Llama 3.2 Instruct 11B (Vision)
Llama 3.2 Instruct 11B (Vision)
The Llama 3.2 11B Vision Instruction Model is a multimodal large language model optimized for visual recognition, image reasoning, image description generation, and answering general questions about images. This model takes text and images as input and generates text as output.
Intelligence(Relatively Weak)
Speed(Medium)
Input Supported Modalities
Yes
Is Reasoning Model
128,000
Context Window
128,000
Maximum Output Tokens
2023-12-31
Knowledge Cutoff
Pricing
¥0.43 /M tokens
Input
¥0.43 /M tokens
Output
¥1.15 /M tokens
Blended Price
Quick Simple Comparison
Llama 4 Scout
¥0.08
Llama 4 Maverick
¥0.17
Llama 3.3 Instruct 70B
¥0.2
Basic Parameters
GPT-4.1 Technical Parameters
Parameter Count
10,600.0M
Context Length
128.00k tokens
Training Data Cutoff
2023-12-31
Open Source Category
Open Weights (Permissive License)
Multimodal Support
Text, Image
Throughput
168
Release Date
2024-09-25
Response Speed
109.052,444 tokens/s
Benchmark Scores
Below is the performance of claude-monet in various standard benchmark tests. These tests evaluate the model's capabilities in different tasks and domains.
Intelligence Index
2504
Large Language Model Intelligence Level
Coding Index
-
Indicator of AI model performance on coding tasks
Math Index
-
Capability indicator in solving mathematical problems, mathematical reasoning, or performing math-related tasks
MMLU Pro
46.4
Massive Multitask Multimodal Understanding - Testing understanding of text, images, audio, and video
GPQA
22.1
Graduate Physics Questions Assessment - Testing advanced physics knowledge with diamond science-level questions
HLE
5.2
The model's comprehensive average score on the Hugging Face Open LLM Leaderboard
LiveCodeBench
11
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
68.7
Score achieved by the AI model on the specific HumanEval benchmark test set
Math 500 Score
51.6
Score on the first 500 larger, more well-known mathematical benchmark tests
AIME Score
9.3
An indicator measuring an AI model's ability to solve high-difficulty mathematical competition problems (specifically AIME level)
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