30.5BStufe 100Benötigt ca. 22.8 GB
Apple
MacBook Pro M4 Pro 24GB
M4LaptopM4UNIFIEDMetal
24GB
Unified Memory
273GB/s
Bandwidth
40W TDP$1,999 MSRP
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 MacBook Pro M4 Pro 24GB
Apple Silicon local AI performance. Excellent for local AI. Your MacBook Pro M4 Pro 24GB with 24 GB unified memory can run 78 models natively, 179 more with limits. The best match is Qwen 3.5 9B at 38 tok/s for interactive local LLM use.
78
Run great
257
Total compatible
24B
Max parameters
38
Best tok/sMEASURED
Comparison guide
Best Local LLMs for MacBook Pro M4 Pro 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.
Cost vs cloud API
2.9× cheaper than Claude Sonnet / GPT-4o per token
Assumes 4 hours/day of active inference at 38 tok/s, MacBook Pro M4 Pro 24GB amortized over 36 months, US residential electricity ($0.15/kWh), blended cloud pricing at $10 per 1M tokens (GPT-4o / Claude Sonnet tier).
16.4M
Tokens/month at this pace
$56.1
Monthly local cost
$164
Same tokens on cloud API
$3.42
Local $/1M tokens
Break-even: amortizes in 12.2 months vs cloud API. Price reference: $2.0k (MacBook Pro M4 Pro 24GB).
Quick picks
Best Local LLMs by Task
Top recommendations for common local AI workloads on your MacBook Pro M4 Pro 24GB
About MacBook Pro M4 Pro 24GB for AI
MacBook Pro M4 Pro 24GB with 24 GB unified memory. Fourth-generation Apple Silicon with enhanced Neural Engine and improved memory bandwidth, designed for AI-first workflows including local LLM inference.
All 374 models tested
Model Compatibility Tiers
Every model ranked by how well it runs on your MacBook Pro M4 Pro 24GB, grouped by fit quality
Runs Great (78 models)
These models fit comfortably and run at full speed on your Mac.
Runs with Limits (189 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 |
|---|---|---|
| LLM Chat (7B) | Runs natively | Llama 3.1 8B Q4 |
| LLM Coding (30B) | Needs offload | Qwen 3 30B Q4 |
| LLM Large (70B) | Won’t fit | Llama 3.1 70B Q4 |
| Image Gen (SDXL) | Runs natively | SDXL 1.0 FP16 |
| Image Gen (Flux) | Won't fit | Flux.1 Dev FP16 |
| Image Gen (SD 3.5) | Runs with sequential offload | SD 3.5 Large FP16 |
| Video Short (25f) | Runs natively | LTX Video 2B |
| Video Long (100f) | Won't fit | Wan Video 14B |
Same chip, more memory
Upgrade to More Memory? Here's What You Gain
Compare M4 configurations to see which models become available
MacBook Pro M4 32GB
32 GB unified memory
89
Run great
292
Total fit
Unlocks: Qwen3-Coder 30B A3B Instruct, Qwen 3.5 27B
ultra-efficientgood-memoryportable
Spezifikationen
Rechenleistung
ArchitekturM4
Speicher
Gemeinsamer Speicher24 GB
Bandbreite273 GB/s
TypUnified LPDDR5X
Allgemein
FamilieM4
SegmentLaptop
InterconnectUNIFIED
Compute-PlattformMETAL
MSRP$1,999
TDP40W
Hauptmerkmale
M4 chip (2nd-gen 3nm TSMC)24 GB unified memory (shared CPU/GPU/Neural Engine)273 GB/s memory bandwidth16-core Neural EngineMetal 3 GPU compute (MLX framework)MacBook Pro 14"/16" form factor
Für KI-Workloads
Stärken
- Enhanced 16-core Neural Engine for ML acceleration
- Up to 546 GB/s memory bandwidth (Max)
- Excellent power efficiency for sustained inference
- Best-in-class MLX performance
- Thunderbolt 5 for external GPU expansion
Hinweise
- Maximum 128 GB unified memory (less than some workstations)
- No CUDA support — limited to MLX and llama.cpp Metal
Architecture
M4
Apple M4 is the latest Apple Silicon generation, using TSMC's second-generation 3nm process. It features an enhanced Neural Engine with up to 38 TOPS and higher memory bandwidth across all tiers.
AI Relevance
The M4 Max with 128 GB unified memory and up to 546 GB/s bandwidth is currently the fastest Apple Silicon option for local LLM inference. Combined with MLX framework optimizations, it delivers the best tokens-per-second of any Mac configuration.
Process: TSMC 3nm (2nd gen)Platform: METALPrecisions: FP32, FP16
M4 is Apple's most AI-capable chip yet with up to 546 GB/s bandwidth in the Max variant. The unified memory architecture means models up to ~90 GB (at 72% usable) can run natively without offloading, covering most 70B models at Q4 quantization.
All workloads
Recommendations by Workload
The best local LLM for each task on your MacBook Pro M4 Pro 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.
38.0 tok/s · 60K ctx · llama.cpp
10.1 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.
38.0 tok/s · 60K ctx · llama.cpp
11.2 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.
38.0 tok/s · 60K ctx · llama.cpp
13.4 GB / 24.0 GB Unified Memory
Reasoning
SQwen 3.5 9B
Qwen 3.5 9B matches Reasoning 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.
38.0 tok/s · 60K ctx · llama.cpp
11.2 GB / 24.0 GB Unified Memory
RAG
AGranite 4.1 8B
Granite 4.1 8B matches RAG and keeps a practical fit profile. It sits in the middle of the current generation mix. It fits natively with comfortable headroom. Context coverage stays within the requested workload envelope. Known distribution channels: huggingface, ollama.
46.3 tok/s · 58K ctx · llama.cpp
13.3 GB / 24.0 GB Unified Memory
Fast erreichbar
Modelle, die Sie mit einem Upgrade ausführen könnten
Hochwertige Modelle, die etwas mehr Speicher benötigen
397BStufe 100Benötigt ca. 247.1 GB
123BStufe 100Benötigt ca. 81.2 GB
Läuft auf NVIDIA DGX Spark 128GB
1000BStufe 100Benötigt ca. 617.2 GB
1000BStufe 100Benötigt ca. 617.2 GB
Image & Video Generation
Diffusion Model Compatibility
28 of 52 models can generate images or video on your MacBook Pro M4 Pro 24GB
| Model | Max Resolution | Gen Time | Grade |
|---|---|---|---|
| SD TurboImage | 512×512 | ~4s | S |
| Stable Diffusion 1.5Image | 512×768 | ~8.1s | S |
| Realistic Vision v5.1Image | 512×768 | ~8.1s | S |
| DreamShaper 8Image | 512×768 | ~8.1s | S |
| LCM DreamShaper v7Image | 512×768 | ~2.4s | S |
| PixArt-SigmaImage | 1024×1024 | ~32.4s | S |
| SDXL TurboImage | 512×512 | ~4s | S |
| SDXL LightningImage | 1024×1024 | ~12.1s | S |
| Stable Diffusion XL 1.0Image | 1024×1024 | ~32.4s | S |
| Playground v2.5Image | 1024×1024 | ~48.6s | S |
| RealVisXL v5.0Image | 1024×1024 | ~36.4s | S |
| DreamShaper XLImage | 1024×1024 | ~36.4s | S |
| Juggernaut XL v9Image | 1024×1024 | ~36.4s | S |
| Animagine XL 3.1Image | 1024×1024 | ~36.4s | S |
| Pony Diffusion V6 XLImage | 1024×1024 | ~36.4s | S |
| Animagine XL 4.0Image | 1024×1024 | ~36.4s | S |
| Illustrious XLImage | 1024×1024 | ~36.4s | S |
| Wan Video 2.1 1.3BVideo | 256×256 | ~23.7s/frame | S |
| Stable Diffusion 3.5 MediumImage | 1024×1024 | ~56.7s | S |
| Flux.2 Klein 4BImage | 256×256 | ~21.9s | S |
| LTX Video 2BVideo | 256×256 | ~1m 24s/frame | S |
| KolorsImage | 256×256 | ~2m 52s | S |
| Stable CascadeImage | 1024×1024 | ~1m 21s | B |
| AuraFlow v0.3Image | 1024×1024 | ~2m 26s | B |
| Stable Diffusion 3.5 LargeImage | 256×256 | ~8m 1s | B |
| Stable Diffusion 3.5 Large TurboImage | 256×256 | ~1m 27s | B |
| CogVideoX 2BVideo | 256×256 | ~1m 24s/frame | D |
| Z-Image TurboImage | 256×256 | ~1m 7s | D |
| FramePack I2VVideo | 256×256 | ~59.4s/frame | F |
| HunyuanVideoVideo | 256×256 | ~59.4s/frame | F |
| ChromaImage | 256×256 | ~32.4s | F |
| Flux.1 DevImage | 256×256 | ~2m 26s | F |
| Flux.1 SchnellImage | 256×256 | ~28.3s | F |
| LTX Video 13BVideo | 256×256 | ~59.4s/frame | F |
| Flux.1 Kontext DevImage | 256×256 | ~2m 42s | F |
| AnimateDiff v1.5.3Video | 512×768 | ~14.8s/frame | F |
| Cosmos Diffusion 7BVideo | 256×256 | ~1m 30s/frame | F |
| CogVideoX 5BVideo | 256×256 | ~40.6s/frame | F |
| Wan2.2 TI2V 5BVideo | 256×256 | ~40.6s/frame | F |
| Flux.2 Klein 9BImage | 256×256 | ~16.2s | F |
| Flux.1 Fill DevImage | 256×256 | ~2m 18s | F |
| Mochi 1 PreviewVideo | 256×256 | ~53.5s/frame | F |
| HunyuanVideo 1.5Video | 256×256 | ~49.7s/frame | F |
| Helios 14BVideo | 256×256 | ~1m 1s/frame | F |
| SkyReels V2 14BVideo | 256×256 | ~1m 1s/frame | F |
| Wan Video 2.1 14BVideo | 256×256 | ~1m 1s/frame | F |
| Wan Video 2.2 14BVideo | 256×256 | ~1m 1s/frame | F |
| Qwen ImageImage | 256×256 | ~54.5s | F |
| Qwen Image EditImage | 256×256 | ~54.5s | F |
| Flux.2 DevImage | 256×256 | ~25m 32s | F |
| MAGI-1Video | 256×256 | ~1m 16s/frame | F |
| HunyuanImage 3.0Image | 256×256 | ~1m 36s | F |
Image models estimated at 1024×1024 (28 steps, FP16). Video models estimated at 768×512 (25 frames, 30 steps, FP16). Actual performance varies with runtime and system load.
Get started in 2 minutes
Run Local AI on Your MacBook Pro M4 Pro 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 MacBook Pro M4 Pro 24GB. Pull and run it:
ollama run qwen3.5:9bWhat to expect: With 24 GB unified memory, your top models will run at 38-43-56 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 MacBook Pro M4 Pro 24GB
See what you unlock with more unified memory
Upgrade-Optionen
Upgrade-Optionen
RTX 4000 Ada 20GBNächste Stufe360 GB/s (+87)
B
Unlocks 12 additional models that do not fit on the current setup.Schaltet frei Qwen3-Coder 30B A3B Instruct, Qwen 3.5 27B, Qwen3-VL 30B A3B Instruct+9 weitere · +29% schneller im Durchschnitt
Unlocks 12 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 29%.
ca. $1,250 MSRP
MacBook Pro M1 Pro 32GBApple-Upgrade
32 GB Unified (+8)
B
Unlocks 29 additional models that do not fit on the current setup.Schaltet frei Qwen3-Coder 30B A3B Instruct, Qwen 3.5 27B, Qwen3-VL 30B A3B Instruct+26 weitere
Unlocks 29 additional models that do not fit on the current setup.
ca. $1,999 MSRP
Intel Arc Pro B60 24GBBestes Preis-Leistungs-Verhältnis456 GB/s (+183)
A
Unlocks 34 additional models that do not fit on the current setup.Schaltet frei Qwen3-Coder 30B A3B Instruct, Qwen 3.5 27B, Qwen3-VL 30B A3B Instruct+31 weitere · +11% schneller im Durchschnitt
Unlocks 34 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 11%.
ca. $599 MSRP
AMD Instinct MI350X 288GBGrößter Sprung
288 GB VRAM (+264)8000 GB/s (+7727)
B
Unlocks 79 additional models that do not fit on the current setup.Schaltet frei Qwen3-Coder 30B A3B Instruct, Qwen 3.5 397B A17B, Devstral 2 123B Instruct+76 weitere · +351% schneller im Durchschnitt
Unlocks 79 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 351%.
ca. $8,000 MSRP
Frequently Asked Questions
Can MacBook Pro M4 Pro 24GB run AI models?
Yes! MacBook Pro M4 Pro 24GB (24 GB unified memory) can run 78 models at full speed and 257 total. Top picks: Qwen 3.5 9B (score: 94/100), Qwen 3 8B (score: 92/100), Qwen 3.5 4B (score: 90/100). See the full tiered compatibility list above.
How much unified memory does MacBook Pro M4 Pro 24GB have for AI?
MacBook Pro M4 Pro 24GB has 24 GB of unified memory shared between CPU and GPU, all available for AI model inference. Unlike discrete GPUs with separate VRAM, unified memory means models can use the full 24 GB without data transfer overhead.
Is unified memory on MacBook Pro M4 Pro 24GB the same as VRAM for local AI?
Not exactly. Unified memory is excellent for making larger models fit on Apple Silicon, because the CPU and GPU share one memory pool. But it is still not identical to dedicated VRAM on a high-bandwidth discrete GPU. For local AI, unified memory often wins on flexibility and capacity, while discrete GPUs can still win on raw tokens per second once a model fits comfortably.
Is MacBook Pro M4 Pro 24GB good for running LLMs locally?
Yes, MacBook Pro M4 Pro 24GB is excellent for running LLMs locally. With 24 GB unified memory and Metal acceleration, it handles 257 models with top scores above 80/100.
Why can a smaller CUDA GPU sometimes feel faster than MacBook Pro M4 Pro 24GB for local AI?
Because fit and speed are not the same thing. MacBook Pro M4 Pro 24GB can often fit larger models thanks to unified memory, but a smaller NVIDIA GPU with fast dedicated VRAM and mature CUDA kernels can still deliver higher decode throughput once the model fits. In practice, Apple Silicon is excellent for flexible local AI on one machine, while CUDA often stays ahead for the easiest setup and highest raw inference speed.
What is the best way to run AI models on MacBook Pro M4 Pro 24GB?
We recommend using llama.cpp on MacBook Pro M4 Pro 24GB. Install it with a single command, then pull your preferred model. llama.cpp supports Metal acceleration out of the box on Apple Silicon.
What is the best coding model for MacBook Pro M4 Pro 24GB?
For coding on MacBook Pro M4 Pro 24GB, we recommend Qwen 3.5 9B. It achieves 38.0 tokens per second with 60K context window using 11.2 GB of unified memory. 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.
Can MacBook Pro M4 Pro 24GB run Flux for image generation?
MacBook Pro M4 Pro 24GB can run Flux.1 Dev with sequential offloading or at reduced precision (FP8/NF4). The Schnell variant is faster and fits more easily in 24 GB unified memory.
What image and video AI models can I run on MacBook Pro M4 Pro 24GB?
MacBook Pro M4 Pro 24GB (24 GB unified memory) supports various AI generation tasks. For image generation, SDXL and Stable Diffusion 3.5 run well with Metal acceleration. For video, LTX Video 2.3 can generate short clips.
Is MacBook Pro M4 Pro 24GB good for AI image generation?
MacBook Pro M4 Pro 24GB is good for AI image generation. It handles SDXL and SD 3.5 well with Metal acceleration. Larger models like Flux may need offloading.
Should I upgrade from MacBook Pro M4 Pro 24GB for AI?
There are 4 upgrade path(s) from MacBook Pro M4 Pro 24GB: RTX 4000 Ada 20GB (20 GB), MacBook Pro M1 Pro 32GB (32 GB). Upgrading would unlock larger models like Qwen3-Coder 30B A3B Instruct and Qwen 3.5 397B A17B and faster inference.
Can MacBook Pro M4 Pro 24GB run Qwen 3.5?
Yes, MacBook Pro M4 Pro 24GB with 24 GB can run Qwen 3.5 9B at Q8 (near-lossless, ~9.6 GB) and Qwen 3.5 27B at Q4 with limited context. For best results on Mac, use MLX or Ollama.
What are the best local LLMs for MacBook Pro M4 Pro 24GB?
The best local LLMs for MacBook Pro M4 Pro 24GB (24 GB) are: Qwen 3.5 9B (94/100, 38 tok/s), Qwen 3 8B (92/100, 43 tok/s), Qwen 3.5 4B (90/100, 56 tok/s). These models fit natively in unified memory with room for context. For coding, try the top coding pick above. For general chat, the highest-scored model gives the best Apple Silicon local AI experience.
How fast is MacBook Pro M4 Pro 24GB for local LLM performance?
MacBook Pro M4 Pro 24GB achieves 27-38 tok/s for well-fitted models with 273 GB/s memory bandwidth. Token generation speed on Apple Silicon is primarily limited by memory bandwidth and fit. Comfortable reading speed is about 6-8 tokens per second, so most natively-fitting models will feel responsive for interactive chat. MLX generally delivers 10-20% better performance than llama.cpp on newer Apple Silicon chips.
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