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DeepSeek — KI-Modelle im Überblick

DeepSeek aus Hangzhou demonstriert mit V3 und R1, dass chinesische Open-Weight-Modelle die Frontier erreichen können — zu einem Bruchteil der Trainingskosten.

8aktive Modelle
51,5Top-Quality (DeepSeek: DeepSeek V4 Pro)
28. April 2026Letzte Synchronisation
#1

DeepSeek: DeepSeek V4 Pro

deepseek/deepseek-v4-pro
51,5
Quality
Speed35,6 t/s
Latency1,29 s
Input$1.74
Output$3.48

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,...

#2

DeepSeek: DeepSeek V4 Flash

deepseek/deepseek-v4-flash
46,5
Quality
Speed79,0 t/s
Latency753 ms
Input$0.14
Output$0.28

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...

#3

DeepSeek: DeepSeek V3.1 Terminus

deepseek/deepseek-v3.1-terminus
33,9
Quality
Speed0 t/s
Latency0 ms
Input$1.635
Output$2.75

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...

#4

DeepSeek: DeepSeek V3.2

deepseek/deepseek-v3.2
32,1
Quality
Speed80,7 t/s
Latency741 ms
Input$0.28
Output$0.42

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...

#5

DeepSeek: DeepSeek V3.2 Speciale

deepseek/deepseek-v3.2-speciale
29,4
Quality
Speed0 t/s
Latency0 ms
Input$0
Output$0

DeepSeek-V3.2-Speciale is a high-compute variant of DeepSeek-V3.2 optimized for maximum reasoning and agentic performance. It builds on DeepSeek Sparse Attention (DSA) for efficient long-context processing, then scales post-training reinforcement learning...

#6

DeepSeek: R1

deepseek/deepseek-r1
27,1
Quality
Speed0 t/s
Latency0 ms
Input$1.35
Output$4.20

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....

#7

DeepSeek: R1 Distill Qwen 32B

deepseek/deepseek-r1-distill-qwen-32b
17,2
Quality
Speed0 t/s
Latency0 ms
Input$0
Output$0

DeepSeek R1 Distill Qwen 32B is a distilled large language model based on [Qwen 2.5 32B](https://huggingface.co/Qwen/Qwen2.5-32B), using outputs from [DeepSeek R1](/deepseek/deepseek-r1). It outperforms OpenAI's o1-mini across various benchmarks, achieving new...

#8

DeepSeek: R1 Distill Llama 70B

deepseek/deepseek-r1-distill-llama-70b
16
Quality
Speed45,1 t/s
Latency451 ms
Input$0.70
Output$1.05

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...

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