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Solar Pro 2 (Reasoning)
Reasoning-enhanced version of Solar Pro 2, optimized for complex multi-step logical thinking tasks. Features dedicated reasoning mode capable of structured thinking and multi-step task execution, supports agentic workflows. Excels in mathematical reasoning, code generation, and complex problem-solving, ideal for high-difficulty applications requiring deep thinking and step-by-step reasoning.
Intelligence(Medium)
Speed(Slow)
Input Supported Modalities
Yes
Is Reasoning Model
65,536
Context Window
-
Maximum Output Tokens
-
Knowledge Cutoff
Pricing
- /M tokens
Input
- /M tokens
Output
￥3.6 /M tokens
Blended Price
Quick Simple Comparison
Solar Pro 2
Solar Pro 2 (Reasoning)
Solar Pro 2 (Preview)
Basic Parameters
Solar Pro 2 (Reasoning)Technical Parameters
Parameter Count
Not Announced
Context Length
65.54k tokens
Training Data Cutoff
Open Source Category
Proprietary
Multimodal Support
Text Only
Throughput
Release Date
2025-07-09
Response Speed
0 tokens/s
Benchmark Scores
Below is the performance of Solar Pro 2 (Reasoning) in various standard benchmark tests. These tests evaluate the model's capabilities in different tasks and domains.
Intelligence Index
58.21
Large Language Model Intelligence Level
Coding Index
45.9
Indicator of AI model performance on coding tasks
Math Index
82.83
Capability indicator in solving mathematical problems, mathematical reasoning, or performing math-related tasks
MMLU Pro
80.5
Massive Multitask Multimodal Understanding - Testing understanding of text, images, audio, and video
GPQA
68.7
Graduate Physics Questions Assessment - Testing advanced physics knowledge with diamond science-level questions
HLE
7
The model's comprehensive average score on the Hugging Face Open LLM Leaderboard
LiveCodeBench
61.6
Specific evaluation focused on assessing large language models' ability in real-world code writing and solving programming competition problems
SciCode
30.2
The model's capability in code generation for scientific computing or specific scientific domains
HumanEval
96.8
Score achieved by the AI model on the specific HumanEval benchmark test set
Math 500 Score
96.7
Score on the first 500 larger, more well-known mathematical benchmark tests
AIME Score
69
An indicator measuring an AI model's ability to solve high-difficulty mathematical competition problems (specifically AIME level)
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