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Qwen vs DeepSeek

Alibaba's open-weight model family, strong on multilingual and coding tasks.

Comparaison des critères

Comparaison de Qwen et DeepSeek
Critère Qwen DeepSeek
Context window 128k tokens 128k tokens
License Apache-2.0 for most sizes MIT for code, DeepSeek License for weights
Open weights Yes Yes
Parameters 0.5B to 72B 7B to 67B
Provider Alibaba DeepSeek

Les lignes grisées sont identiques pour les deux ; ce sont les lignes qui diffèrent qui motivent la recommandation ci-dessous.

Lequel choisir ?

Généré à partir des différences ci-dessus par des règles structurées, et non par un modèle.

Choose Qwen if…

Aucun des attributs enregistrés ne le distingue à son avantage.

Choose DeepSeek if…

Aucun des attributs enregistrés ne le distingue à son avantage.

Qwen

model · Models

Qwen is an open-weight language model family from Alibaba, released in a range of sizes and with a strong showing on multilingual and code benchmarks. It solves the same problem as other open-weight models: letting a team run a capable model without depending on a closed API. It exists as one of the few families that publishes both very small and very large variants, which makes it a common default when you need a model that fits a specific memory budget.

DeepSeek

model · Models

DeepSeek is an open-weight model family whose published training methods attracted attention for reaching competitive quality at lower reported cost. It solves the cost question in training rather than in inference, which is where most optimisation effort goes. It exists as evidence that architecture and training-schedule choices matter enough to change what a given budget can produce, and its weights and methods are published.