← All models
Meta · dense · Llama 3.3 Community License
What runs Llama 3.3 70B Instruct
Dense 70B model from December 2024. The classic two-24 GB-GPU workload and the usual yardstick for dense-model memory bandwidth.
- Parameters
- 70B
- 4-bit file
- 39.6 GB
- Q4_K_M
- Needs at 8k context
- 43.6 GB
- Longest context
- 131,072 tokens
Context memory: 327,680 bytes per token. Standard GQA: 2 x 80 layers x 8 KV heads x 128 head dim x 2 bytes (fp16). How context memory works.
Measured on this hardware
Machines that hold the 4-bit file with 8,192 tokens of context and have published runs on the same chip or cards, fastest first. Median of single-user runs with plain decoding.
| Machine | Fit | Price | Generation |
|---|---|---|---|
| Dell Pro Max Tower T2 with NVIDIA RTX PRO 6000 BlackwellNVIDIA workstation | Fits | ~$13,909 | 32 tok/smedian of 1 run |
| 1x RTX PRO 6000 BlackwellSingle GPU | Fits | ~$20,833 | 32 tok/smedian of 1 run |
| Apple Mac Studio (M5 Ultra, 64-core GPU)Apple unified memory | Fitsassumed limitfrom 96 GB | ~$5,499–$9,499 | 24 tok/smedian of 3 runs |
| 2x RTX 3090 (used)Multi-GPU | Fits | ~$3,639 + unpriced parts | 20 tok/smedian of 1 run |
| Apple Mac Studio (M5 Max, 40-core GPU)Apple unified memory | Fitsassumed limitfrom 64 GB | ~$3,099–$5,099 | 13 tok/smedian of 3 runs |
| Apple MacBook Pro 14-inch (M5 Max, 40-core GPU)Apple unified memory | Fitsassumed limitfrom 64 GB | ~$4,699–$6,699 | 13 tok/smedian of 3 runs |
| Apple MacBook Pro 16-inch (M5 Max, 40-core GPU)Apple unified memory | Fitsassumed limitfrom 64 GB | ~$4,999–$6,999 | 13 tok/smedian of 3 runs |
| Apple Mac mini (M5 Pro, 20-core GPU)Apple unified memory | Fitsassumed limitfrom 64 GB | ~$1,899–$2,899 | 6.9 tok/smedian of 3 runs |
| Framework Desktop (Ryzen AI Max+ 395)AMD unified memory | Fitsassumed limitfrom 64 GB | ~$1,959–$3,449 | 4.8 tok/smedian of 4 runs |
| GMKtec EVO-X2 (Ryzen AI Max+ 395)AMD unified memory | Fitsassumed limitfrom 64 GB | ~$2,600–$4,000 | 4.8 tok/smedian of 4 runs |
| Beelink GTR9 Pro (Ryzen AI Max+ 395)AMD unified memory | Fits | ~$4,699 | 4.8 tok/smedian of 4 runs |
| Minisforum MS-S1 MAX (Ryzen AI Max+ 395)AMD unified memory | Fits | ~$4,899 | 4.8 tok/smedian of 4 runs |
| Corsair AI Workstation 300 (Ryzen AI Max+ 395)AMD unified memory | Fits | ~$4,800 | 4.8 tok/smedian of 4 runs |
| HP Z2 Mini G1a (Ryzen AI Max+ PRO 395)AMD unified memory | Fits | ~$4,999 | 4.8 tok/smedian of 4 runs |
Estimated, not measured
These fit but nobody has published a run we could match. The figure is memory bandwidth divided by the bytes read per token, scaled by the share of that ceiling measured runs reach. How estimates work.
| Machine | Fit | Price | Generation |
|---|---|---|---|
| Dell Pro Precision with GB300NVIDIA workstation | Fits | ~$159,283 | ~113–136 tok/sestimate |
| 2x RTX 5090Multi-GPU | Fits | ~$4,109 + unpriced parts | ~21–32 tok/sestimate |
| Apple Mac Studio (M5 Ultra, 80-core GPU)Apple unified memory | Fitsassumed limitfrom 96 GB | ~$6,799–$10,799 | ~21–26 tok/sestimate |
| RTX 5090 + EPYC 9355P with 768 GB DDR5 (MoE offload)Hybrid GPU + RAM | GPU + RAM offloadassumed limit | ~$3,763 + unpriced parts | ~13–21 tok/sestimate, part in RAM |
| 4x Instinct MI50 32GB (used) on EPYC 7003Multi-GPU | Fits | ~$1,998 + unpriced parts | ~12–19 tok/sestimate |
| 2x Radeon RX 7900 XTXMulti-GPU | Fits | ~$5,637 | ~11–17 tok/sestimate |
| 4x RTX 3090 (used) on EPYC 7003, open frameMulti-GPU | Fits | ~$2,178 + unpriced parts | ~11–17 tok/sestimate |
| tiny corp tinybox red flashGPU desktop (prebuilt) | Fits | ~$22,000 | ~7.4–12 tok/sestimate |
| 2x Intel Arc Pro B60Multi-GPU | Fits | ~$4,367 | ~5.3–8.3 tok/sestimate |
| Apple Mac mini (M5 Pro, 16-core GPU)Apple unified memory | Fitsassumed limitfrom 64 GB | ~$1,699–$2,699 | ~5.3–6.6 tok/sestimate |
| Framework Desktop (Ryzen AI Max+ PRO 495)AMD unified memory | Fitsassumed limit | ~$6,799 | ~4.4–5.2 tok/sestimate |
| NVIDIA DGX SparkNVIDIA GB10 | Fitsassumed limit | ~$4,699 | ~4.4–5.2 tok/sestimate |
| Dell Pro Precision with GB10NVIDIA GB10 | Fitsassumed limit | ~$5,523 | ~4.4–5.2 tok/sestimate |
| RTX 3090 (used) + 128 GB DDR5 on AM5 (MoE offload)Hybrid GPU + RAM | GPU + RAM offloadassumed limit | ~$4,833 + unpriced parts | ~2.1–3.4 tok/sestimate, part in RAM |
Fits, no speed figure
Too large for
Apple Mac Studio (M5 Max, 32-core GPU), Apple MacBook Pro 14-inch (M5 Max, 32-core GPU), Apple MacBook Pro 16-inch (M5 Max, 32-core GPU), Framework Desktop (Ryzen AI Max 385), 1x RTX 3090 (used), 1x RTX 5090. A smaller quant may fit: try the calculator.
Files
| Quant | Format | Size | Repo |
|---|---|---|---|
| 4bit | MLX | 37.0 GB | mlx-community/Llama-3.3-70B-Instruct-4bit |
| Q4_K_M | GGUF | 39.6 GB | unsloth/Llama-3.3-70B-Instruct-GGUF |
| Q5_K_M | GGUF | 46.5 GB | unsloth/Llama-3.3-70B-Instruct-GGUF |
| Q6_K | GGUF | 53.9 GB | unsloth/Llama-3.3-70B-Instruct-GGUF |
| 8bit | MLX | 69.8 GB | mlx-community/Llama-3.3-70B-Instruct-8bit |
| Q8_0 | GGUF | 69.8 GB | unsloth/Llama-3.3-70B-Instruct-GGUF |
Sources
- huggingface.co: model card: params, context, license, attention layout, description
- huggingface.co: downloads (last 30 days), license tag, safetensors param count
- huggingface.co: layer count, KV heads and head size (public mirror of the original weights)
- huggingface.co: GGUF file sizes (shards summed)
- huggingface.co: MLX 4bit safetensors sizes
- huggingface.co: MLX 8bit safetensors sizes