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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/embeddinggemma 300M/on Intel Arc A370M 4GB

Can it run?

Can Intel Arc A370M 4GB run embeddinggemma 300M?

CUsable

Runs well

Using Q6_K in Ollama

Capabilities:

Fit status

Runs well

Decode

57.6 tok/s

TTFT

3360 ms

Safe context

24K

Memory

2.6 GB / 4.0 GB

Memory breakdown

Weights0.2 GB
KV Cache0.8 GB
Runtime1.2 GB
Headroom0.4 GB

Performance by workload

WorkloadGradeFitDecodeTTFTContext
Agentic CodingCRuns well57.6 tok/s4887 ms48K
ChatCRuns well57.6 tok/s1833 ms12K
CodingCRuns well57.6 tok/s3360 ms24K
RAGCRuns well57.6 tok/s6109 ms48K
ReasoningCRuns well57.6 tok/s3971 ms24K

Quantization options

How embeddinggemma 300M (0.30000001192092896B params) fits at each quantization level on Intel Arc A370M 4GB (4.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
0.1 GB
LowD30
Q3_K_S
3
0.1 GB
LowD30
NVFP4
4
0.2 GB
MediumD30
Q4_K_M
4
0.2 GB
MediumD30
Q5_K_M
5
0.2 GB
HighD30
Q6_K
6
0.2 GB
HighD30
Q8_0
8
0.3 GB
Very HighD31
F16Best for your GPU
16
0.6 GB
MaximumD33

Get started

HuggingFace
huggingface-cli download hf-ggml-org--embeddinggemma-300m-gguf
See all results for Intel Arc A370M 4GBSee all hardware for embeddinggemma 300M