Zhipu AI has launched the MathGLM mathematical model, aimed at enhancing the performance of large models in mathematical reasoning. MathGLM can accurately compute arithmetic operations, including basic arithmetic and complex mixed operations. MathGLM has shown excellent performance in solving math problems in Chinese. Its performance on arithmetic tasks surpasses that of GPT-4. MathGLM has achieved good results in addressing math problems for different grade levels and solving practical math problems.
Researchers from Tsinghua University and others have introduced MathGLM, a 2 billion parameter language model that outperforms GPT-4 with nearly 100% accuracy in arithmetic tasks. MathGLM utilizes a decoder-only architecture and has significantly improved its mathematical capabilities through training on a large-scale arithmetic dataset. It also surpasses models like GPT-4 and ChatGPT in handling complex mixed arithmetic operations with intricate numerical formats.
Openai
-
Input tokens/M
Output tokens/M
Context Length
Anthropic
$105
$525
200
Alibaba
$4
$16
1k
Bytedance
$0.8
$2
256
$3.5
$12
128
Deepseek
$8
32
Google
$21
$70
$210
Tencent
$100
Four Arithmetic Operations MCP Server Project
A simple calculator service based on a custom model context protocol (MCP), supporting basic arithmetic operations and deployed via Docker containers.
The Arithmo MCP Server is a high-performance arithmetic operation server based on the MCP protocol, supporting basic operations such as addition, subtraction, multiplication, and division. It is lightweight and easy to expand.
A simple MCP server implementation for teaching purposes, supporting basic arithmetic operations
An MCP server that provides four arithmetic operation functions, supports addition, subtraction, multiplication, and division operations, and can be called through the Claude application.
This is a mathematical calculation server based on the MCP protocol, supporting basic arithmetic operations and matrix multiplication, and is built using Python 3.13+ and the uv toolchain.
%20--%3e%3cdefs%3e%3cstyle%3e%20.st0%20{%20fill:%20%23061b40;%20}%20.st1%20{%20fill:%20%23306af1;%20}%20.st2%20{%20fill:%20%235ce5cf;%20}%20%3c/style%3e%3c/defs%3e%3cg%3e%3cpath%20class='st0'%20d='M55,10.5h9v3h-9v9h12V7.5h-12v3ZM64,19.5h-6v-3h6v3Z'/%3e%3cpolygon%20class='st0'%20points='69%2016.5%2078%2016.5%2078%2019.5%2069%2019.5%2069%2022.5%2081%2022.5%2081%2013.5%2072%2013.5%2072%2010.5%2081%2010.5%2081%207.5%2069%207.5%2069%2016.5'/%3e%3cpolygon%20class='st0'%20points='95%2010.5%2095%207.5%2083%207.5%2083%2022.5%2095%2022.5%2095%2019.5%2086%2019.5%2086%2016.5%2095%2016.5%2095%2013.5%2086%2013.5%2086%2010.5%2095%2010.5'/%3e%3cpath%20class='st0'%20d='M40,1.5v21h11.6l1.4-1.4v-7.6h0c0,0-1.4-1.5-1.4-1.5l1.4-1.4V2.9l-1.4-1.4h-11.6ZM50,19.5h-7v-6h7v6ZM50,10.5h-7v-6h7v6Z'/%3e%3c/g%3e%3cpath%20class='st1'%20d='M23.1,24L14.7,4.8l-4.9,11.2h3.8l-1.8,4H3.3L12.1,0H2C.9,0,0,.9,0,2v20c0,1.1.9,2,2,2h21.1Z'/%3e%3cpath%20class='st2'%20d='M34,0h-16.8l10.6,24h6.2c1.1,0,2-.9,2-2V2C36,.9,35.1,0,34,0ZM32.5,20h-4V4h4v16Z'/%3e%3c/svg%3e)
