Gemini-2.0-Flash-001
N/A
Model parameter quantity
Google
Affiliated organization
Closed Source
License Type
February 5, 2025
Release time
Related figures
Model Introduction
Gemini 2.0 Flash builds on the performance of Gemini 1.5 Flash, introducing multimodal input/output support (including images, video, audio, and text), along with real-time functionalities such as steerable text-to-speech and native image generation. The specific version being used is Gemini-2.0-Flash-001.
Comprehensive score
Language dialogue
Knowledge reserve
Reasoning association
Mathematical calculation
Code writing
Command following
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Language comprehension ability
Often makes semantic misjudgments, leading to obvious logical disconnects in responses.
6.7
Knowledge coverage scope
Possesses core knowledge of mainstream disciplines, but has limited coverage of cutting-edge interdisciplinary fields.
8.7
Reasoning ability
Can perform logical reasoning with more than three steps, though efficiency drops when handling nonlinear relationships.
7.0
Model comparison
Gemini-2.0-Flash-001 vs Qwen2.5-7B-Instruct
Like Qwen2, the Qwen2.5 language models support up to 128K tokens and can generate up to 8K tokens. They also maintain multilingual support for over 29 languages, including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean, Vietnamese, Thai, Arabic, and more.
Gemini-2.0-Flash-001 vs GPT-4o-mini-20240718
GPT-4o-mini is an API model produced by OpenAI, with the specific version number being gpt-4o-mini-2024-07-18.
Gemini-2.0-Flash-001 vs GPT-4o-mini-20240718
GPT-4o-mini is an API model produced by OpenAI, with the specific version number being gpt-4o-mini-2024-07-18.
Gemini-2.0-Flash-001 vs Gemini-2.5-Pro-Preview-05-06
Gemini 2.5 Pro is a model released by Google DeepMind artificial intelligence research team, using version number Gemini-2.5-Pro-Preview-05-06.
Gemini-2.0-Flash-001 vs DeepSeek-V2-Chat-0628
DeepSeek-V2 is a strong Mixture-of-Experts (MoE) language model characterized by economical training and efficient inference. It comprises 236B total parameters, of which 21B are activated for each token. Compared with DeepSeek 67B, DeepSeek-V2 achieves stronger performance, and meanwhile saves 42.5% of training costs, reduces the KV cache by 93.3%, and boosts the maximum generation throughput to 5.76 times.
Related model
Gemma-3-27B-it
Gemma is a family of lightweight, state-of-the-art open models from Google, built from the same research and technology used to create the Gemini models.
Gemini-2.5-Pro
The official release version of the Gemini 2.5 pro
Gemini-1.5-Pro-Latest
Gemini 1.5 Pro introduces a breakthrough context window of up to two million tokens — the longest context window of any large scale foundation model yet. It achieves near-perfect recall on long-context retrieval tasks across modalities, unlocking the ability to accurately process large-scale documents, thousands of lines of code, hours of audio, video, and more.
Gemma-2-27B-it
Gemma is a family of lightweight, state-of-the-art open models from Google, built from the same research and technology used to create the Gemini models.
Gemma-2-27B-it
Gemma is a family of lightweight, state-of-the-art open models from Google, built from the same research and technology used to create the Gemini models.
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