30.5BTier 100Needs ~22.8 GB
Apple
Mac mini M2 24GB
M2DesktopM2UNIFIEDMetal
Operating mode
Choose the run profile you want to optimize
Apple Silicon can fit a lot thanks to unified memory. This selector changes which serving posture we optimize for when surfacing the best local LLMs for this Mac.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Best Local LLMs for Mac mini M2 24GB
Apple Silicon local AI performance. Excellent for local AI. Your Mac mini M2 24GB with 24 GB unified memory can run 76 models natively, 181 more with limits. The best match is Qwen 3.5 9B at 13 tok/s for interactive local LLM use.
76
Run great
257
Total compatible
24B
Max parameters
13
Best tok/sEST.
Comparison guide
Best Local LLMs for Mac mini M2 24GB — full ranked guide
Top models ranked for coding, chat, and writing with FAQ and buyer guidance — the comparison-intent companion to this spec sheet.
Quick picks
Best Local LLMs by Task
Top recommendations for common local AI workloads on your Mac mini M2 24GB
About Mac mini M2 24GB for AI
Mac mini M2 24GB with 24 GB unified memory. Second-generation Apple Silicon with improved GPU performance and memory bandwidth, offering a strong balance of efficiency and AI capability.
All 374 models tested
Model Compatibility Tiers
Every model ranked by how well it runs on your Mac mini M2 24GB, grouped by fit quality
Runs Great (76 models)
These models fit comfortably and run at full speed on your Mac.
Runs with Limits (191 models)
These models run but may need quantization or have reduced context windows.
Won't Fit (107 models)
These models are too large for your Mac's unified memory.
Beyond LLMs
AI Capability Matrix
What AI tasks this Mac can handle — from text generation to image and video creation.
| Capability | Status | Representative Model | Detail |
|---|---|---|---|
| LLM Chat (7B) | Runs natively | Llama 3.1 8B Q4 | — |
| LLM Coding (30B) | Needs offload | Qwen 3 30B Q4 | — |
Same chip, more memory
Upgrade to More Memory? Here's What You Gain
Compare M2 configurations to see which models become available
MacBook Pro M2 Pro 16GB
16 GB unified memory
59
Run great
212
Total fit
MacBook Pro M2 Pro 32GB
32 GB unified memory
89
Run great
292
Total fit
Unlocks: Qwen3-Coder 30B A3B Instruct, Qwen 3.5 27B
good-unified-memorymlx-optimized
Specifications
Compute
ArchitectureM2
Memory
Unified Memory24 GB
Bandwidth100 GB/s
General
FamilyM2
SegmentDesktop
InterconnectUNIFIED
Compute PlatformMETAL
MSRP$1,199
Key Features
M2 chip (2nd-gen 5nm TSMC)24 GB unified memory (shared CPU/GPU/Neural Engine)100 GB/s memory bandwidth16-core Neural EngineMetal 3 GPU compute (MLX framework)
For AI Workloads
Strengths
- Improved memory bandwidth over M1 (~50% increase)
- Unified memory architecture ideal for LLM inference
- Strong MLX ecosystem support
- Excellent performance per watt
Considerations
- Still limited by memory capacity in base configurations
- Lower bandwidth than discrete datacenter GPUs
Architecture
M2
Apple M2 is the second generation of Apple Silicon, with improved GPU cores and higher memory bandwidth. The M2 Ultra scales to 192 GB unified memory via UltraFusion die-to-die interconnect.
AI Relevance
Higher memory bandwidth (~50% more than M1 in Ultra config) directly improves token generation speed for LLMs. The M2 Ultra with 192 GB unified memory can run 70B models at full Q4 quantization with good performance.
Process: TSMC 5nm (2nd gen)Platform: METALPrecisions: FP32, FP16
M2 brings a 10-core GPU with improved memory bandwidth. The 100 GB/s bandwidth in base models and up to 200 GB/s in Pro/Max variants provides solid decode throughput for local LLMs.
All workloads
Recommendations by Workload
The best local LLM for each task on your Mac mini M2 24GB
Chat
SQwen 3.5 9B
Qwen 3.5 9B matches Chat and keeps a practical fit profile. It is a recent-generation family, which helps on current local SOTA workloads. It fits natively with comfortable headroom. Context coverage stays within the requested workload envelope. Known distribution channels: huggingface, ollama, lm-studio.
9.9 tok/s · 47K ctx · llama.cpp
12.0 GB / 24.0 GB Unified Memory
Coding
SQwen 3.5 9B
Qwen 3.5 9B is a specialized fit for Coding. It is a recent-generation family, which helps on current local SOTA workloads. It fits natively with comfortable headroom. Context coverage stays within the requested workload envelope. Known distribution channels: huggingface, ollama, lm-studio.
9.9 tok/s · 47K ctx · llama.cpp
13.1 GB / 24.0 GB Unified Memory
Agentic Coding
SQwen 3.5 9B
Qwen 3.5 9B is a specialized fit for Agentic Coding. It is a recent-generation family, which helps on current local SOTA workloads. It fits natively with comfortable headroom. Context coverage stays within the requested workload envelope. Known distribution channels: huggingface, ollama, lm-studio.
Just out of reach
Models you could run with an upgrade
High-quality models that need a bit more memory
397BTier 100Needs ~247.1 GB
123BTier 100Needs ~81.2 GB
Runs on NVIDIA DGX Spark 128GB
1000BTier 100Needs ~617.2 GB
1000BTier 100Needs ~617.2 GB
Image & Video Generation
Diffusion Model Compatibility
28 of 52 models can generate images or video on your Mac mini M2 24GB
| Model | Max Resolution | Gen Time | Grade |
|---|---|---|---|
| SD TurboImage | 512×512 | ~4.8s | S |
| Stable Diffusion 1.5Image | 512×768 | ~9.6s | S |
| Realistic Vision v5.1Image | 512×768 | ~9.6s | S |
| DreamShaper 8Image | 512×768 | ~9.6s | S |
| LCM DreamShaper v7 |
Get started in 2 minutes
Run Local AI on Your Mac mini M2 24GB
Everything you need to start running models locally with Metal acceleration and Apple Silicon unified memory
1
Install Ollama
Ollama runs natively on macOS with Metal GPU acceleration. One command to install.
curl -fsSL https://ollama.com/install.sh | sh2
Pull your first model
Qwen 3.5 9B is the best match for your Mac mini M2 24GB. Pull and run it:
ollama run qwen3.5:9bWhat to expect: With 24 GB unified memory, your top models will run at 13-14-29 tokens/sec — fast enough for interactive chat and local LLM workflows. Cloud APIs like ChatGPT typically stream at 30-60 tok/s, so Apple Silicon is competitive for many models when the fit is good.
Upgrade paths
Upgrade from Mac mini M2 24GB
See what you unlock with more unified memory
Upgrade options
Upgrade options
360 GB/s (+260)
B
Unlocks 12 additional models that do not fit on the current setup.Unlocks Qwen3-Coder 30B A3B Instruct, Qwen 3.5 27B, Qwen3-VL 30B A3B Instruct+9 more · +193% faster avg
Unlocks 12 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 193%.
~$1,250 MSRP
MacBook Pro M1 Pro 32GBApple upgrade
32 GB Unified (+8)200 GB/s (+100)
B
Unlocks 29 additional models that do not fit on the current setup.Unlocks Qwen3-Coder 30B A3B Instruct, Qwen 3.5 27B, Qwen3-VL 30B A3B Instruct+26 more · +57% faster avg
Unlocks 29 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 57%.
~$1,999 MSRP
456 GB/s (+356)
A
Unlocks 34 additional models that do not fit on the current setup.Unlocks Qwen3-Coder 30B A3B Instruct, Qwen 3.5 27B, Qwen3-VL 30B A3B Instruct+31 more · +152% faster avg
Unlocks 34 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 152%.
~$599 MSRP
AMD Instinct MI350X 288GBBiggest leap
288 GB VRAM (+264)8000 GB/s (+7900)
B
Unlocks 79 additional models that do not fit on the current setup.Unlocks Qwen3-Coder 30B A3B Instruct, Qwen 3.5 397B A17B, Devstral 2 123B Instruct+76 more · +925% faster avg
Unlocks 79 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 925%.
~$8,000 MSRP
Frequently Asked Questions
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