option
Home
List of Al models
Ministral-8B-Instruct-2410

Ministral-8B-Instruct-2410

Add comparison
Add comparison
Model parameter quantity
8B
Model parameter quantity
Affiliated organization
Mistral AI
Affiliated organization
Open Source
License Type
Release time
October 16, 2024
Release time

Model Introduction
The Ministral-8B-Instruct-2410 Language Model is an instruct fine-tuned model significantly outperforming existing models of similar size, released under the Mistral Research License.
Swipe left and right to view more
Language comprehension ability Language comprehension ability
Language comprehension ability
Often makes semantic misjudgments, leading to obvious logical disconnects in responses.
4.3
Knowledge coverage scope Knowledge coverage scope
Knowledge coverage scope
Possesses core knowledge of mainstream disciplines, but has limited coverage of cutting-edge interdisciplinary fields.
7.2
Reasoning ability Reasoning ability
Reasoning ability
Unable to maintain coherent reasoning chains, often causing inverted causality or miscalculations.
2.8
Related model
Mistral-Large-Instruct-2411 Mistral-Large-Instruct-2411 is an advanced dense Large Language Model (LLM) of 123B parameters with state-of-the-art reasoning, knowledge and coding capabilities extending Mistral-Large-Instruct-2407 with better Long Context, Function Calling and System Prompt.
Mistral-Large-Instruct-2411 Mistral-Large-Instruct-2411 is an advanced dense Large Language Model (LLM) of 123B parameters with state-of-the-art reasoning, knowledge and coding capabilities extending Mistral-Large-Instruct-2407 with better Long Context, Function Calling and System Prompt.
Mistral-Small-Instruct-2409 With 22 billion parameters, Mistral Small v24.09 offers customers a convenient mid-point between Mistral NeMo 12B and Mistral Large 2, providing a cost-effective solution that can be deployed across various platforms and environments.
Mistral-Small-Instruct-2409 With 22 billion parameters, Mistral Small v24.09 offers customers a convenient mid-point between Mistral NeMo 12B and Mistral Large 2, providing a cost-effective solution that can be deployed across various platforms and environments.
Ministral-8B-Instruct-2410 The Ministral-8B-Instruct-2410 Language Model is an instruct fine-tuned model significantly outperforming existing models of similar size, released under the Mistral Research License.
Relevant documents
Cursor AI Coding Startup to Hire 200 in Asia-Pacific After Significant Investment from SpaceX AI coding startup Cursor has unveiled a major global expansion, planning to hire 200 employees across the Asia-Pacific region over the next six months. Key roles include marketing engineers, field engineers, and AI deployment engineers. This move und
Claude Used to Create Malicious npm Packages: Over 670 Compromised Threaten Open Source A recent cybersecurity incident reveals how large language models (LLMs) are being weaponized for malicious software development. Security researcher Sibi Moosa spotted an attacker using the alias "mousie-5212-super-formatter" leveraging Anthropic's
Reliance unveils $110B AI investment plan as India accelerates tech drive Mukesh Ambani, the billionaire chairman of India's Reliance conglomerate, announced on Thursday a ₹10 trillion (roughly $110 billion) plan to build AI computing infrastructure across India over the next seven years.Speaking at the India AI Impact Sum
Zhiyuan WITA Ends 'Naked' Robot Interaction with First Compliance Filing The embodied intelligence sector has reached a significant milestone. According to the latest announcement from the Shanghai Cyberspace Administration, the WITA large model developed by Zhiyuan has successfully completed the filing process, becoming
Anthropic Study Links Polished AI Content to Reduced Human Thinking When you see AI instantly produce a well-structured, logically clear piece of code or document, are you tempted to trust it without a second thought? According to AIbase, the leading AI company Anthropic recently published a research report titled "A
Model comparison
Start the comparison
OR