Llama 3.2 11B Vision
Llama 3.2 11B Vision is worth evaluating for rag, long context, and vision when its provider route and context window match the workload.
Use it for
- Teams evaluating rag, long context, and vision
- Workloads that can use a 128k context window
- Buyers comparing 1 tracked provider route
Do not use it for
- Workloads where another current model has stronger sourced task evidence
- Family
- Llama 3.2
- Released
- 2024-09-25
- Context
- 128k
- Parameters
- 10.6B
- Architecture
- Decoder Only
- Knowledge cutoff
- 2024-03
- Specialization
- general
- Training
- finetuned
Large-scale open-source AI for social technologies.
Cheapest of 1 route · AWS Bedrock
About
Multimodal 11B parameter model balancing capability and computational efficiency
Llama 3.2 11B Vision is an open-source model in the Llama 3.2 family. The structured metadata tracks a 128k-token context window, vision, and structured outputs. This page tracks provider routes through AWS Bedrock, with the cheapest tracked route listed at $0.2 input and $0.27 output per 1M tokens. Headline tracked benchmarks include Massive Multi-discipline Multimodal Understanding 50.7 and MMLU PRO 46.4.
Top use-case fit
RAG
Included by capability and metadata signals in the decision map.
Long context
Included by capability and metadata signals in the decision map.
Vision
Q/$ A1 relevant benchmark in the decision map.
Provider price ladder
Compare API pricing across 1 providers for input and output tokens, batch, and cached reads when available.
| Provider | Input / 1M | Output / 1M | Route |
|---|---|---|---|
| AWS Bedrock | $0.200 | $0.270 | Serverless |
Capabilities
Benchmark peer barsfor Vision
Benchmark scores(2)
| Benchmark | Score | Version | Source |
|---|---|---|---|
| Massive Multi-discipline Multimodal Understanding | 50.7 | — | https://mmmu-benchmark.github.io/ |
| MMLU PRO | 46.4 | — | https://huggingface.co/spaces/TIGER-Lab/MMLU-Pro |
Migration checks
No linked migration route is available for this model yet.