Apple M3 (8GB)
The Apple M3 (8GB) has 8 GB VRAM and 100 GB/s memory bandwidth. It can run 0 of our 80 tracked models natively in VRAM at 8k context.
With 8 GB LPDDR5, the Apple M3 (8GB) is a laptop-tier GPU that can run 0 models natively. It's best for smaller models under 8B parameters.
Apple M3 (8GB): 8GB at 100 GB/s — base M3.
7B at Q4 tight. ~3-6 t/s for 7B.
8GB is minimum — consider 16GB+.
| Vendor | Apple |
| Architecture | Apple M3 |
| CPU cores | 8 (4P + 4E) |
| VRAM | 8 GB (unified) |
| Memory type | LPDDR5 |
| Memory bandwidth | 100 GB/s |
| Compute backend | METAL |
| Tier | Laptop |
| Released | 2023 |
| Models (native) | 0 / 80 |
| Models (offload) | 0 / 80 |
Software: MLX gives the best performance on Apple Silicon; llama.cpp Metal backend is a solid alternative. Both are well-supported by Ollama.
Models this GPU runs natively in VRAM (0)
None.
Too large for this GPU (80)
- Llama 3.3 70B Instruct
- Llama 3.1 8B Instruct
- Llama 3.2 3B Instruct
- Llama 3.2 1B Instruct
- Qwen 2.5 72B Instruct
- Qwen 2.5 32B Instruct
- Qwen 2.5 14B Instruct
- Qwen 2.5 7B Instruct
- Qwen 2.5 3B Instruct
- Qwen 2.5 Coder 32B Instruct
- Mistral Small 22B
- Mistral Nemo 12B Instruct
- Mistral 7B Instruct v0.3
- Mixtral 8x7B Instruct v0.1
- Gemma 2 27B Instruct
- Gemma 2 9B Instruct
- Gemma 2 2B Instruct
- Phi-3.5 Mini Instruct
- DeepSeek R1 Distill Llama 70B
- DeepSeek R1 Distill Qwen 32B
- DeepSeek R1 Distill Llama 8B
- Command-R 35B
- Yi 1.5 34B Chat
- SmolLM2 1.7B Instruct
- SmolLM2 360M Instruct
- Llama 3.1 70B Instruct
- Qwen 2.5 1.5B Instruct
- Qwen 2.5 0.5B Instruct
- Mixtral 8x22B Instruct v0.1
- Llama 3.1 405B Instruct
- Phi-4 14B Instruct
- DeepSeek V3 671B
- DeepSeek R1 671B
- Mistral Small 3.1 24B Instruct
- Gemma 3 27B Instruct
- Gemma 3 12B Instruct
- Gemma 3 4B Instruct
- Gemma 3 1B Instruct
- Llama 4 Scout 109B
- Llama 4 Maverick 400B
- Qwen3 235B-A22B (MoE)
- Qwen3 30B-A3B (MoE)
- Qwen3 32B
- Qwen3 14B
- Qwen3 8B
- MiniMax M1 456B
- GPT-OSS 120B
- GPT-OSS 20B
- GLM-4.5 355B
- GLM-4.5 Air 106B
- GLM-4.6 355B
- GLM-4.6V 106B
- Nemotron 3 Nano 30B
- GLM-4.7 358B
- Gemma 4 31B
- Gemma 4 26B (MoE)
- Gemma 4 E4B
- Gemma 4 E2B
- Qwen 3.5 35B-A3B (MoE)
- Qwen 3.5 122B-A10B (MoE)
- MiniMax M2.5 229B
- GLM-5 744B
- MiniMax M2.7 229B
- Nemotron 3 Super 120B
- Qwen 3.6 27B
- Qwen 3.6 35B
- Kimi K2.6
- GLM-5.1 754B
- DeepSeek V4 Pro 1.6T
- DeepSeek V4 Flash 284B
- Gemma 4 12B (Unified)
- GLM-5.2 753B
- Nemotron 3 Ultra 550B-A55B
- Step 3.5 Flash
- Step 3.7 Flash
- MiMo V2.5 Pro
- Kimi K2.5
- MiniMax M3
- Inkling
- Bonsai 27B
Frequently asked questions
- How much VRAM does the Apple M3 (8GB) have?
- The Apple M3 (8GB) has 8 GB of LPDDR5 with 100 GB/s memory bandwidth (unified system memory, shared between CPU and GPU).
- What is the Apple M3 (8GB) best for?
- With 8 GB of VRAM, the Apple M3 (8GB) is best for running compact models (1B–8B) at low quantization, suitable for edge inference, prototyping, and lightweight tasks.
- What LLMs can the Apple M3 (8GB) run locally?
- The Apple M3 (8GB) cannot run any of the 80 tracked models fully in VRAM at 8k context. It may handle smaller models with CPU offload.
- Can the Apple M3 (8GB) run Llama 3.3 70B Instruct?
- The Apple M3 (8GB) does not have enough VRAM to run Llama 3.3 70B Instruct. You would need more VRAM or a lower quantization level.
- Can the Apple M3 (8GB) run Qwen 3.6 27B?
- The Apple M3 (8GB) does not have enough VRAM to run Qwen 3.6 27B. You would need more VRAM or a lower quantization level.
- Can the Apple M3 (8GB) run Llama 3.1 8B Instruct?
- The Apple M3 (8GB) does not have enough VRAM to run Llama 3.1 8B Instruct. You would need more VRAM or a lower quantization level.