ChatCodingReasoningMulti-Purpose70.6B
Llama 3.3 70B Instruct
Llama · Llama 3.3 Community License
Flagship Llama 3.3 model with best-in-class general and coding performance.
- Parameters
- 70.6B
- Context
- 131,072 tokens
- Released
- 2024-12-06
- Engines
- llama.cpp, ollama, vLLM, TGI
- Builder Tools
- Cursor, Continue, Aider, Open WebUI, LM Studio
Llama 3.3 70B Instruct (70.6B) requires 61 GB VRAM at recommended quality (Q6_K). On NVIDIA GeForce RTX 5090, expect approximately 12 tok/s at Q4_K_M. For the best experience, Mac Studio AI Builder ($3,999) is recommended.
— OwnRig methodology, data updated 2026-03-15
VRAM Requirements
| Quality | Quantization | VRAM | File Size |
|---|---|---|---|
| full | Q8_0 | 78 GB | 70 GB |
| recommended | Q6_K | 61 GB | 52 GB |
| recommended | Q5_K_M | 51 GB | 43 GB |
| efficient | Q4_K_M | 41 GB | 35 GB |
| compressed | Q3_K_M | 33 GB | 27 GB |
Context Length Impact
KV cache VRAM at Q6_K quality. Longer context = more memory.
| Context | KV Cache | Total VRAM |
|---|---|---|
| 2K | 1.2 GB | 62.2 GBexceeds 24 GB |
| 4K | 2.3 GB | 63.3 GBexceeds 24 GB |
| 8K | 4.6 GB | 65.6 GBexceeds 24 GB |
| 16K | 9.2 GB | 70.2 GBexceeds 24 GB |
| 32K | 18.4 GB | 79.4 GBexceeds 24 GB |
| 64K | 36.9 GB | 97.9 GBexceeds 24 GB |
| 128K | 73.7 GB | 134.7 GBexceeds 24 GB |
Compatible GPUs
Performance data for Llama 3.3 70B Instruct across different hardware.
| Device | Quantization | Speed | Rating | Fits in VRAM |
|---|---|---|---|---|
| NVIDIA GeForce RTX 4090 | Q3_K_M | 6 tok/s | Marginal | ✗ (offload) |
| Apple M4 Max (64GB Unified) | Q3_K_M | 7 tok/s | Acceptable | ✓ |
| Apple M4 Max (128GB Unified) | Q4_K_M | 7 tok/s | Acceptable | ✓ |
| NVIDIA GeForce RTX 5090 | Q4_K_M | 12 tok/s | Good | ✓ |
| NVIDIA GeForce RTX 4060 8GB | Q2_K | — | Not Viable | ✗ (offload) |
| NVIDIA GeForce RTX 4070 Ti 12GB | Q2_K | — | Not Viable | ✗ (offload) |
| NVIDIA GeForce RTX 3080 10GB | Q2_K | — | Not Viable | ✗ (offload) |
| Apple M3 Pro (18GB Unified) | Q2_K | — | Not Viable | ✗ (offload) |
Builder Context
Llama 3.3 70B Instruct is commonly used with Cursor, Continue, Aider, Open WebUI, LM Studio. For an AI coding workflow, pair it with an embedding model like nomic-embed-text for local RAG.
Recommended Builds
Complete PC builds that can run Llama 3.3 70B Instruct.
Frequently Asked Questions
- How much VRAM does Llama 3.3 70B Instruct need?
- Llama 3.3 70B Instruct requires 61 GB VRAM at recommended quality (Q6_K). At lower quality settings, it can fit in as little as 33 GB.
- What is the best GPU for Llama 3.3 70B Instruct?
- The NVIDIA GeForce RTX 5090 delivers the best performance for Llama 3.3 70B Instruct, achieving 12 tok/s at Q4_K_M with an good rating.
- What quantization should I use for Llama 3.3 70B Instruct?
- For the best quality, use Q6_K (61 GB VRAM). If your GPU has limited VRAM, Q3_K_M (33 GB) is the most efficient option with acceptable quality.
- Is Llama 3.3 70B Instruct good for coding?
- Yes. Llama 3.3 70B Instruct is used with Cursor, Continue, Aider, Open WebUI, LM Studio for local AI coding. For the best coding experience, pair it with an embedding model for local RAG.
Data confidence: estimated. Last updated: 2026-03-15. Source