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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/Mac mini M2 24GB
Apple

Apple

Mac mini M2 24GB

M2DesktopM2UNIFIEDMetal
24GB
Unified Memory
100GB/s
Bandwidth
$1,199 MSRP

About this GPU 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.

Specifications

Compute
ArchitectureM2
Memory
Unified Memory24 GB
Bandwidth100 GB/s
General
FamilyM2
SegmentDesktop
InterconnectUNIFIED
Compute PlatformMETAL
MSRP$1,199

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.

Recommendations by Workload

Agentic Coding

C

Yi Coder 9B

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 11.8 tok/s · 47K ctx · llama.cpp
11.8 GB / 24.0 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 7.6 tok/s · 11K ctx · llama.cpp
13.1 GB / 24.0 GB Unified Memory

Coding

C

Gemma 3 12B

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 8.9 tok/s · 22K ctx · llama.cpp
12.7 GB / 24.0 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 13.3 tok/s · 51K ctx · llama.cpp
10.9 GB / 24.0 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 should run, but memory headroom will be limited. Known channels: huggingface, ollama, lm-studio.

Decode 7.6 tok/s · 19K ctx · llama.cpp
14.2 GB / 24.0 GB Unified Memory

Full Model Compatibility

UnslothQwen3.5 9B
C49
9B10.4 GB12 tok/s27K ctx
dense
HauhauCSHQwen3.5 9B Uncensored HauhauCS Aggressive
C49
9B10.4 GB12 tok/s27K ctx
dense
Lmstudio-communityLQwen3.5 9B
C48
9B10.4 GB12 tok/s27K ctx
dense
BartowskiBMeta Llama 3.1 8B Instruct
C48
8B9.6 GB13 tok/s29K ctx
dense
XtunerXllava llama 3 8b v1 1
C48
8B9.6 GB13 tok/s29K ctx
dense
UnslothDeepSeek R1 0528 Qwen3 8B
C48
8B9.6 GB13 tok/s29K ctx
dense
MaziyarPanahiMMeta Llama 3 8B Instruct
C48
8B9.6 GB13 tok/s29K ctx
dense
Hugging-quantsHLlama 3.2 1B Instruct Q8 0
C48
1B5.1 GB68 tok/s54K ctx
dense
QwenQwen2.5 1.5B Instruct
C47
1.5B5.2 GB65 tok/s53K ctx
dense
TheBlokeTLlama 2 7B Chat
C47
7B8.9 GB15 tok/s31K ctx
dense
TheBlokeTMistral 7B Instruct v0.2
C47
7B8.9 GB15 tok/s31K ctx
dense
MaziyarPanahiMMistral 7B Instruct v0.3
C47
7B8.9 GB15 tok/s31K ctx
dense
Googlegemma 2b
C47
2B5.5 GB53 tok/s50K ctx
dense
TheBlokeTTinyLlama 1.1B Chat v1.0
C47
1.1B5.0 GB65 tok/s56K ctx
dense
TheDrummerTGemmasutra Mini 2B v1
C47
2B5.5 GB53 tok/s50K ctx
dense
Ggml-orgGSmolVLM 500M Instruct
C47
0.5B4.7 GB68 tok/s59K ctx
dense
BartowskiBgemma 2 2b it
C47
2B5.9 GB42 tok/s47K ctx
dense
BartowskiBLlama 3.2 3B Instruct
C47
3B6.5 GB31 tok/s43K ctx
dense
Ggml-orgGembeddinggemma 300M
C47
0.3B4.5 GB68 tok/s61K ctx
dense
QwenQwen2.5 3B Instruct
C47
3B6.1 GB36 tok/s45K ctx
dense
UnslothQwen3.5 4B
C46
4B6.7 GB27 tok/s41K ctx
dense
Lmstudio-communityLgemma 3 4b it
C46
4B6.7 GB27 tok/s41K ctx
dense
MistralCodestral 2 25.08
D29
22B20.3 GB5 tok/s14K ctx
dense
DeepSeekDeepSeek R1 671B
F0
671B418.6 GB2 tok/s4K ctx
moe
MistralDevstral 2 123B Instruct
F0
123B97.7 GB2 tok/s4K ctx
dense
Z.aiGLM-5
F0
744B463.6 GB2 tok/s4K ctx
moe
UnslothQwen3.5 27B
F0
27B24.2 GB4 tok/s11K ctx
dense
UnslothQwen3.5 35B A3B
F0
35B30.3 GB3 tok/s9K ctx
dense
Moonshot AIKimi K2.5
F0
1000B618.5 GB2 tok/s4K ctx
moe
MistralMistral Large 3
F0
675B421.6 GB2 tok/s4K ctx
+1moe
MistralMistral Small 4 119B
F0
119B77.1 GB3 tok/s4K ctx
moe
AlibabaQwen3-Coder 30B A3B Instruct
F0
30.5B22.9 GB9 tok/s12K ctx
moe
AlibabaQwen3-Coder 480B A35B Instruct
F0
480B301.8 GB2 tok/s4K ctx
moe
AlibabaQwen3-Coder-Next
F0
80B53.1 GB4 tok/s5K ctx
moe
UnslothQwen3.5 122B A10B
F0
122B82.3 GB2 tok/s4K ctx
dense
DeepSeekDeepSeek V3 671B
F0
671B418.6 GB2 tok/s4K ctx
moe
MistralMixtral 8x22B
F0
141B95.6 GB2 tok/s4K ctx
moe
AlibabaQwen 2.5 72B
F0
72B58.7 GB2 tok/s5K ctx
dense
AlibabaQwen 3 235B A22B
F0
235B150.3 GB2 tok/s4K ctx
moe
AlibabaQwen3-VL 30B A3B Instruct
F0
30B22.6 GB9 tok/s12K ctx
moe
UnslothQwen3.5 397B A17B
F0
397B307.7 GB2 tok/s4K ctx
dense
MistralDevstral Small 2 24B Instruct
F0
24B21.9 GB4 tok/s13K ctx
dense
MetaLlama 3.3 70B
F0
70B57.1 GB2 tok/s5K ctx
dense
MetaLlama 4 Maverick 17B 128E
F0
400B250.1 GB2 tok/s4K ctx
moe
CohereCommand A 111B
F0
111B88.5 GB2 tok/s4K ctx
dense
AlibabaQwen 2.5 Coder 32B
F0
32B28.0 GB3 tok/s10K ctx
dense
AlibabaQwen 2.5 VL 72B
F0
72B58.7 GB2 tok/s5K ctx
dense
Unslothgemma 3 27b it
F0
27B24.2 GB4 tok/s11K ctx
dense
Lmstudio-communityLQwen3.5 35B A3B
F0
35B30.3 GB3 tok/s9K ctx
dense
MistralDevstral Small 1.1
F0
24B21.9 GB4 tok/s13K 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 ~424.4 GB
MistralDevstral 2 123B Instruct
123BTier 5Needs ~117.0 GB
Runs on Mac Studio M3 Ultra 256GB
Z.aiGLM-5
744BTier 5Needs ~469.8 GB
UnslothQwen3.5 27B
27BTier 5Needs ~28.4 GB
Runs on RTX 5090 32GB (~$1,999)
UnslothQwen3.5 35B A3B
35BTier 5Needs ~35.8 GB
Runs on Mac mini M4 64GB (~$1,099)

Upgrade paths

Upgrade from Mac mini M2 24GB

See what you unlock with more powerful hardware

Upgrade options

Upgrade options

NVIDIARTX 4000 Ada 20GBNext step up
360 GB/s (+260)
A
Unlocks Qwen3-Coder 30B A3B Instruct, Qwen3-VL 30B A3B Instruct, Codestral 2 25.08+15 more · +309% faster avg

 

AppleMacBook Pro M1 Pro 32GBApple upgrade
32 GB Unified (+8)200 GB/s (+100)
B
Unlocks Qwen3-Coder 30B A3B Instruct, Qwen3-VL 30B A3B Instruct, Devstral Small 2 24B Instruct+27 more · +82% faster avg

~$1,999 MSRP

AppleMac mini M4 64GBBest value
64 GB Unified (+40)120 GB/s (+20)
B
Unlocks Qwen3.5 27B, Qwen3.5 35B A3B, Qwen3-Coder 30B A3B Instruct+51 more · +13% faster avg

~$1,099 MSRP

AMDAMD Instinct MI350X 288GBBiggest leap
288 GB VRAM (+264)8000 GB/s (+7900)
A
Unlocks Devstral 2 123B Instruct, Qwen3.5 27B, Qwen3.5 35B A3B+81 more · +6872% faster avg

~$8,000 MSRP

Compare this Mac