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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 M1 16GB
Apple

Apple

MacBook Air M1 16GB

M1LaptopM1UNIFIEDMetal
16GB
Unified Memory
68GB/s
Bandwidth
$999 MSRP

About this GPU for AI

MacBook Air M1 16GB with 16 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 Memory16 GB
Bandwidth68 GB/s
General
FamilyM1
SegmentLaptop
InterconnectUNIFIED
Compute PlatformMETAL
MSRP$999

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

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 9.6 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 8.4 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 9.6 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 8.4 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 8.4 tok/s · 21K ctx · llama.cpp
8.8 GB / 16.0 GB Unified Memory

Full Model Compatibility

TheBlokeTLlama 2 7B Chat
C50
7B8.0 GB10 tok/s23K ctx
dense
TheBlokeTMistral 7B Instruct v0.2
C50
7B8.0 GB10 tok/s23K ctx
dense
MaziyarPanahiMMistral 7B Instruct v0.3
C50
7B8.0 GB10 tok/s23K ctx
dense
BartowskiBMeta Llama 3.1 8B Instruct
C50
8B8.8 GB8 tok/s21K ctx
dense
XtunerXllava llama 3 8b v1 1
C50
8B8.8 GB8 tok/s21K ctx
dense
UnslothDeepSeek R1 0528 Qwen3 8B
C50
8B8.8 GB8 tok/s21K ctx
dense
MaziyarPanahiMMeta Llama 3 8B Instruct
C50
8B8.8 GB8 tok/s21K ctx
dense
UnslothQwen3.5 4B
C48
4B5.9 GB17 tok/s31K ctx
dense
BartowskiBgemma 2 2b it
C48
2B5.1 GB26 tok/s36K ctx
dense
BartowskiBLlama 3.2 3B Instruct
C48
3B5.6 GB19 tok/s33K ctx
dense
Lmstudio-communityLgemma 3 4b it
C48
4B5.9 GB17 tok/s31K ctx
dense
Googlegemma 2b
C48
2B4.6 GB33 tok/s40K ctx
dense
QwenQwen2.5 1.5B Instruct
C48
1.5B4.3 GB41 tok/s42K ctx
dense
Hugging-quantsHLlama 3.2 1B Instruct Q8 0
C48
1B4.2 GB43 tok/s43K ctx
dense
QwenQwen2.5 3B Instruct
C47
3B5.3 GB22 tok/s35K ctx
dense
TheDrummerTGemmasutra Mini 2B v1
C47
2B4.6 GB33 tok/s40K ctx
dense
TheBlokeTTinyLlama 1.1B Chat v1.0
C47
1.1B4.1 GB41 tok/s45K ctx
dense
Ggml-orgGSmolVLM 500M Instruct
C47
0.5B3.8 GB43 tok/s48K ctx
dense
Ggml-orgGembeddinggemma 300M
C47
0.3B3.7 GB43 tok/s50K ctx
dense
UnslothQwen3.5 9B
C46
9B9.5 GB7 tok/s19K ctx
dense
HauhauCSHQwen3.5 9B Uncensored HauhauCS Aggressive
C46
9B9.5 GB7 tok/s19K ctx
dense
Lmstudio-communityLQwen3.5 9B
C46
9B9.5 GB7 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 GB3 tok/s8K ctx
dense
UnslothQwen3.5 35B A3B
F0
35B29.4 GB2 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 GB2 tok/s4K ctx
moe
AlibabaQwen3-Coder 30B A3B Instruct
F0
30.5B22.0 GB6 tok/s8K ctx
moe
AlibabaQwen3-Coder 480B A35B Instruct
F0
480B300.9 GB2 tok/s4K ctx
moe
AlibabaQwen3-Coder-Next
F0
80B52.2 GB3 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 GB6 tok/s8K ctx
moe
UnslothQwen3.5 397B A17B
F0
397B306.8 GB2 tok/s4K ctx
dense
MistralDevstral Small 2 24B Instruct
F0
24B21.0 GB3 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 GB2 tok/s7K ctx
dense
AlibabaQwen 2.5 VL 72B
F0
72B57.8 GB2 tok/s4K ctx
dense
Unslothgemma 3 27b it
F0
27B23.3 GB3 tok/s8K ctx
dense
Lmstudio-communityLQwen3.5 35B A3B
F0
35B29.4 GB2 tok/s6K ctx
dense
MistralCodestral 2 25.08
F0
22B19.5 GB3 tok/s9K ctx
dense
MistralDevstral Small 1.1
F0
24B21.0 GB3 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 M1 16GB

See what you unlock with more powerful hardware

Upgrade options

Upgrade options

NVIDIARTX A2000 12GBNext step up
288 GB/s (+220)
A
Unlocks LLaVA 1.6 13B, CodeLlama 13B Instruct, OLMo 2 13B+2 more · +441% faster avg

 

AMDRX 7600 XT 16GBBest value
288 GB/s (+220)
A
Unlocks StarCoder 15B, DeepSeek R1 Distill Qwen 14B, Phi-4-reasoning-plus 14B+28 more · +271% faster avg

~$329 MSRP

AppleMac mini M2 24GBApple upgrade
24 GB Unified (+8)100 GB/s (+32)
A
Unlocks StarCoder 15B, DeepSeek R1 Distill Qwen 14B, Phi-4-reasoning-plus 14B+28 more · +45% faster avg

~$1,199 MSRP

AMDAMD Instinct MI350X 288GBBiggest leap
288 GB VRAM (+272)8000 GB/s (+7932)
A
Unlocks Devstral 2 123B Instruct, Qwen3.5 27B, Qwen3.5 35B A3B+112 more · +9976% faster avg

~$8,000 MSRP

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