deepseek r1 asked for 1 truly novel insight about humans
With the help of the latest and most advanced model, you can use the extremely stable DeepSeek-v3 for free without any limitations and without any system busyness or answer failures that are common with other DeepSeek.
Access to DeepSeek-v3 AI Powered & Stable within 3 simple steps
First, click on the "Start Now" button on the page in order to successfully access the stable DeepSeek-v3.
Next, in the new dialog box, enter your question or instructions that are clear to ensure the quality of output.
DeepSeek-v3 will fully understand your question and provide you with cutting-edge AI solutions. Also, based on your question, it will reason and answer other questions that you may need.
Competitive collection of key-features that make DeepSeek-v3 model stand out
In the innovative Mix-of-Experts architecture with 671B total parameters, 37B parameters are activated for each token for optimal efficiency and performance.
It provides you with the stable output of cutting-edge results by using state-of-the-art language models across multiple benchmarks.
Extensive professional model training was performed on DeepSeek-v3 to ensure its diversity of data sources and a full range of high-quality content.
Although it is large, DeepSeek-v3 has efficient reasoning capabilities to answer your questions quickly, even give you instant output.
DeepSeek-v3 model allows you to use it for free and without any restrictions. You can keep typing your questions and get answers in a single window.
As a global AI, DeepSeek-v3 supports different languages and multiple deployment options for NVIDIA, AMD GPUs and Huawei Ascend NPUs.
DeepSeek-v3, at the top of the open source models and a strong competitor to other models, is a major breakthrough in speed, performance, and cost-effectiveness compared to previous models.
Benchmark (Metric) | DeepSeek V3 | DeepSeek V2.5 | Qwen2.5 | Llama3.1 | Claude-3.5 | GPT-4o | |
---|---|---|---|---|---|---|---|
0905 | 72B-Inst | 405B-Inst | Sonnet-1022 | 0513 | |||
Architecture | MoE | MoE | Dense | Dense | - | - | |
# Activated Params | 37B | 21B | 72B | 405B | - | - | |
# Total Params | 671B | 236B | 72B | 405B | - | - | |
English | MMLU (EM) | 88.5 | 80.6 | 85.3 | 88.6 | 88.3 | 87.2 |
MMLU-Redux (EM) | 89.1 | 80.3 | 85.6 | 86.2 | 88.9 | 88.0 | |
MMLU-Pro (EM) | 75.9 | 66.2 | 71.6 | 73.3 | 78.0 | 72.6 | |
DROP (3-shot F1) | 91.6 | 87.8 | 76.7 | 88.7 | 88.3 | 83.7 | |
IF-Eval (Prompt Strict) | 86.1 | 80.6 | 84.1 | 86.0 | 86.5 | 84.3 | |
GPQA-Diamond (Pass@1) | 59.1 | 41.3 | 49.0 | 51.1 | 65.0 | 49.9 | |
SimpleQA (Correct) | 24.9 | 10.2 | 9.1 | 17.1 | 28.4 | 38.2 | |
FRAMES (Acc.) | 73.3 | 65.4 | 69.8 | 70.0 | 72.5 | 80.5 | |
LongBench v2 (Acc.) | 48.7 | 35.4 | 39.4 | 36.1 | 41.0 | 48.1 | |
Code | HumanEval-Mul (Pass@1) | 82.6 | 77.4 | 77.3 | 77.2 | 81.7 | 80.5 |
LiveCodeBench (Pass@1-COT) | 40.5 | 29.2 | 31.1 | 28.4 | 36.3 | 33.4 | |
LiveCodeBench (Pass@1) | 37.6 | 28.4 | 28.7 | 30.1 | 32.8 | 34.2 | |
Codeforces (Percentile) | 51.6 | 35.6 | 24.8 | 25.3 | 20.3 | 23.6 | |
SWE Verified (Resolved) | 42.0 | 22.6 | 23.8 | 24.5 | 50.8 | 38.8 | |
Aider-Edit (Acc.) | 79.7 | 71.6 | 65.4 | 63.9 | 84.2 | 72.9 | |
Aider-Polyglot (Acc.) | 49.6 | 18.2 | 7.6 | 5.8 | 45.3 | 16.0 | |
Math | AIME 2024 (Pass@1) | 39.2 | 16.7 | 23.3 | 23.3 | 16.0 | 9.3 |
MATH-500 (EM) | 90.2 | 74.7 | 80.0 | 73.8 | 78.3 | 74.6 | |
CNMO 2024 (Pass@1) | 43.2 | 10.8 | 15.9 | 6.8 | 13.1 | 10.8 | |
Chinese | CLUEWSC (EM) | 90.9 | 90.4 | 91.4 | 84.7 | 85.4 | 87.9 |
C-Eval (EM) | 86.5 | 79.5 | 86.1 | 61.5 | 76.7 | 76.0 | |
C-SimpleQA (Correct) | 64.1 | 54.1 | 48.4 | 50.4 | 51.3 | 59.3 |
Let's see what the experts say about DeepSeek-v3, an advanced AI language model!
deepseek r1 asked for 1 truly novel insight about humans
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No. The model taps into the latest DeepSeek APIs: DeepSeek-v3 and DeepSeek-R1. With it, you can have unlimited use with unofficial high-speed implementation, and without the frequent questioning failures or system busyness that occur with other models.
DeepSeek-v3 supports multiple languages and multiple deployment options, including NVIDIA, AMD GPUs and Huawei Ascend NPUs.
DeepSeek-v3 combines the 671B parameter MoE architecture, multi-token prediction and assisted no-load balancing to deliver superior performance.
You can deploy DeepSeek-v3 with a variety of frameworks, such as SGLang, LMDeploy, TensorRT-LLM, vLLM, and it supports 2 inference modes: FP8 and BF16.
Yes. According to its Terms of Use and Privacy Policy, DeepSeek-v3 allows you to use it for commercial purposes.