Compare
Llama 3.3 70B Instruct vs Llama 3.1 8B Instruct
Same hardware, same arithmetic, side by side. Every memory figure is calculated from published model geometry rather than quoted from a marketing page.
Estimated
Side by side
On GeForce RTX 4090
| Property | Llama 3.3 70B Instruct | Llama 3.1 8B Instruct |
|---|---|---|
| Organization | Meta | Meta |
| Parameters | 70.6B | 8B |
| Architecture | Llama · dense | Llama · dense |
| Context | 128k | 128k |
| Layers | 80 | 32 |
| Hidden size | 8,192 | 4,096 |
| KV heads | 8 of 64 | 8 of 32 |
| Licence | Llama 3.3 Community License | Llama 3.1 Community License |
| Commercial use | Yes | Yes |
| Modalities | text | text |
| Released | 2024-12-06 | 2024-07-23 |
| Recommended quantization | Q4_K_M | Q8_0 |
| Memory needed | 44 GB | 9.5 GB |
| Estimated tok/s | 18 | 92 |
| Fit | Runs with CPU offload | Excellent fit |
| Fine-tune here | No | Yes |
| MMLU (reported) | 86% | 69.4% |
| HUMANEVAL (reported) | 88.4% | 72.6% |
Benchmark rows are figures the model's authors published, not ModelLM measurements, and the two models may not have been evaluated under identical conditions.
Trade-offs
Llama 3.3 70B Instruct
Delivers close to Llama 3.1 405B quality at a size a dual-GPU workstation or 64 GB Mac can actually hold.
Strengths
- Top-tier open general quality
- 128k context
- Broad tooling support
Limitations
- Needs 48 GB+ for comfortable use
- Local fine-tuning is a multi-GPU exercise
Llama 3.1 8B Instruct
The most widely supported open model there is. If a tool, adapter or tutorial exists, it was written for this one first.
Strengths
- Unmatched ecosystem support
- 128k context
- Very stable fine-tuning behaviour
Limitations
- Benchmarks now behind newer 7–9B models
- Community licence with an acceptable-use policy
Common comparisons