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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 Air M2 16GB
Apple

Apple

MacBook Air M2 16GB

M2LaptopM2UNIFIEDMetal
16GB
Unified Memory
100GB/s
Bandwidth
$1,199 MSRP

About this GPU for AI

MacBook Air M2 16GB with 16 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 Memory16 GB
Bandwidth100 GB/s
General
FamilyM2
SegmentLaptop
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

Codestral Mamba 7B

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.

Decode 15.2 tok/s · 41K ctx · llama.cpp
9.1 GB / 16.0 GB Unified Memory

Chat

C

Qwen 3 8B

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 13.3 tok/s · 11K ctx · llama.cpp
8.3 GB / 16.0 GB Unified Memory

Coding

C

Codestral Mamba 7B

This model is still usable for 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.

Decode 15.2 tok/s · 23K ctx · llama.cpp
8.0 GB / 16.0 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 should run, but memory headroom will be limited.

Decode 13.3 tok/s · 37K ctx · llama.cpp
10.0 GB / 16.0 GB Unified Memory

Reasoning

C

Qwen 3 8B

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 13.3 tok/s · 21K ctx · llama.cpp
8.8 GB / 16.0 GB Unified Memory

Full Model Compatibility

TheBlokeTLlama 2 7B Chat
C51
7B8.0 GB15 tok/s23K ctx
dense
TheBlokeTMistral 7B Instruct v0.2
C51
7B8.0 GB15 tok/s23K ctx
dense
MaziyarPanahiMMistral 7B Instruct v0.3
C51
7B8.0 GB15 tok/s23K ctx
dense
BartowskiBMeta Llama 3.1 8B Instruct
C51
8B8.8 GB13 tok/s21K ctx
dense
XtunerXllava llama 3 8b v1 1
C51
8B8.8 GB13 tok/s21K ctx
dense
UnslothDeepSeek R1 0528 Qwen3 8B
C51
8B8.8 GB13 tok/s21K ctx
dense
MaziyarPanahiMMeta Llama 3 8B Instruct
C51
8B8.8 GB13 tok/s21K ctx
dense
UnslothQwen3.5 4B
C49
4B5.9 GB27 tok/s31K ctx
dense
BartowskiBgemma 2 2b it
C49
2B5.1 GB42 tok/s36K ctx
dense
BartowskiBLlama 3.2 3B Instruct
C49
3B5.6 GB31 tok/s33K ctx
dense
Lmstudio-communityLgemma 3 4b it
C49
4B5.9 GB27 tok/s31K ctx
dense
Googlegemma 2b
C49
2B4.6 GB53 tok/s40K ctx
dense
QwenQwen2.5 1.5B Instruct
C49
1.5B4.3 GB65 tok/s42K ctx
dense
Hugging-quantsHLlama 3.2 1B Instruct Q8 0
C49
1B4.2 GB68 tok/s43K ctx
dense
QwenQwen2.5 3B Instruct
C49
3B5.3 GB36 tok/s35K ctx
dense
TheDrummerTGemmasutra Mini 2B v1
C49
2B4.6 GB53 tok/s40K ctx
dense
TheBlokeTTinyLlama 1.1B Chat v1.0
C49
1.1B4.1 GB65 tok/s45K ctx
dense
Ggml-orgGSmolVLM 500M Instruct
C48
0.5B3.8 GB68 tok/s48K ctx
dense
Ggml-orgGembeddinggemma 300M
C48
0.3B3.7 GB68 tok/s50K ctx
dense
UnslothQwen3.5 9B
C48
9B9.5 GB12 tok/s19K ctx
dense
HauhauCSHQwen3.5 9B Uncensored HauhauCS Aggressive
C48
9B9.5 GB12 tok/s19K ctx
dense
Lmstudio-communityLQwen3.5 9B
C48
9B9.5 GB12 tok/s19K ctx
dense
DeepSeekDeepSeek R1 671B
F0
671B417.7 GB2 tok/s4K ctx
moe
MistralDevstral 2 123B Instruct
F0
123B96.9 GB2 tok/s4K ctx
dense
Z.aiGLM-5
F0
744B462.7 GB2 tok/s4K ctx
moe
UnslothQwen3.5 27B
F0
27B23.3 GB4 tok/s8K ctx
dense
UnslothQwen3.5 35B A3B
F0
35B29.4 GB3 tok/s6K ctx
dense
Moonshot AIKimi K2.5
F0
1000B617.6 GB2 tok/s4K ctx
moe
MistralMistral Large 3
F0
675B420.8 GB2 tok/s4K ctx
+1moe
MistralMistral Small 4 119B
F0
119B76.2 GB3 tok/s4K ctx
moe
AlibabaQwen3-Coder 30B A3B Instruct
F0
30.5B22.0 GB9 tok/s8K ctx
moe
AlibabaQwen3-Coder 480B A35B Instruct
F0
480B300.9 GB2 tok/s4K ctx
moe
AlibabaQwen3-Coder-Next
F0
80B52.2 GB4 tok/s4K ctx
moe
UnslothQwen3.5 122B A10B
F0
122B81.5 GB2 tok/s4K ctx
dense
DeepSeekDeepSeek V3 671B
F0
671B417.7 GB2 tok/s4K ctx
moe
MistralMixtral 8x22B
F0
141B94.7 GB2 tok/s4K ctx
moe
AlibabaQwen 2.5 72B
F0
72B57.8 GB2 tok/s4K ctx
dense
AlibabaQwen 3 235B A22B
F0
235B149.4 GB2 tok/s4K ctx
moe
AlibabaQwen3-VL 30B A3B Instruct
F0
30B21.7 GB9 tok/s8K ctx
moe
UnslothQwen3.5 397B A17B
F0
397B306.8 GB2 tok/s4K ctx
dense
MistralDevstral Small 2 24B Instruct
F0
24B21.0 GB4 tok/s9K ctx
dense
MetaLlama 3.3 70B
F0
70B56.3 GB2 tok/s4K ctx
dense
MetaLlama 4 Maverick 17B 128E
F0
400B249.3 GB2 tok/s4K ctx
moe
CohereCommand A 111B
F0
111B87.7 GB2 tok/s4K ctx
dense
AlibabaQwen 2.5 Coder 32B
F0
32B27.1 GB3 tok/s7K ctx
dense
AlibabaQwen 2.5 VL 72B
F0
72B57.8 GB2 tok/s4K ctx
dense
Unslothgemma 3 27b it
F0
27B23.3 GB4 tok/s8K ctx
dense
Lmstudio-communityLQwen3.5 35B A3B
F0
35B29.4 GB3 tok/s6K ctx
dense
MistralCodestral 2 25.08
F0
22B19.5 GB5 tok/s9K ctx
dense
MistralDevstral Small 1.1
F0
24B21.0 GB4 tok/s9K 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 ~423.5 GB
MistralDevstral 2 123B Instruct
123BTier 5Needs ~116.1 GB
Runs on Mac Studio M3 Ultra 256GB
Z.aiGLM-5
744BTier 5Needs ~469.0 GB
UnslothQwen3.5 27B
27BTier 5Needs ~27.5 GB
Runs on RTX 5090 32GB (~$1,999)
UnslothQwen3.5 35B A3B
35BTier 5Needs ~34.9 GB
Runs on Mac mini M4 64GB (~$1,099)

Upgrade paths

Upgrade from MacBook Air M2 16GB

See what you unlock with more powerful hardware

Upgrade options

Upgrade options

NVIDIARTX A2000 12GBNext step up
288 GB/s (+188)
A
Unlocks LLaVA 1.6 13B, CodeLlama 13B Instruct, OLMo 2 13B+2 more · +240% faster avg

 

AMDRX 7600 XT 16GBBest value
288 GB/s (+188)
A
Unlocks StarCoder 15B, DeepSeek R1 Distill Qwen 14B, Phi-4-reasoning-plus 14B+28 more · +133% faster avg

~$329 MSRP

AppleMac mini M2 24GBApple upgrade
24 GB Unified (+8)
A
Unlocks StarCoder 15B, DeepSeek R1 Distill Qwen 14B, Phi-4-reasoning-plus 14B+28 more

~$1,199 MSRP

AMDAMD Instinct MI350X 288GBBiggest leap
288 GB VRAM (+272)8000 GB/s (+7900)
A
Unlocks Devstral 2 123B Instruct, Qwen3.5 27B, Qwen3.5 35B A3B+112 more · +6234% faster avg

~$8,000 MSRP

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