Friday, 7 August 2026 | Updating Daily AI insight, written for builders

DeepSeek V4-Pro

DeepSeek V4-Pro — Specifiche

SviluppatoreDeepSeek
TipoLLM (MoE)
ModalitàTesto → Testo
Parametri1,6 trilioni totali / ~49 miliardi attivi (MoE)
Finestra contestuale1 milione
Output massimo384K
LicenzaMIT (open)
Pesi aperti
Pubblicato2026-04
Prezzo dell’input0,435 $ /1 milione
Prezzo dell’output0,87 $ /1 milione
Provider APIDeepSeek, OpenRouter

Esegui localmente

VRAM (4-bit)~800 GB
GPU minima richiestaServer multi-GPU (es. 8× H100 80 GB)

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What is DeepSeek V4-Pro?

DeepSeek V4-Pro is the company’s open flagship: a 1.6-trillion-parameter mixture-of-experts
activating around 49B parameters per token, with a 1M-token context window and MIT-licensed
weights. The API speaks both OpenAI and Anthropic request formats, which makes it unusually
easy to drop into an existing codebase — often a base-URL and key change rather than a
rewrite.

Pricing is $0.435 in / $0.87 out per million tokens, which blends to roughly $0.52 — around
a twentieth of frontier pricing for a model that holds its own on general reasoning. That
ratio, not the parameter count, is why V4-Pro matters. The dual-format API compatibility
compounds it: the switching cost that normally protects incumbent providers largely
disappears, so V4-Pro is a genuine option for teams that would otherwise never evaluate a
Chinese lab’s model. Self-hosting is a data-centre exercise — roughly 800 GB of VRAM at
4-bit, so eight H100 80GBs or more — meaning the open licence here buys auditability and
provider portability rather than a realistic on-premises deployment for most organisations.

DeepSeek V4-Pro pricing: API cost per 1M tokens

Input (per ogni milione di token)$0.435
Output (per ogni milione di token)$0.870
Output/input ratio
Blended (4:1 in:out)$0.522 per 1M tokens

What DeepSeek V4-Pro costs per month

Real monthly spend at a 4:1 input-to-output mix — the ratio a typical chat or RAG workload actually produces.

Carico di lavoroToken/meseCost / month
Progetto secondario1 milione in ingresso / 0,25 milioni in uscita$0.65
Piccolo team20 milioni in ingresso / 5 milioni in uscita$13
Produzione200 milioni in ingresso / 50 milioni in uscita$131

Run your own numbers in the Calcolatore dei costi delle API per l'IA.

Cheaper alternatives to DeepSeek V4-Pro

ModelloCosto combinato ($/1 milione)You save
DeepSeek V4-Flash aperta$0.16868% più economico

Self-host or pay the API?

DeepSeek V4-Pro is open-weight, so you can run it yourself. It needs ~800 GB of VRAM at 4-bit (Multi-GPU server (e.g. 8× H100 80GB)). Self-hosting only beats the API once your volume is high enough to keep that hardware busy — the calcolatore self-hosting vs API works out the break-even point for your token volume.

Domande frequenti

How much does DeepSeek V4-Pro cost per 1M tokens?

DeepSeek V4-Pro costs $0.435 per 1M input tokens and $0.870 per 1M output tokens. At a typical 4:1 input-to-output mix that blends to about $0.522 per 1M tokens.

How much does DeepSeek V4-Pro cost per month?

A small-team workload of 20M input and 5M output tokens a month costs about $13 on DeepSeek V4-Pro. A side project (1M in / 0.25M out) costs roughly $0.65.

What is a cheaper alternative to DeepSeek V4-Pro?

DeepSeek V4-Flash is the strongest cheaper option in our database at $0.168 per 1M blended — about 68% less than DeepSeek V4-Pro. It is also open-weight, so self-hosting is an option.

Can I run DeepSeek V4-Pro locally?

Yes. DeepSeek V4-Pro is open-weight and needs about ~800 GB of VRAM at 4-bit quantisation (Multi-GPU server (e.g. 8× H100 80GB)).

Why does DeepSeek V4-Pro charge more for output than input?

Output tokens are generated one at a time and cannot be batched the way a prompt can, so they cost the provider more to serve. DeepSeek V4-Pro charges 2× more for output, which is why prompt-heavy workloads are far cheaper to run than generation-heavy ones.

See every DeepSeek model priced side by side: DeepSeek API pricing.

Prices are the published list rates for the model's primary API and are reviewed as providers change them. Volume, batch and cached-input discounts are not included. Compare every model side by side in the Database di modelli di intelligenza artificiale o il Classifica LLM.

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