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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/GPUs/Intel Arc A370M 4GB
Intel

Intel

Intel Arc A370M 4GB

Arc A MobileLaptopAlchemistMOBILEoneAPI
4GB
VRAM
112GB/s
Bandwidth
8TFLOPS
FP16 Compute
64TOPS
INT8 Inference
VRAM4 GBBandwidth112 GB/sCompute8 TFInference64 TOPS
Intel Arc A370M 4GBCategory AvgIntel Arc A380 6GB

Specifications

Compute
FP168 TFLOPS
INT864 TOPS
ArchitectureAlchemist
Memory
VRAM4 GB
Bandwidth112 GB/s
General
FamilyArc A Mobile
SegmentLaptop
InterconnectMOBILE
Compute PlatformONEAPI

Architecture

Alchemist

Alchemist is Intel's first discrete GPU architecture under the Arc brand, using Xe-HPG cores manufactured on TSMC's N6 process. It features XMX (Xe Matrix Extensions) engines for AI acceleration.

AI Relevance

XMX engines provide some AI inference acceleration via oneAPI/SYCL. However, the software ecosystem for LLM inference on Intel Arc is still developing, with limited runtime support compared to CUDA.

Process: TSMC N6Platform: ONEAPIPrecisions: FP32, FP16, INT8

Recommendations by Workload

Agentic Coding

C

Qwen 2.5 Coder 1.5B

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 54.9 tok/s · 33K ctx · llama.cpp
3.0 GB / 4.0 GB VRAM

Chat

C

Qwen 3 1.7B

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 52.9 tok/s · 10K ctx · llama.cpp
3.1 GB / 4.0 GB VRAM

Coding

C

Qwen 2.5 Coder 1.5B

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, lm-studio.

Decode 54.9 tok/s · 21K ctx · llama.cpp
3.0 GB / 4.0 GB VRAM

RAG

C

Qwen 3 1.7B

This model is still usable for rag, but it is not the most specialized pick. It belongs to a current frontier family for local AI. It fits natively with comfortable headroom. Known channels: huggingface, ollama, lm-studio.

Decode 52.9 tok/s · 33K ctx · llama.cpp
3.1 GB / 4.0 GB VRAM

Reasoning

C

DeepSeek R1 1.5B

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

Decode 54.9 tok/s · 21K ctx · llama.cpp
3.0 GB / 4.0 GB VRAM

Full Model Compatibility

Hugging-quantsHLlama 3.2 1B Instruct Q8 0
B56
1B2.9 GB58 tok/s22K ctx
dense
QwenQwen2.5 1.5B Instruct
B55
1.5B3.0 GB55 tok/s21K ctx
dense
TheBlokeTTinyLlama 1.1B Chat v1.0
B55
1.1B2.8 GB55 tok/s23K ctx
dense
Ggml-orgGSmolVLM 500M Instruct
C54
0.5B2.5 GB58 tok/s25K ctx
dense
Ggml-orgGembeddinggemma 300M
C53
0.3B2.3 GB58 tok/s27K ctx
dense
Googlegemma 2b
C52
2B3.3 GB45 tok/s19K ctx
dense
TheDrummerTGemmasutra Mini 2B v1
C52
2B3.3 GB45 tok/s19K ctx
dense
BartowskiBgemma 2 2b it
C51
2B3.7 GB35 tok/s17K ctx
dense
QwenQwen2.5 3B Instruct
C51
3B3.9 GB30 tok/s16K ctx
dense
BartowskiBLlama 3.2 3B Instruct
D40
3B4.3 GB25 tok/s15K ctx
dense
UnslothQwen3.5 4B
D39
4B4.5 GB20 tok/s14K ctx
dense
Lmstudio-communityLgemma 3 4b it
D39
4B4.5 GB20 tok/s14K ctx
dense
DeepSeekDeepSeek R1 671B
F0
671B416.4 GB2 tok/s4K ctx
moe
MistralDevstral 2 123B Instruct
F0
123B95.5 GB2 tok/s4K ctx
dense
Z.aiGLM-5
F0
744B461.4 GB2 tok/s4K ctx
moe
UnslothQwen3.5 27B
F0
27B22.0 GB3 tok/s4K ctx
dense
UnslothQwen3.5 35B A3B
F0
35B28.1 GB3 tok/s4K ctx
dense
UnslothQwen3.5 9B
F0
9B8.2 GB10 tok/s8K ctx
dense
Moonshot AIKimi K2.5
F0
1000B616.3 GB2 tok/s4K ctx
moe
MistralMistral Large 3
F0
675B419.5 GB2 tok/s4K ctx
+1moe
MistralMistral Small 4 119B
F0
119B74.9 GB2 tok/s4K ctx
moe
AlibabaQwen3-Coder 30B A3B Instruct
F0
30.5B20.7 GB8 tok/s4K ctx
moe
AlibabaQwen3-Coder 480B A35B Instruct
F0
480B299.6 GB2 tok/s4K ctx
moe
AlibabaQwen3-Coder-Next
F0
80B50.9 GB3 tok/s4K ctx
moe
HauhauCSHQwen3.5 9B Uncensored HauhauCS Aggressive
F0
9B8.2 GB10 tok/s8K ctx
dense
UnslothQwen3.5 122B A10B
F0
122B80.1 GB2 tok/s4K ctx
dense
BartowskiBMeta Llama 3.1 8B Instruct
F0
8B7.4 GB11 tok/s9K ctx
dense
DeepSeekDeepSeek V3 671B
F0
671B416.4 GB2 tok/s4K ctx
moe
MistralMixtral 8x22B
F0
141B93.4 GB2 tok/s4K ctx
moe
AlibabaQwen 2.5 72B
F0
72B56.5 GB2 tok/s4K ctx
dense
AlibabaQwen 3 235B A22B
F0
235B148.1 GB2 tok/s4K ctx
moe
AlibabaQwen3-VL 30B A3B Instruct
F0
30B20.4 GB8 tok/s4K ctx
moe
TheBlokeTLlama 2 7B Chat
F0
7B6.7 GB13 tok/s10K ctx
dense
XtunerXllava llama 3 8b v1 1
F0
8B7.4 GB11 tok/s9K ctx
dense
UnslothQwen3.5 397B A17B
F0
397B305.5 GB2 tok/s4K ctx
dense
MistralDevstral Small 2 24B Instruct
F0
24B19.7 GB4 tok/s4K ctx
dense
MetaLlama 3.3 70B
F0
70B54.9 GB2 tok/s4K ctx
dense
MetaLlama 4 Maverick 17B 128E
F0
400B248.0 GB2 tok/s4K ctx
moe
TheBlokeTMistral 7B Instruct v0.2
F0
7B6.7 GB13 tok/s10K ctx
dense
UnslothDeepSeek R1 0528 Qwen3 8B
F0
8B7.4 GB11 tok/s9K ctx
dense
CohereCommand A 111B
F0
111B86.4 GB2 tok/s4K ctx
dense
AlibabaQwen 2.5 Coder 32B
F0
32B25.8 GB3 tok/s4K ctx
dense
AlibabaQwen 2.5 VL 72B
F0
72B56.5 GB2 tok/s4K ctx
dense
Unslothgemma 3 27b it
F0
27B22.0 GB3 tok/s4K ctx
dense
Lmstudio-communityLQwen3.5 9B
F0
9B8.2 GB10 tok/s8K ctx
dense
MaziyarPanahiMMistral 7B Instruct v0.3
F0
7B6.7 GB13 tok/s10K ctx
dense
MaziyarPanahiMMeta Llama 3 8B Instruct
F0
8B7.4 GB11 tok/s9K ctx
dense
Lmstudio-communityLQwen3.5 35B A3B
F0
35B28.1 GB3 tok/s4K ctx
dense
MistralCodestral 2 25.08
F0
22B18.2 GB4 tok/s4K ctx
dense
MistralDevstral Small 1.1
F0
24B19.7 GB4 tok/s4K 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 ~422.2 GB
MistralDevstral 2 123B Instruct
123BTier 5Needs ~114.8 GB
Runs on Mac Studio M3 Ultra 256GB
Z.aiGLM-5
744BTier 5Needs ~467.6 GB
UnslothQwen3.5 27B
27BTier 5Needs ~26.2 GB
Runs on RTX 5090 32GB (~$1,999)
UnslothQwen3.5 35B A3B
35BTier 5Needs ~33.6 GB
Runs on Mac mini M4 64GB (~$1,099)

Upgrade paths

Upgrade from Intel Arc A370M 4GB

See what you unlock with more powerful hardware

Upgrade options

Upgrade options

IntelIntel Arc A380 6GBNext step up
6 GB VRAM (+2)186 GB/s (+74)
A
Unlocks Qwen3.5 4B, gemma 3 4b it, gemma 3 4b it+14 more · +44% faster avg

 

IntelIntel Arc A550M 8GBIntel upgrade
8 GB VRAM (+4)224 GB/s (+112)
A
Unlocks Meta Llama 3.1 8B Instruct, Qwen3.5 4B, Llama 2 7B Chat+116 more · +4% faster avg

 

IntelIntel Arc B580 12GBBest value
12 GB VRAM (+8)456 GB/s (+344)
A
Unlocks Qwen3.5 9B, Qwen3.5 9B Uncensored HauhauCS Aggressive, Meta Llama 3.1 8B Instruct+150 more · +89% faster avg

~$249 MSRP

AMDAMD Instinct MI350X 288GBBiggest leap
288 GB VRAM (+284)8000 GB/s (+7888)
A
Unlocks Devstral 2 123B Instruct, Qwen3.5 27B, Qwen3.5 35B A3B+260 more · +3513% faster avg

~$8,000 MSRP

Compare this GPU