Meta: Llama 3.3 70B Instruct
Meta
Capabilities
Strengths
- Open weights enable full self-hosting and data privacy
- Large context window (131K) excellent for long documents
- Strong multilingual capabilities across tasks
- Affordable mid-tier pricing for open-weight model
Weaknesses
- Slow inference speed (96 tok/s) limits real-time applications
- Weak coding and reasoning performance (0.3, 0.27)
- No vision capability for multimodal tasks
- Limited mathematical reasoning (0.39 fitness)
Pricing
Input / 1M tokens
$0.09999999999999999
Output / 1M tokens
$0.32
Context window
131.072k
Transparency
Open weights
10.0 / 10
Open training data
0.0 / 10
Open methodology
7.5 / 10
Licence openness
6.0 / 10
Provider disclosure
7.0 / 10
FMTI company score
N/A
Llama 3.3 ships with publicly downloadable weights under Meta's Llama License. Meta publishes detailed model cards and training methodology. Training data composition not fully disclosed. Strong open-weight positioning enables self-hosting and full data privacy control.
Sustainability
Inference energy
N/A
Training footprint
N/A
Provider infrastructure
5.5 / 10
70B parameter count suggests moderate inference energy relative to flagship models. Meta's infrastructure sustainability metrics not widely published. Self-hosting capability reduces reliance on provider infrastructure but does not offset unknown training footprint.