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ERNIE 4.5 Turbo 128K
百度が開発した次世代のマルチモーダル推論モデルで、ERNIE 4.0アーキテクチャをベースに128Kの超長コンテキストウィンドウを拡張し、クロスモーダルの意味関連と複雑な長文生成をサポートします。入力価格は基礎モデルより50%低下し、総合性能はDeepSeek V3と同レベルに達しています。
Intelligence(Medium)
Speed(Slow)
Input Supported Modalities
Yes
Is Reasoning Model
128,000
Context Window
128,000
Maximum Output Tokens
2024-10-31
Knowledge Cutoff
Pricing
￥4 /M tokens
Input
￥16 /M tokens
Output
￥7 /M tokens
Blended Price
Quick Simple Comparison
ERNIE-4.5-Turbo
￥0.56
ERNIE-4.5-Turbo-128K
￥0.56
ERNIE-X1-Turbo-32K
￥0.28
Basic Parameters
ERNIE-4.5-Turbo-128KTechnical Parameters
Parameter Count
Not Announced
Context Length
128.00k tokens
Training Data Cutoff
2024-10-31
Open Source Category
Proprietary
Multimodal Support
Text, Image
Throughput
0
Release Date
2025-03-17
Response Speed
0 tokens/s
Benchmark Scores
Below is the performance of ERNIE-4.5-Turbo-128K in various standard benchmark tests. These tests evaluate the model's capabilities in different tasks and domains.
Intelligence Index
52.3
Large Language Model Intelligence Level
Coding Index
69.7
Indicator of AI model performance on coding tasks
Math Index
85.6
Capability indicator in solving mathematical problems, mathematical reasoning, or performing math-related tasks
MMLU Pro
-
Massive Multitask Multimodal Understanding - Testing understanding of text, images, audio, and video
GPQA
-
Graduate Physics Questions Assessment - Testing advanced physics knowledge with diamond science-level questions
HLE
-
The model's comprehensive average score on the Hugging Face Open LLM Leaderboard
LiveCodeBench
-
Specific evaluation focused on assessing large language models' ability in real-world code writing and solving programming competition problems
SciCode
-
The model's capability in code generation for scientific computing or specific scientific domains
HumanEval
-
Score achieved by the AI model on the specific HumanEval benchmark test set
Math 500 Score
-
Score on the first 500 larger, more well-known mathematical benchmark tests
AIME Score
-
An indicator measuring an AI model's ability to solve high-difficulty mathematical competition problems (specifically AIME level)
GPT 5 Mini
openai
￥1.8
Input tokens/million
￥14.4
Output tokens/million
400k
Context Length
GPT 5 Standard
openai
￥63
Input tokens/million
￥504
Output tokens/million
400k
Context Length
GPT 5 Nano
openai
￥0.36
Input tokens/million
￥2.88
Output tokens/million
400k
Context Length
GPT 5
openai
￥9
Input tokens/million
￥72
Output tokens/million
400k
Context Length
GLM 4.5
chatglm
￥0.43
Input tokens/million
￥1.01
Output tokens/million
131k
Context Length
Gemini 1.0 Pro
google
￥3.6
Input tokens/million
￥10.8
Output tokens/million
33k
Context Length
Gemini 2.0 Flash Lite (Preview)
google
￥0.58
Input tokens/million
￥2.16
Output tokens/million
1M
Context Length
GPT 4
openai
￥216
Input tokens/million
￥432
Output tokens/million
8192
Context Length