With 24 GB unified memory (about 16.1 GB usable by the GPU), these are the best open models that fit. The top pick is gpt-oss 20B (MoE, MXFP4) at MXFP4 (~15.1 GB, ~20 tok/s): ollama run gpt-oss:20b.
Best for coding: gpt-oss 20B (MoE, MXFP4) (gpt-oss:20b), DeepSeek Coder V2 Lite 16B (MoE) (deepseek-coder-v2:16b-lite-instruct-q5_K_M), Mistral Small 24B (mistral-small:24b).
Runtimes available for this hardware: Ollama, LM Studio, llama.cpp, MLX.
Open the interactive checker for M4 24GB| # | Model | Quant | Memory needed | Fit | Speed | Command |
|---|---|---|---|---|---|---|
| 1 | gpt-oss 20B (MoE, MXFP4) | MXFP4 | 15.1 GB | fits in fast memory | ~20 tok/s | ollama run gpt-oss:20b |
| 2 | DeepSeek R1 Distill Qwen 14B | Q4_K_M | 10.3 GB | fits in fast memory | ~11 tok/s | ollama run deepseek-r1:14b |
| 3 | Phi-4 14B | Q4_K_M | 10.4 GB | fits in fast memory | ~11 tok/s | ollama run phi4:14b |
| 4 | Qwen3 14B | Q4_K_M | 10.6 GB | fits in fast memory | ~10 tok/s | ollama run qwen3:14b |
| 5 | Mistral Small 24B | Q4_K_M | 15.8 GB | fits in fast memory | ~7 tok/s | ollama run mistral-small:24b |
| 6 | Nimble v3 9B (Bespoke Labs, decision) | Q8_0 | 10.6 GB | fits in fast memory | ~10 tok/s | ollama run nimble-v3:9b-q8_0 |
| 7 | Qwen3 8B | Q8_0 | 9.9 GB | fits in fast memory | ~11 tok/s | ollama run qwen3:8b-q8_0 |
| 8 | DeepSeek R1 0528 Qwen3 8B | Q8_0 | 9.9 GB | fits in fast memory | ~11 tok/s | ollama run deepseek-r1:8b-0528-qwen3-q8_0 |
| 9 | DeepSeek R1 Distill Qwen 7B | Q8_0 | 9.1 GB | fits in fast memory | ~12 tok/s | ollama run deepseek-r1:7b-qwen-distill-q8_0 |
| 10 | Qwen 2.5 VL 7B | Q8_0 | 10.4 GB | fits in fast memory | ~10 tok/s | ollama run qwen2.5vl:7b-q8_0 |
| 11 | MiniCPM-V 2.6 8B | Q8_0 | 10.1 GB | fits in fast memory | ~11 tok/s | ollama run minicpm-v:8b-2.6-q8_0 |
| 12 | DeepSeek Coder V2 Lite 16B (MoE) | Q5_K_M | 13 GB | fits in fast memory | ~26 tok/s | ollama run deepseek-coder-v2:16b-lite-instruct-q5_K_M |
Estimates, not benchmarks. Model sizes are ollama.com download sizes; memory needed adds headroom for ~8k tokens of context; speeds are rough figures from memory bandwidth. Data updated 2026-10-14.
A project by OnDevice Labs · llms.txt