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All estimates are approximations based on mathematical models and public specifications. Actual performance may vary. Do not make purchasing decisions based solely on these estimates.

Data sourced from Hugging Face, Ollama, and official model documentation. Model names and logos are trademarks of their respective owners.

© 2026 Will It Run AI — Fase Consulting Ibiza, S.L. (NIF: B57969656)

Home/Hardware/Macs/MacBook Pro M1 Max 32GB
Apple

Apple

MacBook Pro M1 Max 32GB

M1LaptopM1UNIFIEDMetal
32GB
Unified Memory
400GB/s
Bandwidth
$2,499 MSRP

About this GPU for AI

MacBook Pro M1 Max 32GB with 32 GB unified memory. Apple's first custom silicon for Mac, delivering excellent power efficiency and unified memory architecture for local AI inference.

Specifications

Compute
ArchitectureM1
Memory
Unified Memory32 GB
Bandwidth400 GB/s
General
FamilyM1
SegmentLaptop
InterconnectUNIFIED
Compute PlatformMETAL
MSRP$2,499

For AI Workloads

Strengths
  • Unified memory eliminates CPU-GPU transfer bottleneck
  • Excellent power efficiency for always-on inference
  • Native MLX support with growing ecosystem
Considerations
  • Limited memory bandwidth compared to newer chips
  • Smaller unified memory options limit model size
  • No hardware ray tracing acceleration

Architecture

M1

Apple M1 is the first Apple Silicon chip for Mac, featuring a unified memory architecture where CPU, GPU, and Neural Engine share the same high-bandwidth memory pool. Available in base, Pro, Max, and Ultra variants with 16-128 GB unified memory.

AI Relevance

Unified memory architecture is a game-changer for LLM inference — the entire memory pool is accessible to both CPU and GPU, eliminating the discrete VRAM bottleneck. An M1 Max with 64 GB can run 30B+ models that would be impossible on a 24 GB discrete GPU.

Process: TSMC 5nmPlatform: METALPrecisions: FP32, FP16

First-generation Apple Silicon with 8-core GPU. The unified memory architecture is particularly beneficial for LLM inference as it eliminates the PCIe bottleneck that discrete GPUs face when offloading.

Recommendations by Workload

Agentic Coding

C

Gemma 3 12B

This model is still usable for agentic-coding, but it is not the most specialized pick. It sits in the middle of the current model mix. It fits natively with comfortable headroom. Known channels: huggingface, ollama, lm-studio.

Decode 30.1 tok/s · 48K ctx · llama.cpp
15.4 GB / 32.0 GB Unified Memory

Chat

C

Qwen 3 14B

This model is a direct match for chat. It belongs to a current frontier family for local AI. It fits natively with comfortable headroom. Known channels: huggingface, ollama, lm-studio.

Decode 25.8 tok/s · 13K ctx · llama.cpp
14.0 GB / 32.0 GB Unified Memory

Coding

C

Qwen 2.5 Coder 14B

This model is a direct match for coding. It sits in the middle of the current model mix. It fits natively with comfortable headroom. Known channels: huggingface, ollama, lm-studio.

Decode 25.8 tok/s · 24K ctx · llama.cpp
15.1 GB / 32.0 GB Unified Memory

RAG

C

granite 8b code instruct 4k

This model is a direct match for rag. It sits in the middle of the current model mix. It fits natively with comfortable headroom.

Decode 45.1 tok/s · 63K ctx · llama.cpp
11.7 GB / 32.0 GB Unified Memory

Reasoning

C

Qwen 3 14B

This model is a direct match for reasoning. It belongs to a current frontier family for local AI. It fits natively with comfortable headroom. Known channels: huggingface, ollama, lm-studio.

Decode 25.8 tok/s · 24K ctx · llama.cpp
15.1 GB / 32.0 GB Unified Memory

Full Model Compatibility

AlibabaQwen3-VL 30B A3B Instruct
C51
30B23.5 GB32 tok/s16K ctx
moe
AlibabaQwen3-Coder 30B A3B Instruct
C51
30.5B23.8 GB30 tok/s16K ctx
moe
UnslothQwen3.5 9B
C50
9B11.3 GB40 tok/s33K ctx
dense
HauhauCSHQwen3.5 9B Uncensored HauhauCS Aggressive
C50
9B11.3 GB40 tok/s33K ctx
dense
Lmstudio-communityLQwen3.5 9B
C50
9B11.3 GB40 tok/s33K ctx
dense
BartowskiBMeta Llama 3.1 8B Instruct
C50
8B10.5 GB45 tok/s35K ctx
dense
XtunerXllava llama 3 8b v1 1
C50
8B10.5 GB45 tok/s35K ctx
dense
UnslothDeepSeek R1 0528 Qwen3 8B
C50
8B10.5 GB45 tok/s35K ctx
dense
MaziyarPanahiMMeta Llama 3 8B Instruct
C50
8B10.5 GB45 tok/s35K ctx
dense
TheBlokeTLlama 2 7B Chat
C49
7B9.7 GB52 tok/s38K ctx
dense
TheBlokeTMistral 7B Instruct v0.2
C49
7B9.7 GB52 tok/s38K ctx
dense
MaziyarPanahiMMistral 7B Instruct v0.3
C49
7B9.7 GB52 tok/s38K ctx
dense
UnslothQwen3.5 4B
C49
4B7.6 GB90 tok/s49K ctx
dense
Lmstudio-communityLgemma 3 4b it
C49
4B7.6 GB90 tok/s49K ctx
dense
BartowskiBLlama 3.2 3B Instruct
C49
3B7.3 GB104 tok/s50K ctx
dense
QwenQwen2.5 3B Instruct
C49
3B7.0 GB120 tok/s53K ctx
dense
BartowskiBgemma 2 2b it
C49
2B6.8 GB141 tok/s54K ctx
dense
MistralCodestral 2 25.08
C49
22B21.2 GB16 tok/s17K ctx
dense
MistralDevstral Small 2 24B Instruct
C48
24B22.7 GB15 tok/s16K ctx
dense
MistralDevstral Small 1.1
C48
24B22.7 GB15 tok/s16K ctx
dense
Googlegemma 2b
C48
2B6.4 GB180 tok/s58K ctx
dense
TheDrummerTGemmasutra Mini 2B v1
C48
2B6.4 GB180 tok/s58K ctx
dense
QwenQwen2.5 1.5B Instruct
C48
1.5B6.1 GB220 tok/s61K ctx
dense
Hugging-quantsHLlama 3.2 1B Instruct Q8 0
C48
1B6.0 GB231 tok/s62K ctx
dense
TheBlokeTTinyLlama 1.1B Chat v1.0
C48
1.1B5.8 GB220 tok/s63K ctx
dense
Ggml-orgGSmolVLM 500M Instruct
C47
0.5B5.6 GB231 tok/s66K ctx
dense
Ggml-orgGembeddinggemma 300M
C47
0.3B5.4 GB231 tok/s68K ctx
dense
UnslothQwen3.5 27B
D38
27B25.0 GB13 tok/s15K ctx
dense
Unslothgemma 3 27b it
D38
27B25.0 GB13 tok/s15K ctx
dense
DeepSeekDeepSeek R1 671B
F0
671B419.4 GB2 tok/s4K ctx
moe
MistralDevstral 2 123B Instruct
F0
123B98.6 GB3 tok/s4K ctx
dense
Z.aiGLM-5
F0
744B464.4 GB2 tok/s4K ctx
moe
UnslothQwen3.5 35B A3B
F0
35B31.2 GB10 tok/s12K ctx
dense
Moonshot AIKimi K2.5
F0
1000B619.4 GB2 tok/s4K ctx
moe
MistralMistral Large 3
F0
675B422.5 GB2 tok/s4K ctx
+1moe
MistralMistral Small 4 119B
F0
119B78.0 GB9 tok/s5K ctx
moe
AlibabaQwen3-Coder 480B A35B Instruct
F0
480B302.6 GB2 tok/s4K ctx
moe
AlibabaQwen3-Coder-Next
F0
80B54.0 GB14 tok/s7K ctx
moe
UnslothQwen3.5 122B A10B
F0
122B83.2 GB3 tok/s4K ctx
dense
DeepSeekDeepSeek V3 671B
F0
671B419.4 GB2 tok/s4K ctx
moe
MistralMixtral 8x22B
F0
141B96.5 GB5 tok/s4K ctx
moe
AlibabaQwen 2.5 72B
F0
72B59.5 GB5 tok/s6K ctx
dense
AlibabaQwen 3 235B A22B
F0
235B151.1 GB4 tok/s4K ctx
moe
UnslothQwen3.5 397B A17B
F0
397B308.6 GB2 tok/s4K ctx
dense
MetaLlama 3.3 70B
F0
70B58.0 GB5 tok/s6K ctx
dense
MetaLlama 4 Maverick 17B 128E
F0
400B251.0 GB3 tok/s4K ctx
moe
CohereCommand A 111B
F0
111B89.4 GB3 tok/s4K ctx
dense
AlibabaQwen 2.5 Coder 32B
F0
32B28.9 GB11 tok/s13K ctx
dense
AlibabaQwen 2.5 VL 72B
F0
72B59.5 GB5 tok/s6K ctx
dense
Lmstudio-communityLQwen3.5 35B A3B
F0
35B31.2 GB10 tok/s12K ctx
dense

Just out of reach

Models you could run with an upgrade

High-quality models that need a bit more memory

DeepSeekDeepSeek R1 671B
671BTier 5Needs ~425.2 GB
MistralDevstral 2 123B Instruct
123BTier 5Needs ~117.8 GB
Runs on Mac Studio M3 Ultra 256GB
Z.aiGLM-5
744BTier 5Needs ~470.7 GB
UnslothQwen3.5 27B
27BTier 5Needs ~29.3 GB
Runs on RTX 5090 32GB (~$1,999)
UnslothQwen3.5 35B A3B
35BTier 5Needs ~36.6 GB
Runs on Mac mini M4 64GB (~$1,099)

Upgrade paths

Upgrade from MacBook Pro M1 Max 32GB

See what you unlock with more powerful hardware

Upgrade options

Upgrade options

NVIDIANVIDIA A10 24GBNext step up
600 GB/s (+200)
B
Unlocks Qwen3.5 27B, gemma 3 27b it, gemma 3 27b it+2 more · +109% faster avg

 

AppleMacBook Pro M4 Max 36GBApple upgrade
36 GB Unified (+4)410 GB/s (+10)
B
Unlocks Qwen3.5 27B, gemma 3 27b it, gemma 3 27b it+2 more · +16% faster avg

~$2,499 MSRP

AppleMac mini M4 64GBBest value
64 GB Unified (+32)
B
Unlocks Qwen3.5 27B, Qwen3.5 35B A3B, Qwen 2.5 Coder 32B+21 more

~$1,099 MSRP

AMDAMD Instinct MI350X 288GBBiggest leap
288 GB VRAM (+256)8000 GB/s (+7600)
A
Unlocks Devstral 2 123B Instruct, Qwen3.5 27B, Qwen3.5 35B A3B+51 more · +2157% faster avg

~$8,000 MSRP

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