rank
int64 1
112
| model
stringlengths 5
65
| accuracy
float64 10.6
89.7
| parameters
float64 1.5
540
⌀ | extra_training_data
stringclasses 2
values | paper
stringlengths 0
110
| code
stringclasses 3
values | result
stringclasses 3
values | year
int64 2.02k
2.02k
| tags
listlengths 0
3
|
|---|---|---|---|---|---|---|---|---|---|
1
|
Gemini 2.0 Flash Experimental
| 89.7
| null |
No
|
No
|
No
| 2,024
|
[] |
|
2
|
Qwen2.5-Math-72B-Instruct (TIR,Greedy)
| 88.1
| 72
|
Yes
|
Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement
|
No
|
Yes
| 2,024
|
[] |
3
|
GPT-4 Turbo (MACM, w/code, voting)
| 87.92
| null |
No
|
MACM: Utilizing a Multi-Agent System for Condition Mining in Solving Complex Mathematical Problems
|
Yes
|
Yes
| 2,024
|
[
"code environment",
"majority voting",
"multi-agent"
] |
4
|
Qwen2.5-Math-72B-Instruct (COT,Greedy)
| 85.9
| 72
|
Yes
|
Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement
|
No
|
Yes
| 2,024
|
[] |
5
|
Qwen2.5-Math-7B-Instruct (TIR,Greedy)
| 85.2
| 7
|
Yes
|
Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement
|
No
|
Yes
| 2,024
|
[] |
6
|
GPT-4-code model (CSV, w/ code, SC, k=16)
| 84.3
| null |
No
|
Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification
|
Yes
|
Yes
| 2,023
|
[
"multi-agent",
"majority voting",
"code environment"
] |
7
|
Qwen2-Math-72B-Instruct (greedy)
| 84
| 72
|
Yes
|
Qwen2 Technical Report
|
Yes
|
Yes
| 2,024
|
[] |
8
|
Qwen2.5-Math-7B-Instruct (COT,Greedy)
| 83.6
| 7
|
Yes
|
Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement
|
No
|
Yes
| 2,024
|
[] |
9
|
Qwen2.5-Math-1.5B-Instruct (TIR,Greedy)
| 79.9
| 1.5
|
Yes
|
Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement
|
No
|
Yes
| 2,024
|
[] |
10
|
OpenMath2-Llama3.1-70B (majority@256)
| 79.6
| null |
Yes
|
OpenMathInstruct-2: Accelerating AI for Math with Massive Open-Source Instruction Data
|
Yes
|
Yes
| 2,024
|
[] |
11
|
OpenMath2-Llama3.1-8B (majority@256)
| 76.1
| null |
Yes
|
OpenMathInstruct-2: Accelerating AI for Math with Massive Open-Source Instruction Data
|
Yes
|
Yes
| 2,024
|
[] |
12
|
Qwen2.5-Math-1.5B-Instruct (COT,Greedy)
| 75.8
| 1.5
|
Yes
|
Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement
|
No
|
Yes
| 2,024
|
[] |
13
|
GPT-4-code model (CSV, w/ code)
| 73.5
| null |
No
|
Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification
|
Yes
|
Yes
| 2,023
|
[
"code environment"
] |
14
|
CR (GPT-4-turbo model, w/ code)
| 72.2
| null |
No
|
Cumulative Reasoning with Large Language Models
|
Yes
|
Yes
| 2,023
|
[
"code environment"
] |
15
|
OpenMath2-Llama3.1-70B
| 71.9
| null |
Yes
|
OpenMathInstruct-2: Accelerating AI for Math with Massive Open-Source Instruction Data
|
Yes
|
Yes
| 2,024
|
[] |
16
|
LogicNet (with code interpreter)
| 71.2
| null |
Yes
|
Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification
|
Yes
|
Yes
| 2,023
|
[] |
17
|
Qwen2-72B-Instruct-Step-DPO (0-shot CoT, w/o code)
| 70.8
| null |
Yes
|
Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs
|
Yes
|
Yes
| 2,024
|
[] |
18
|
GPT-4-code model (w/ code)
| 69.7
| null |
No
|
Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification
|
Yes
|
Yes
| 2,023
|
[
"code environment"
] |
19
|
OpenMath2-Llama3.1-8B
| 67.8
| null |
Yes
|
OpenMathInstruct-2: Accelerating AI for Math with Massive Open-Source Instruction Data
|
Yes
|
Yes
| 2,024
|
[] |
20
|
AlphaMath-7B-SBS@3
| 66.3
| null |
No
|
AlphaMath Almost Zero: Process Supervision without Process
|
Yes
|
Yes
| 2,024
|
[
"code environment"
] |
21
|
Minerva 62B (maj5@256)
| 64.9
| 62
|
No
|
Solving Quantitative Reasoning Problems with Language Models
|
Yes
|
Yes
| 2,022
|
[] |
22
|
DAMOMath-7B
| 64.5
| 7
|
Yes
| 2,024
|
[] |
|||
23
|
MMOS-DeepSeekMath-7B (0-shot,k=50)
| 63.7
| 7
|
Yes
|
An Empirical Study of Data Ability Boundary in LLMs' Math Reasoning
|
Yes
|
Yes
| 2,024
|
[
"code environment",
"zero-shot",
"majority voting"
] |
24
|
GPT-4-code model (w/o code)
| 60.8
| null |
No
|
Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification
|
Yes
|
Yes
| 2,023
|
[] |
25
|
OpenMath-CodeLlama-70B (w/ code, SC, k=50)
| 60.4
| 70
|
Yes
|
OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset
|
Yes
|
Yes
| 2,024
|
[
"code environment",
"majority voting"
] |
26
|
OpenMath-CodeLlama-34B (w/ code, SC, k=50)
| 60.2
| 34
|
Yes
|
OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset
|
Yes
|
Yes
| 2,024
|
[
"code environment",
"majority voting"
] |
27
|
ToRA-Code 34B model (w/ code, SC, k=50)
| 60
| 34
|
Yes
|
ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving
|
Yes
|
Yes
| 2,023
|
[
"majority voting",
"code environment",
"gpt-4 distillation"
] |
28
|
DeepSeekMATH-RL-7B (w/ code, greedy decoding)
| 58.8
| 7
|
Yes
|
DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
|
Yes
|
Yes
| 2,024
|
[] |
29
|
OpenMath-Llama2-70B (w/ code, SC, k=50)
| 58.3
| 70
|
Yes
|
OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset
|
Yes
|
Yes
| 2,024
|
[
"code environment",
"majority voting"
] |
30
|
CR (GPT-4 model, w/o code)
| 58
| null |
No
|
Cumulative Reasoning with Large Language Models
|
Yes
|
Yes
| 2,023
|
[] |
31
|
OpenMath-CodeLlama-13B (w/ code, SC, k=50)
| 57.6
| 13
|
Yes
|
OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset
|
Yes
|
Yes
| 2,024
|
[
"code environment",
"majority voting"
] |
32
|
OpenMath-Mistral-7B (w/ code, SC, k=50)
| 57.2
| 7
|
Yes
|
OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset
|
Yes
|
Yes
| 2,024
|
[
"code environment",
"majority voting"
] |
33
|
ToRA 70B (w/ code, SC, k=50)
| 56.9
| 70
|
Yes
|
ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving
|
Yes
|
Yes
| 2,023
|
[
"majority voting",
"code environment",
"gpt-4 distillation"
] |
34
|
SKiC (GPT-4 model)
| 56.4
| null |
No
|
Skills-in-Context Prompting: Unlocking Compositionality in Large Language Models
|
No
|
Yes
| 2,023
|
[
"code environment"
] |
35
|
DART-Math-Llama3-70B-Prop2Diff (0-shot CoT, w/o code)
| 56.1
| 70
|
Yes
|
DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving
|
Yes
|
Yes
| 2,024
|
[] |
36
|
OpenMath-CodeLlama-7B (w/ code, SC, k=50)
| 55.6
| 7
|
Yes
|
OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset
|
Yes
|
Yes
| 2,024
|
[
"code environment",
"majority voting"
] |
37
|
MMOS-DeepSeekMath-7B (0-shot)
| 55
| 7
|
Yes
|
An Empirical Study of Data Ability Boundary in LLMs' Math Reasoning
|
Yes
|
Yes
| 2,024
|
[] |
38
|
DART-Math-Llama3-70B-Uniform (0-shot CoT, w/o code)
| 54.9
| 70
|
Yes
|
DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving
|
Yes
|
Yes
| 2,024
|
[] |
39
|
PHP (GPT-4 model)
| 53.9
| null |
No
|
Progressive-Hint Prompting Improves Reasoning in Large Language Models
|
Yes
|
Yes
| 2,023
|
[] |
40
|
DART-Math-DSMath-7B-Prop2Diff (0-shot CoT, w/o code)
| 53.6
| 7
|
Yes
|
DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving
|
Yes
|
Yes
| 2,024
|
[] |
41
|
Gemini Ultra (4-shot)
| 53.2
| null |
No
|
Gemini: A Family of Highly Capable Multimodal Models
|
Yes
|
Yes
| 2,023
|
[] |
42
|
DART-Math-DSMath-7B-Uniform (0-shot CoT, w/o code)
| 52.9
| 7
|
Yes
|
DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving
|
Yes
|
Yes
| 2,024
|
[] |
43
|
GPT-4 model (w/ code, PAL)
| 51.8
| null |
No
|
PAL: Program-aided Language Models
|
Yes
|
Yes
| 2,022
|
[
"code environment"
] |
44
|
DeepSeekMATH-RL-7B (greedy decoding)
| 51.7
| 7
|
Yes
|
DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
|
Yes
|
Yes
| 2,024
|
[] |
45
|
AlphaLLM (with MCTS)
| 51
| null |
No
|
Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing
|
Yes
|
Yes
| 2,024
|
[] |
46
|
ToRA-Code 34B (w/ code)
| 50.8
| 34
|
Yes
|
ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving
|
Yes
|
Yes
| 2,023
|
[
"code environment",
"gpt-4 distillation"
] |
47
|
OpenMath-CodeLlama-70B (w/ code)
| 50.7
| 70
|
Yes
|
OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset
|
Yes
|
No
| 2,024
|
[
"code environment"
] |
48
|
Minerva 540B (maj1@k, k=64)
| 50.3
| null |
No
|
Solving Quantitative Reasoning Problems with Language Models
|
Yes
|
Yes
| 2,022
|
[
"majority voting"
] |
49
|
ToRA 70B (w/ code)
| 49.7
| 70
|
Yes
|
ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving
|
Yes
|
Yes
| 2,023
|
[
"code environment",
"gpt-4 distillation"
] |
50
|
MMOS-CODE-34B (0-shot)
| 49.5
| 34
|
Yes
|
An Empirical Study of Data Ability Boundary in LLMs' Math Reasoning
|
Yes
|
Yes
| 2,024
|
[] |
51
|
DeepSeekMath-7B-KPMath-Plus
| 48.8
| 7
|
No
|
Key-Point-Driven Data Synthesis with its Enhancement on Mathematical Reasoning
| 2,024
|
[] |
||
52
|
PaLM 2 (few-shot, k=4, SC)
| 48.8
| null |
No
|
PaLM 2 Technical Report
|
Yes
|
No
| 2,023
|
[
"majority voting"
] |
53
|
Llemma-34B-KPMath-Plus
| 48.6
| 34
|
No
|
Key-Point-Driven Data Synthesis with its Enhancement on Mathematical Reasoning
| 2,024
|
[] |
||
54
|
OpenMath-CodeLlama-34B (w/ code)
| 48.3
| 34
|
Yes
|
OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset
|
Yes
|
Yes
| 2,024
|
[
"code environment"
] |
55
|
Shepherd + DeepSeek-67B (SFT on MetaMATH + PRM rerank, k=256)
| 48.1
| 67
|
Yes
|
Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotations
|
Yes
|
No
| 2,023
|
[
"rerank"
] |
56
|
ToRA-Code 13B (w/ code)
| 48.1
| 13
|
Yes
|
ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving
|
Yes
|
Yes
| 2,023
|
[
"code environment",
"gpt-4 distillation"
] |
57
|
Minerva 8B (maj5@256)
| 47.6
| 8
|
No
|
Solving Quantitative Reasoning Problems with Language Models
|
Yes
|
Yes
| 2,022
|
[] |
58
|
Mistral-7B-KPMath-Plus
| 46.8
| 7
|
Yes
|
Key-Point-Driven Data Synthesis with its Enhancement on Mathematical Reasoning
| 2,024
|
[] |
||
59
|
DART-Math-Llama3-8B-Prop2Diff (0-shot CoT, w/o code)
| 46.6
| 8
|
Yes
|
DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving
|
Yes
|
Yes
| 2,024
|
[] |
60
|
OpenMath-Llama2-70B (w/ code)
| 46.3
| 70
|
Yes
|
OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset
|
Yes
|
No
| 2,024
|
[] |
61
|
OpenMath-CodeLlama-13B (w/ code)
| 45.5
| 13
|
Yes
|
OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset
|
Yes
|
No
| 2,024
|
[] |
62
|
DART-Math-Mistral-7B-Prop2Diff (0-shot CoT, w/o code)
| 45.5
| 7
|
Yes
|
DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving
|
No
|
Yes
| 2,024
|
[] |
63
|
DART-Math-Llama3-8B-Uniform (0-shot CoT, w/o code)
| 45.3
| 8
|
Yes
|
DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving
|
Yes
|
Yes
| 2,024
|
[] |
64
|
MathCoder-CL-34B
| 45.2
| 34
|
Yes
|
MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning
|
Yes
|
No
| 2,023
|
[] |
65
|
MathCoder-L-34B
| 45.1
| 34
|
Yes
|
MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning
|
Yes
|
No
| 2,023
|
[] |
66
|
MMIQC-72B
| 45
| 72
|
Yes
|
Augmenting Math Word Problems via Iterative Question Composing
|
Yes
|
Yes
| 2,024
|
[] |
67
|
ToRA-Code 7B (w/ code)
| 44.6
| 7
|
Yes
|
ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving
|
Yes
|
Yes
| 2,023
|
[
"code environment",
"gpt-4 distillation"
] |
68
|
OpenMath-Mistral-7B (w/ code)
| 44.5
| 7
|
Yes
|
OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset
|
Yes
|
No
| 2,024
|
[] |
69
|
MMOS-CODE-7B (0-shot)
| 44.3
| 7
|
Yes
|
An Empirical Study of Data Ability Boundary in LLMs' Math Reasoning
|
Yes
|
Yes
| 2,024
|
[] |
70
|
OpenMath-CodeLlama-7B (w/ code)
| 43.6
| 7
|
Yes
|
OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset
|
Yes
|
No
| 2,024
|
[] |
71
|
Shepherd+Mistral-7B (SFT on MetaMATH + PRM RL+ PRM rerank, k=256)
| 43.5
| 7
|
Yes
|
Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotations
|
Yes
|
No
| 2,023
|
[
"rerank"
] |
72
|
DART-Math-Mistral-7B-Uniform (0-shot CoT, w/o code)
| 43.5
| 7
|
Yes
|
DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving
|
Yes
|
Yes
| 2,024
|
[] |
73
|
Minerva 62B (maj1@k, k=64)
| 43.4
| 62
|
No
|
Solving Quantitative Reasoning Problems with Language Models
|
Yes
|
Yes
| 2,022
|
[
"majority voting"
] |
74
|
ToRA 13B (w/ code)
| 43
| 13
|
Yes
|
ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving
|
Yes
|
Yes
| 2,023
|
[
"code environment",
"gpt-4 distillation"
] |
75
|
GPT-4
| 42.5
| null |
No
|
Sparks of Artificial General Intelligence: Early experiments with GPT-4
|
Yes
|
Yes
| 2,023
|
[] |
76
|
SFT-Mistral-7B
| 41.8
| 7
|
Yes
| 2,024
|
[] |
|||
77
|
Llama2-13B-KPMath-Plus
| 41
| 13
|
No
|
Key-Point-Driven Data Synthesis with its Enhancement on Mathematical Reasoning
| 2,024
|
[] |
||
78
|
ToRA 7B (w/ code)
| 40.1
| 7
|
Yes
|
ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving
|
Yes
|
Yes
| 2,023
|
[
"code environment",
"gpt-4 distillation"
] |
79
|
MathCoder-CL-13B
| 35.9
| 13
|
Yes
|
MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning
|
Yes
|
No
| 2,023
|
[] |
80
|
MuggleMATH-70B
| 35.6
| 70
|
Yes
|
MuggleMath: Assessing the Impact of Query and Response Augmentation on Math Reasoning
|
Yes
|
No
| 2,023
|
[] |
81
|
PaLM 2 (few-shot, k=4, CoT)
| 34.3
| null |
No
|
PaLM 2 Technical Report
|
Yes
|
No
| 2,023
|
[] |
82
|
Minerva 540B
| 33.6
| 540
|
No
|
Solving Quantitative Reasoning Problems with Language Models
|
Yes
|
No
| 2,022
|
[] |
83
|
Minerva 540B (5-shot)
| 33.6
| 540
|
No
|
Galactica: A Large Language Model for Science
|
Yes
|
No
| 2,022
|
[] |
84
|
Shepherd + Mistral-7B (SFT on MetaMATH + PRM RL)
| 33
| 7
|
Yes
|
Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotations
|
Yes
|
No
| 2,023
|
[] |
85
|
WizardMath-7B-V1.1
| 33
| 7
|
Yes
|
WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct
|
Yes
|
No
| 2,023
|
[] |
86
|
Gemini Pro (4-shot)
| 32.6
| null |
No
|
Gemini: A Family of Highly Capable Multimodal Models
|
Yes
|
Yes
| 2,023
|
[] |
87
|
MuggleMATH-13B
| 30.7
| 13
|
Yes
|
MuggleMath: Assessing the Impact of Query and Response Augmentation on Math Reasoning
|
Yes
|
No
| 2,023
|
[] |
88
|
MathCoder-CL-7B
| 30.2
| 7
|
Yes
|
MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning
|
Yes
|
No
| 2,023
|
[] |
89
|
MathCoder-L-13B
| 29.9
| 13
|
Yes
|
MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning
|
Yes
|
No
| 2,023
|
[] |
90
|
Qwen2idae-16x14B (4-shot)
| 29.9
| null |
Yes
|
Parameter-Efficient Sparsity Crafting from Dense to Mixture-of-Experts for Instruction Tuning on General Tasks
|
Yes
|
No
| 2,024
|
[] |
91
|
OpenChat-3.5-1210 7B
| 28.9
| 7
|
No
|
OpenChat: Advancing Open-source Language Models with Mixed-Quality Data
|
Yes
|
No
| 2,023
|
[] |
92
|
OpenChat-3.5 7B
| 28.6
| 7
|
No
|
OpenChat: Advancing Open-source Language Models with Mixed-Quality Data
|
Yes
|
No
| 2,023
|
[] |
93
|
Mixtral 8x7B (maj@4)
| 28.4
| null |
No
|
Mixtral of Experts
|
Yes
|
Yes
| 2,024
|
[] |
94
|
Minerva 62B (4-shot)
| 27.6
| 62
|
No
|
Solving Quantitative Reasoning Problems with Language Models
|
Yes
|
Yes
| 2,022
|
[] |
95
|
MetaMath 70B
| 26
| 70
|
Yes
|
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
|
Yes
|
No
| 2,023
|
[
"fine-tuned"
] |
96
|
MuggleMATH 7B
| 25.8
| 7
|
Yes
|
MuggleMath: Assessing the Impact of Query and Response Augmentation on Math Reasoning
|
Yes
|
No
| 2,023
|
[] |
97
|
Minerva 8B (maj1@k, k=64)
| 25.4
| 8
|
No
|
Solving Quantitative Reasoning Problems with Language Models
|
Yes
|
Yes
| 2,022
|
[
"majority voting"
] |
98
|
MathCoder-L-7B
| 23.3
| 7
|
Yes
|
MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning
|
Yes
|
No
| 2,023
|
[] |
99
|
WizardMath-70B-V1.0
| 22.7
| 70
|
Yes
|
WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct
|
Yes
|
No
| 2,023
|
[] |
100
|
Camelidae-8×34B (4-shot)
| 22.6
| null |
Yes
|
Parameter-Efficient Sparsity Crafting from Dense to Mixture-of-Experts for Instruction Tuning on General Tasks
|
Yes
|
No
| 2,024
|
[] |
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