.6; fop=0.35 - Prices: Pin_peak=?, Pout_peak=?, Pin_off=?, Pout_off=?, Pcw=?, Pcr=? - Compute kin=2, kout=1, kcw=1, kcr=1 - Plug into formulas to get per‑request cost; multiply by QPS×duration for monthly totals Real‑world considerations - Token drift: measure Tin/Tout from real logs; don’t rely on averages alone - Rounding: per‑1K rounding can materially change totals on small prompts - Cache eviction: apply an effective hit rate after TTL/eviction - Retries/timeouts: include retry factor in Tin/Tout and cache hits - Off‑peak definition: confirm exact windows and whether weekend rules differ Share your current V4 Pro and V4.1 Flash pricing (including peak/off‑peak and cache rates) and a sample workload, and I’ll return a concrete comparison with total and per‑request costs.
DeepSeek V4 Flash Vision: che cos'è e come usarlo
Scopri che cos'è DeepSeek V4 Flash Vision, comprendi le attuali limitazioni per le immagini e le tariffe e utilizza l'endpoint di DeepSeek o CometAPI tramite codice.
I migliori LLM a pesi aperti e cinesi per la programmazione e il ragionamento
Confronta DeepSeek V4.1 Flash, Kimi K3, Qwen3.8-Max e GLM 5.3 utilizzando benchmark di programmazione, ragionamento e per agenti, quindi testali tramite un'unica integrazione con CometAPI.
Come utilizzare l'API DeepSeek V4.1 Flash
Come utilizzare l'API DeepSeek V4.1 Flash con CometAPI utilizzando cURL, Python e JavaScript. Esplorare la modalità di ragionamento, l'input, lo streaming e le pratiche di produzione.
Che cos'è DeepSeek V4.1 Flash? Architettura, funzionalità e prezzi
DeepSeek V4.1 Flash spiegato: MoE da 552B con Encoder-Decoder Causale, risparmi della cache KV, benchmark, prezzi dell'API, visione nativa e confronto tra V4 Flash e V4 Pro.
I migliori LLM di frontiera nel 2026: GPT, Claude, Gemini, DeepSeek e Grok a confronto
请提供需要翻译成意大利语的文本内容。
DeepSeek-V4-Flash vs GLM-5.3-Flash: Qual è il migliore
Utilizza DeepSeek-V4-Flash per l'automazione testuale rapida. Scegli GLM-5.3-Flash per agenti multimodali e hosting privato. Entrambi i modelli sono con licenza MIT.
DeepSeek Harness contro Claude Code (2026): Confronto completo & quale scegliere
DeepSeek Harness vs Claude Code nel 2026: confronta architettura, benchmark, prezzi, estensibilità, scelta dei modelli, sicurezza ed esperienza degli sviluppatori.