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DeepSeek R1

DeepSeek R1 — Spécifications

DéveloppeurDeepSeek
TypeLLM (MoE, raisonnement)
ModalitéTexte → Texte
Paramètres671 milliards au total / 37 milliards actifs (MoE)
Fenêtre de contexte128 K
Sortie maximale
LicenceMIT (ouverte)
Poids ouvertsOui
Publié2025
Prix de l’entrée0,50 $ par million
Prix de la sortie2,15 $ par million
Fournisseurs d'APIDeepSeek, DeepInfra, OpenRouter

Exécutez-le localement

VRAM (4 bits)~400 Go
GPU minimal requisServeur multi-GPU

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What is DeepSeek R1?

DeepSeek R1 is the landmark open reasoning model — a 671B mixture-of-experts activating
37B parameters per token, MIT-licensed, with a 128K context window. It delivered
frontier-class chain-of-thought reasoning at a fraction of proprietary cost and is the model
that made open reasoning weights a mainstream option rather than a research curiosity.

Two things follow from the architecture. First, the API is genuinely cheap at $0.50 in /
$2.15 out per million tokens, because only 37B of the 671B parameters are active on any given
token. Second, self-hosting is not cheap at all: the full weights need roughly 400 GB of VRAM
even at 4-bit quantisation, which means a multi-GPU server, not a workstation. The MIT
licence gives you the right to run it, but the hardware bill is what decides whether you
will. For most teams the correct reading is that R1 is an API model that happens to be
auditable and portable — you can move providers, inspect the weights, and never be locked in,
without personally operating an eight-GPU node. If you want R1-style reasoning on hardware
you own, the 70B distill is the model to look at instead.

DeepSeek R1 pricing: API cost per 1M tokens

Entrée (par million de jetons)$0.500
Sortie (par million de jetons)$2.15
Output/input ratio4.3×
Blended (4:1 in:out)$0.830 per 1M tokens

What DeepSeek R1 costs per month

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

Charge de travailJetons/moisCost / month
Projet secondaire1 million en entrée / 0,25 million en sortie$1.04
Petite équipe20 millions en entrée / 5 millions en sortie$21
Production200 millions en entrée / 50 millions en sortie$208

Run your own numbers in the Calculateur de coûts des API IA.

Cheaper alternatives to DeepSeek R1

ModèleCoût combiné par million de dollarsYou save
DeepSeek V4-Pro ouverte$0.52237% cheaper
DeepSeek V4-Flash ouverte$0.16880% cheaper
Llama 4 Maverick ouverte$0.24071 % moins cher

Self-host or pay the API?

DeepSeek R1 is open-weight, so you can run it yourself. It needs ~400 Go of VRAM at 4-bit (Multi-GPU server). Self-hosting only beats the API once your volume is high enough to keep that hardware busy — the calculateur auto-hébergement vs API works out the break-even point for your token volume.

Questions fréquemment posées

How much does DeepSeek R1 cost per 1M tokens?

DeepSeek R1 costs $0.500 per 1M input tokens and $2.15 per 1M output tokens. At a typical 4:1 input-to-output mix that blends to about $0.830 per 1M tokens.

How much does DeepSeek R1 cost per month?

A small-team workload of 20M input and 5M output tokens a month costs about $21 on DeepSeek R1. A side project (1M in / 0.25M out) costs roughly $1.04.

What is a cheaper alternative to DeepSeek R1?

DeepSeek V4-Pro is the strongest cheaper option in our database at $0.522 per 1M blended — about 37% less than DeepSeek R1. It is also open-weight, so self-hosting is an option.

Can I run DeepSeek R1 locally?

Yes. DeepSeek R1 is open-weight and needs about ~400 GB of VRAM at 4-bit quantisation (Multi-GPU server).

Why does DeepSeek R1 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 R1 charges 4.3× 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 Base de données des modèles d'IA ou le Classement des grands modèles linguistiques (LLM).

⚔️ Compare DeepSeek R1 head-to-head

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