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Llama 3.1 is available in three versions:
| Model | Description | Download |
|---|---|---|
| 405B | Flagship foundation model for widest variety of use cases | Download |
| 70B | Highly performant, cost-effective model for diverse use cases | Download |
| 8B | Light-weight, ultra-fast model that can run anywhere | Download |
Key Capabilities
- Tool Use: Ability to analyze uploaded datasets, plot graphs, and fetch market data.
- Multi-lingual Agents: Capable of translation tasks (e.g., translating stories into different languages).
- Complex Reasoning: Can handle multi-step reasoning tasks and basic arithmetic.
- Coding Assistants: Able to generate complex code, including algorithms for specific tasks.
Ecosystem and Services
Llama 3.1 offers a range of services to support various use cases:
- Inference:
- Real-time inference
- Batch inference
- Downloadable model weights for cost optimization
- Fine-tune, Distill & Deploy:
- Adaptation for specific applications
- Improvement with synthetic data
- On-premises or cloud deployment options
- RAG & Tool Use:
- Zero-shot tool use
- Retrieval-Augmented Generation (RAG) for building agentic behaviors
- Synthetic Data Generation:
- Leverage 405B model for high-quality data generation
- Improve specialized models for specific use cases
Partner Features
Features available for 405B models through partners:
- Real-time inference
- Batch inference
- Fine-tuning
- Model evaluation
- RAG
- Continual pre-training
- Safety guardrails
- Synthetic data generation
- Distillation recipe
Model Evaluations
Performance comparison across various benchmarks:
| Benchmark Category | Benchmark Name | Llama 3.1 8B | Llama 3.1 70B | Llama 3.1 405B |
|---|---|---|---|---|
| General | MMLU (CoT) | 73.0 | 86.0 | 88.6 |
| MMLU PRO (5-shot, CoT) | 48.3 | 66.4 | 73.3 | |
| IFEval | 80.4 | 87.5 | 88.6 | |
| Code | HumanEval (0-shot) | 72.6 | 80.5 | 89.0 |
| MBPP EvalPlus (base) (0-shot) | 72.8 | 86.0 | 88.6 | |
| Math | GSM8K (8-shot, CoT) | 84.5 | 95.1 | 96.8 |
| MATH (0-shot, CoT) | 51.9 | 68.0 | 73.8 | |
| Reasoning | ARC Challenge (0-shot) | 83.4 | 94.8 | 96.9 |
| GPQA (0-shot, CoT) | 32.8 | 46.7 | 51.1 | |
| Tool use | API-Bank (0-shot) | 82.6 | 90.0 | 92.3 |
| BFCL | 76.1 | 84.8 | 88.5 | |
| Gorilla Benchmark API Bench | 8.2 | 29.7 | 35.3 | |
| Nexus (0-shot) | 38.5 | 56.7 | 58.7 | |
| Multilingual | Multilingual MGSM | 68.9 | 86.9 | 91.6 |