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⇱ MacBook Pro M3 24GB: Best Local LLMs — VRAM & tok/s (2026)


Apple

MacBook Pro M3 24GB

M3LaptopM3UNIFIED

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.

See Full AI Tier List for MacBook Pro M3 24GB →

Best Local LLMs for MacBook Pro M3 24GB

Apple Silicon local AI performance. Excellent for local AI. Your MacBook Pro M3 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 MacBook Pro M3 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.

See full comparison →

Quick picks

Best Local LLMs by Task

Top recommendations for common local AI workloads on your MacBook Pro M3 24GB

Best for coding

S

Qwen 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.

10.4 tok/s · 47K ctx · llama.cpp
13.1 GB / 24.0 GB Unified Memory

About MacBook Pro M3 24GB for AI

MacBook Pro M3 24GB with 24 GB unified memory. Third-generation Apple Silicon built on 3nm process with dynamic caching GPU architecture, significantly improving AI inference efficiency.

All 374 models tested

Model Compatibility Tiers

Every model ranked by how well it runs on your MacBook Pro M3 24GB, grouped by fit quality

Runs Great (76 models)

These models fit comfortably and run at full speed on your Mac.

👁 Alibaba
Qwen 3.5 9B
S91
9B11.2 GB13 tok/s60K ctx
dense
👁 Alibaba
Qwen 3 8B
S89
8B10.6 GB15 tok/s65K ctx
dense
👁 Alibaba
Qwen 3.5 4B
S88
4B8.1 GB30 tok/s83K ctx
dense
👁 Alibaba
Qwen 3 14B
S87
14B14.5 GB9 tok/s34K ctx
dense
👁 Microsoft
Phi-4-reasoning-plus 14B
S86
14.7B15.5 GB8 tok/s25K ctx
dense

Runs with Limits (191 models)

These models run but may need quantization or have reduced context windows.

A79
19B17.5 GB6 tok/s8K ctx
dense
👁 DeepSeek
DeepSeek Coder V2 16B
A77
16B16.5 GB17 tok/s20K ctx
moe
👁 OpenAI
GPT-OSS 20B
A76
21B18.7 GB11 tok/s6K ctx
moe
👁 Mistral
Magistral Small 2507
B70
24B20.6 GB4 tok/s4K ctx
dense
👁 Mistral
Devstral Small 2 24B Instruct
B69
24B20.6 GB4 tok/s4K ctx
dense

Won't Fit (107 models)

These models are too large for your Mac's unified memory.

👁 Meta
Llama 3.1 70B
F0
70B51.1 GB2 tok/s4K ctx
dense
👁 Meta
Llama 3.3 70B
F0
70B51.1 GB2 tok/s4K ctx
dense
👁 Alibaba
Qwen 2.5 32B
F0
32B26.9 GB2 tok/s4K ctx
dense
👁 Alibaba
Qwen 2.5 72B
F0
72B52.3 GB2 tok/s4K ctx
dense
👁 Alibaba
Qwen 2.5 Coder 32B
F0
32B26.9 GB2 tok/s4K ctx
dense

Beyond LLMs

AI Capability Matrix

What AI tasks this Mac can handle — from text generation to image and video creation.

CapabilityStatusRepresentative ModelDetail
LLM Chat (7B)Runs nativelyLlama 3.1 8B Q4
LLM Coding (30B)Needs offloadQwen 3 30B Q4

Same chip, more memory

Upgrade to More Memory? Here's What You Gain

Compare M3 configurations to see which models become available

MacBook Pro M3 Pro 18GB

18 GB unified memory

59

Run great

231

Total fit

MacBook Air M3 24GB

24 GB unified memory

76

Run great

257

Total fit

MacBook Pro M3 Pro 36GB

36 GB unified memory

+47 models

94

Run great

304

Total fit

Unlocks: Qwen3-Coder 30B A3B Instruct, Qwen 3.5 27B
good-unified-memorymlx-optimized

Specifications

Compute
ArchitectureM3
Memory
Unified Memory24 GB
Bandwidth100 GB/s
General
FamilyM3
SegmentLaptop
InterconnectUNIFIED
Compute PlatformMETAL
MSRP$1,099

Key Features

M3 chip (3nm 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
  • 3nm process enables higher efficiency
  • Dynamic caching GPU improves utilization
  • Up to 400 GB/s memory bandwidth (Max)
  • Hardware-accelerated ray tracing
  • Strong MLX optimization
Considerations
  • Base M3 still limited to 24 GB unified memory
  • Premium pricing for high-memory configurations

Architecture

M3

Apple M3 is built on TSMC's 3nm process, the first consumer chips at this node. It introduces Dynamic Caching for more efficient GPU memory allocation and hardware-accelerated ray tracing.

AI Relevance

Dynamic Caching improves GPU utilization for compute workloads including ML inference. The M3 Ultra with up to 512 GB unified memory can theoretically hold even unquantized 70B models, though memory bandwidth remains the throughput bottleneck.

Process: TSMC 3nmPlatform: METALPrecisions: FP32, FP16

M3's dynamic caching GPU architecture allocates local memory in hardware in real-time, improving GPU utilization for AI workloads. The M3 Max reaches 400 GB/s bandwidth, competitive with mid-range discrete GPUs.

All workloads

Recommendations by Workload

The best local LLM for each task on your MacBook Pro M3 24GB

Chat

S

Qwen 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.

10.4 tok/s · 47K ctx · llama.cpp
12.0 GB / 24.0 GB Unified Memory

Coding

S

Qwen 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.

10.4 tok/s · 47K ctx · llama.cpp
13.1 GB / 24.0 GB Unified Memory

Agentic Coding

S

Qwen 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

Image & Video Generation

Diffusion Model Compatibility

28 of 52 models can generate images or video on your MacBook Pro M3 24GB

ModelMax ResolutionGen TimeGrade
SD TurboImage512×512~4.6sS
Stable Diffusion 1.5Image512×768~9.2sS
Realistic Vision v5.1Image512×768~9.2sS
DreamShaper 8Image512×768~9.2sS
LCM DreamShaper v7

Get started in 2 minutes

Run Local AI on Your MacBook Pro M3 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 | sh
2

Pull your first model

Qwen 3.5 9B is the best match for your MacBook Pro M3 24GB. Pull and run it:

ollama run qwen3.5:9b
What to expect: With 24 GB unified memory, your top models will run at 13-15-30 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.
See full analysis: Qwen 3.5 9B on MacBook Pro M3 24GB

Upgrade paths

Upgrade from MacBook Pro M3 24GB

See what you unlock with more unified memory

Upgrade options

Upgrade options

👁 NVIDIA
RTX 4000 Ada 20GBNext step up
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 · +182% faster avg

Unlocks 12 additional models that do not fit on the current setup.

Lifts average decode speed across fitting models by about 182%.

~$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 · +52% faster avg

Unlocks 29 additional models that do not fit on the current setup.

Lifts average decode speed across fitting models by about 52%.

~$1,999 MSRP

👁 Intel
Intel Arc Pro B60 24GBBest value
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 · +143% faster avg

Unlocks 34 additional models that do not fit on the current setup.

Lifts average decode speed across fitting models by about 143%.

~$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 · +887% faster avg

Unlocks 79 additional models that do not fit on the current setup.

Lifts average decode speed across fitting models by about 887%.

~$8,000 MSRP

Frequently Asked Questions

Compare with similar

MacBook Pro M3 24GB vs MacBook Pro M4 Pro 24GBMacBook Pro M3 24GB vs Mac mini M2 24GBMacBook Pro M3 24GB vs MacBook Air M3 24GB

Related guides

Best LLM for Mac 2026: Picks for M1/M2/M3/M4 by RAM TierApple Silicon for AI: M4 vs M3 vs M2 ComparisonBest AI Models for 16GB Mac — LLMs, Image, and Video That Actually Fit
Compare this Mac
Metal
24GB
Unified Memory
100GB/s
Bandwidth
$1,099 MSRP
LLM Large (70B)
Won’t fit
Llama 3.1 70B Q4
Image Gen (SDXL)Runs nativelySDXL 1.0 FP16~~36.7s per image
Image Gen (Flux)Won't fitFlux.1 Dev FP16~~2m 45s per image
Image Gen (SD 3.5)Runs with sequential offloadSD 3.5 Large FP16~~9m 4s per image
Video Short (25f)Runs nativelyLTX Video 2B~~1m 36s/frame
Video Long (100f)Won't fitWan Video 14B~~1m 34s/frame
View MacBook Pro M3 Pro 36GBCompare
13.3 tok/s · 60K ctx · llama.cpp
13.4 GB / 24.0 GB Unified Memory

Reasoning

S

Qwen 3 14B

Qwen 3 14B matches Reasoning and keeps a practical fit profile. It is a recent-generation family, which helps on current local SOTA workloads. It should run, but memory headroom will be limited. Context coverage stays within the requested workload envelope. Known distribution channels: huggingface, ollama, lm-studio.

8.6 tok/s · 34K ctx · llama.cpp
14.5 GB / 24.0 GB Unified Memory

RAG

A

Granite 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.

15.0 tok/s · 58K ctx · llama.cpp
13.3 GB / 24.0 GB Unified Memory
Image
512×768
~2.7s
S
PixArt-SigmaImage1024×1024~36.7sS
SDXL TurboImage512×512~4.6sS
SDXL LightningImage1024×1024~13.7sS
Stable Diffusion XL 1.0Image1024×1024~36.7sS
Playground v2.5Image1024×1024~55sS
RealVisXL v5.0Image1024×1024~41.2sS
DreamShaper XLImage1024×1024~41.2sS
Juggernaut XL v9Image1024×1024~41.2sS
Animagine XL 3.1Image1024×1024~41.2sS
Pony Diffusion V6 XLImage1024×1024~41.2sS
Animagine XL 4.0Image1024×1024~41.2sS
Illustrious XLImage1024×1024~41.2sS
Wan Video 2.1 1.3BVideo256×256~26.8s/frameS
Stable Diffusion 3.5 MediumImage1024×1024~1m 4sS
Flux.2 Klein 4BImage256×256~24.7sS
LTX Video 2BVideo256×256~1m 36s/frameS
KolorsImage256×256~3m 15sS
Stable CascadeImage1024×1024~1m 32sB
AuraFlow v0.3Image1024×1024~2m 45sB
Stable Diffusion 3.5 LargeImage256×256~9m 4sB
Stable Diffusion 3.5 Large TurboImage256×256~1m 39sB
CogVideoX 2BVideo256×256~1m 36s/frameD
Z-Image TurboImage256×256~1m 16sD
FramePack I2VVideo256×256~1m 7s/frameF
HunyuanVideoVideo256×256~1m 7s/frameF
ChromaImage256×256~36.7sF
Flux.1 DevImage256×256~2m 45sF
Flux.1 SchnellImage256×256~32.1sF
LTX Video 13BVideo256×256~1m 7s/frameF
Flux.1 Kontext DevImage256×256~3m 3sF
AnimateDiff v1.5.3Video512×768~16.7s/frameF
Cosmos Diffusion 7BVideo256×256~1m 41s/frameF
CogVideoX 5BVideo256×256~45.9s/frameF
Wan2.2 TI2V 5BVideo256×256~45.9s/frameF
Flux.2 Klein 9BImage256×256~18.3sF
Flux.1 Fill DevImage256×256~2m 36sF
Mochi 1 PreviewVideo256×256~1m 1s/frameF
HunyuanVideo 1.5Video256×256~56.2s/frameF
Helios 14BVideo256×256~1m 9s/frameF
SkyReels V2 14BVideo256×256~1m 9s/frameF
Wan Video 2.1 14BVideo256×256~1m 9s/frameF
Wan Video 2.2 14BVideo256×256~1m 9s/frameF
Qwen ImageImage256×256~1m 2sF
Qwen Image EditImage256×256~1m 2sF
Flux.2 DevImage256×256~28m 54sF
MAGI-1Video256×256~1m 26s/frameF
HunyuanImage 3.0Image256×256~1m 49sF

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.

Yes, MacBook Pro M3 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.