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model llm

Qwen3 Highlights Qwen3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models. Built upon extensive training,

2
reasoning math science code

Qwen 3 is the latest large reasoning model developed by Alibaba company. It surpass multiple baselines on coding, math and surpass SOTA model performance on multiple benchmarks. It is said to be relea

3
reasoning

DeepSeek V3 0324 is the latest generation LLM developed by the Deepseek company. It is reported to surpass multiple baselines.

4
model reason

Qwen3-0.6B has the following features: Type: Causal Language Models Training Stage: Pretraining & Post-training Number of Parameters: 0.6B Number of Paramaters (Non-Embedding): 0.44B Number of

5
reasoning math proof

DeepSeek-Prover-V2 is an open-source large language model designed for formal theorem proving in Lean 4, with initialization data collected through a recursive theorem proving pipeline powered by Deep

6
model reason

Qwen3-32B has the following features: Type: Causal Language Models Training Stage: Pretraining & Post-training Number of Parameters: 32.8B Number of Paramaters (Non-Embedding): 31.2B Number of

7
reasoning

Deepseek R2 is the latest large reasoning model developped by the Deepseek company. It surpasses multiple baselines on coding, math benchmarks and lower the training as well as the inference cost by 9

8
model reason

Qwen3 14B has the following features: - Type: Causal Language Models - Training Stage: Pretraining & Post-training - Number of Parameters: 14.8B - Number of Paramaters (Non-Embedding): 13.2B - Nu

9
model reason

Qwen3-8B has the following features: Type: Causal Language Models Training Stage: Pretraining & Post-training Number of Parameters: 8.2B Number of Paramaters (Non-Embedding): 6.95B Number of La

10
model llm

Qwen3 Highlights Qwen3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models. Built upon extensive training,

11
model reason

Qwen3-4B has the following features: Type: Causal Language Models Training Stage: Pretraining & Post-training Number of Parameters: 4.0B Number of Paramaters (Non-Embedding): 3.6B Number of Lay

12
model reason

Qwen3-1.7B has the following features: Type: Causal Language Models Training Stage: Pretraining & Post-training Number of Parameters: 1.7B Number of Paramaters (Non-Embedding): 1.4B Number of L

Top Rated

1
reasoning math science code

Qwen 3 is the latest large reasoning model developed by Alibaba company. It surpass multiple baselines on coding, math and surpass SOTA model performance on multiple benchmarks. It is said to be relea

2
model reason

Qwen3-0.6B has the following features: Type: Causal Language Models Training Stage: Pretraining & Post-training Number of Parameters: 0.6B Number of Paramaters (Non-Embedding): 0.44B Number of

3
model reason

Qwen3-32B has the following features: Type: Causal Language Models Training Stage: Pretraining & Post-training Number of Parameters: 32.8B Number of Paramaters (Non-Embedding): 31.2B Number of

4
reasoning

Deepseek R2 is the latest large reasoning model developped by the Deepseek company. It surpasses multiple baselines on coding, math benchmarks and lower the training as well as the inference cost by 9

5
model llm

Qwen3 Highlights Qwen3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models. Built upon extensive training,

6
reasoning

DeepSeek V3 0324 is the latest generation LLM developed by the Deepseek company. It is reported to surpass multiple baselines.

7
reasoning math proof

DeepSeek-Prover-V2 is an open-source large language model designed for formal theorem proving in Lean 4, with initialization data collected through a recursive theorem proving pipeline powered by Deep

8
model reason

Qwen3 14B has the following features: - Type: Causal Language Models - Training Stage: Pretraining & Post-training - Number of Parameters: 14.8B - Number of Paramaters (Non-Embedding): 13.2B - Nu

9
model reason

Qwen3-8B has the following features: Type: Causal Language Models Training Stage: Pretraining & Post-training Number of Parameters: 8.2B Number of Paramaters (Non-Embedding): 6.95B Number of La

10
model llm

Qwen3 Highlights Qwen3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models. Built upon extensive training,

11
model reason

Qwen3-4B has the following features: Type: Causal Language Models Training Stage: Pretraining & Post-training Number of Parameters: 4.0B Number of Paramaters (Non-Embedding): 3.6B Number of Lay

12
model reason

Qwen3-1.7B has the following features: Type: Causal Language Models Training Stage: Pretraining & Post-training Number of Parameters: 1.7B Number of Paramaters (Non-Embedding): 1.4B Number of L

Reviews

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  • A
    AILearner98 2025-05-12 22:54
    5.0
    Interesting:5,Helpfulness:5,Correctness:5
    Prompt: I have a project name for example "project_a" and I want to support both python (pypi) and typescript (npm) services. Additionally, I have some front end plugin which is associated with the APIs (GET). The package support various endpoint and registry service. How can I set the package folder?

    I asked Qwen3 to help me with the coding problem, which is to create a package folder structure for both python and typescript. It should also contains a folder for plugin. Right now. Qwen3 provides the best answer to me compared to DeepSeek and many other.

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  • K
    kevinsmash 2025-05-04 08:47
    5.0
    Interesting:5,Helpfulness:5,Correctness:5

    Qwen 0.6B small size LLM is extremely powerful in realworld applications such as search and recommendation, query intent recognition, etc. And Qwen3 0.6B model is the SOTA one compared to previous counterparts such as Gemini and Llama small size LLM.

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  • A
    aigc_coder 2025-05-02 12:25
    4.0
    Interesting:4,Helpfulness:4,Correctness:3

    DeepSeek V3 has very high hallucination compared to other large MoE model with such huge size of parameters.

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  • A
    aigc_coder 2025-05-02 12:03
    5.0
    Interesting:5,Helpfulness:5,Correctness:5

    Qwen3 32B model series are the most widely adopted and deployed model in industrial applications, which compromise of inference speed and performance. This updated version of Qwen3 32B model have the thinking mode and non-thinking mode, which supports both the common task of chat/text generation and more complex task of math, code generation, etc. On the AIME and many other math benchmarks, Qwen3 surpass many of the opensource counterpart.

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  • A
    aigc_coder 2025-05-02 11:56
    3.0
    Interesting:3,Helpfulness:2,Correctness:3

    Qwen3 235B A22B model is more like an upgraded version of DeepSeek-R1. And it is also compared with Deepseek R1 model on multiple benchmarks of code and math. Personally, I don't Qwen3 is a huge upgrade compared to Gemini/OpenAI and Deepseek model, but more like a compromised version of complex thinking and realistic usage.

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