Context Window
131,072
Tokens
Model Cost Profile
Developer: meta-llama
Pricing updated Mar 11, 2026
Live Pricing
Input: $0.0490
Output: $0.0490
Pricing via OpenRouter API ยท Last synced Mar 11, 2026 ยท MMLU score via public benchmark data
Meta: Llama 3.2 11B Vision Instruct is designed for teams needing advanced visual understanding and instruction-following capabilities, making it ideal for applications in image analysis and interactive AI systems. With an extensive context window of 131072 tokens, this model supports complex tasks that require significant contextual information, enhancing performance in scenarios like document summarization and multi-turn conversations. At a competitive pricing of $0.05 per million tokens for both input and output, it offers a cost-effective solution for businesses looking to integrate sophisticated AI functionalities into their workflows.
Context Window
131,072
Tokens
Input Price / 1M
$0.0490
Prompt tokens
Output Price / 1M
$0.0490
Completion tokens
Intelligence (MMLU)
46.4
Massive Multitask Language Understanding
Standardized evaluation scores for Meta: Llama 3.2 11B Vision Instruct.
| Usage Type | Price / 1M Tokens |
|---|---|
| Input (Prompt) | $0.0490 |
| Output (Completion) | $0.0490 |
Price History
Current Input / 1M
$0.0490
Current Output / 1M
$0.0490
Estimate monthly spend for Meta: Llama 3.2 11B Vision Instruct based on your workload.
Estimated Monthly Cost
$1.81
25M input + 12M output tokens
Quick links for cost-down decisions before production rollout.
Common pricing and benchmark questions for Meta: Llama 3.2 11B Vision Instruct.
Meta: Llama 3.2 11B Vision Instruct input pricing is $0.0490 per 1M tokens based on the latest synced provider data.
Meta: Llama 3.2 11B Vision Instruct output pricing is $0.0490 per 1M tokens based on the latest synced provider data.
Meta: Llama 3.2 11B Vision Instruct supports a context window of 131,072 tokens.
Use the comparison links on this page to open direct model-vs-model pricing and benchmark pages, then evaluate monthly spend projections for your workload.