Modèles

16 modèles

DeepSeek V4 Flash Vision Exp is an experimental vision-enabled version of [DeepSeek V4 Flash 0731](https://openrouter.ai/deepseek/deepseek-v4-flash-0731) from DeepSeek, adding image understanding while matching the base model on text capabilities including agents,...

par deepseek21 août 2026contexte de 1,05 M386 ₩ / 1 158 ₩ · 1M
1,08 Bn tokens par semaine

DeepSeek V4 Pro 0813 is a large-scale mixture-of-experts model from DeepSeek. This is the GA release of DeepSeek V4 Pro.

par deepseek13 août 2026contexte de 1,05 M1 967 ₩ / 5 900 ₩ · 1M

DeepSeek V4 Pro 0813 is a large-scale mixture-of-experts model from DeepSeek. This is the GA release of DeepSeek V4 Pro.

par deepseek13 août 2026contexte de 1,05 M2 317 ₩ / 6 950 ₩ · 1M
11,29 Bn tokens par semaine

DeepSeek V4 Flash 0731 is a sparse mixture-of-experts model from DeepSeek, with 13B active parameters out of 284B total. This re-post-trained revision is suited for coding, reasoning, and agent workflows....

par deepseek31 juil. 2026contexte de 1,31 M114 ₩ / 316 ₩ · 1M

DeepSeek V4 Flash 0731 is a sparse mixture-of-experts model from DeepSeek, with 13B active parameters out of 284B total. This re-post-trained revision is suited for coding, reasoning, and agent workflows....

par deepseek31 juil. 2026contexte de 1,05 M246 ₩ / 491 ₩ · 1M
1,49 Bn tokens par semaine

DeepSeek V4 Pro is a large-scale Mixture-of-Experts model from DeepSeek with 1.6T total parameters and 49B activated parameters, supporting a 1M-token context window. It is designed for advanced reasoning, coding,...

par deepseek24 avr. 2026contexte de 1,05 M1 331 ₩ / 2 663 ₩ · 1M
5,18 Bn tokens par semaine

DeepSeek V4 Flash is an efficiency-optimized Mixture-of-Experts model from DeepSeek with 284B total parameters and 13B activated parameters, supporting a 1M-token context window. It is designed for fast inference and...

par deepseek24 avr. 2026contexte de 1,05 M144 ₩ / 287 ₩ · 1M

DeepSeek-V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism...

par deepseek1 déc. 2025contexte de 163,84 k472 ₩ / 702 ₩ · 1M

DeepSeek-V3.2-Exp is an experimental large language model released by DeepSeek as an intermediate step between V3.1 and future architectures. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism...

par deepseek29 sept. 2025contexte de 163,84 k474 ₩ / 720 ₩ · 1M

DeepSeek-V3.1 Terminus is an update to [DeepSeek V3.1](/deepseek/deepseek-chat-v3.1) that maintains the model's original capabilities while addressing issues reported by users, including language consistency and agent capabilities, further optimizing the model's...

par deepseek22 sept. 2025contexte de 163,84 k474 ₩ / 1 755 ₩ · 1M

DeepSeek-V3.1 is a large hybrid reasoning model (671B parameters, 37B active) that supports both thinking and non-thinking modes via prompt templates. It extends the DeepSeek-V3 base with a two-phase long-context...

par deepseek21 août 2025contexte de 163,84 k965 ₩ / 2 896 ₩ · 1M

May 28th update to the [original DeepSeek R1](/deepseek/deepseek-r1) Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active...

par deepseek29 mai 2025contexte de 163,84 k878 ₩ / 3 773 ₩ · 1M

DeepSeek V3, a 685B-parameter, mixture-of-experts model, is the latest iteration of the flagship chat model family from the DeepSeek team. It succeeds the [DeepSeek V3](/deepseek/deepseek-chat-v3) model and performs really well...

par deepseek24 mars 2025contexte de 163,84 k439 ₩ / 1 755 ₩ · 1M

DeepSeek R1 Distill Llama 70B is a distilled large language model based on [Llama-3.3-70B-Instruct](/meta-llama/llama-3.3-70b-instruct), using outputs from [DeepSeek R1](/deepseek/deepseek-r1). The model combines advanced distillation techniques to achieve high performance across...

par deepseek24 janv. 2025contexte de 8 k1 404 ₩ / 1 404 ₩ · 1M

DeepSeek R1 is here: Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inference pass....

par deepseek20 janv. 2025contexte de 64 k1 229 ₩ / 4 388 ₩ · 1M

DeepSeek-V3 is the latest model from the DeepSeek team, building upon the instruction following and coding abilities of the previous versions. Pre-trained on nearly 15 trillion tokens, the reported evaluations...

par deepseek27 déc. 2024contexte de 163,84 k562 ₩ / 1 562 ₩ · 1M