Hardware · Intel

What AI models can the Intel Arc A370M run?

VRAM
4.0 GB
Usable for models
4.0 GB
Memory bandwidth
112 GB/s
FP16 compute
6.3 TFLOPS
Released
2022
331 / 622 LLMs run Best: MiniCPM5 2B 29 / 61 Image models run Best: FLUX.2 [klein] 4B 1 / 43 Video models run Best: AnimateDiff v3 (SD 1.5) 62 / 70 Decision models run Best: Jina Reranker v3.5

More about this hardware

MakerIntel
TypeLaptop GPU (soldered memory)
InterfacePCIe 4.0

Apps that run models well on the Intel Arc A370M

Windows

  1. llama.cppSupports Intel Arc through SYCL and Vulkan.
  2. LM StudioPoint-and-click: search, download and chat in one window.
  3. OllamaIntel GPU support here is experimental (Vulkan).
  4. JanPoint-and-click: search, download and chat in one window.

Linux

  1. llama.cppSupports Intel Arc through SYCL and Vulkan.
  2. LM StudioPoint-and-click: search, download and chat in one window.
  3. OllamaIntel GPU support here is experimental (Vulkan).
  4. JanPoint-and-click: search, download and chat in one window.

For a typical model that fits in memory. Each model page picks the best app for that model on this hardware. All apps

Best LLMs for the Intel Arc A370M

Quality Model Quant Memory Speed Runs
57Good quality (B) · 57 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. MiniCPM5 2BOpenBMB Q4_K_M 2.7 GB 41.7 tok/s Runs great
58Good quality (B) · 58 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. Gemma 4 E2BGoogle Q4_K_M 4.0 GB 45.7 tok/s Runs welltight fit
64Good quality (B) · 64 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. Nemotron Labs Dory 1.0 4BNVIDIA Q4_K_M 3.7 GB 26.4 tok/s Runs welltight fit
62Good quality (B) · 62 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. Spark-X2.6 4BSparkLLM Q4_K_M 3.6 GB 25.6 tok/s Runs welltight fit
55Good quality (B) · 55 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking. LFM3 1.7BLiquid AI Q6_K 2.3 GB 42.1 tok/s Runs great
57Good quality (B) · 57 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. TMax 4BAi2 Q4_K_M 3.6 GB 24.9 tok/s Runs welltight fit
58Good quality (B) · 58 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.5 4BAlibaba Q4_K_M 3.9 GB 22.5 tok/s Runs welltight fit
49Fair quality (C) · 49 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. LFM3-VL 2BLiquid AI Q6_K 2.5 GB 38.0 tok/s Runs great
57Good quality (B) · 57 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. Agents-A1 4BInternScience Q4_K_M 3.8 GB 23.1 tok/s Runs welltight fit
47Fair quality (C) · 47 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 75/100 (quality, fit, speed and memory use) sets the ranking. Nanbeige4.2 3BBOSS Zhipin (Nanbeige) Q2_K 3.9 GB 41.4 tok/s Runs welltight fit
55Good quality (B) · 55 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 75/100 (quality, fit, speed and memory use) sets the ranking. Fara 1.5 4BMicrosoft Q4_K_M 3.8 GB 23.1 tok/s Runs welltight fit
43Fair quality (C) · 43 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking. Granite 4.2 3BIBM Q3_K_M 3.3 GB 37.1 tok/s Runs great

Best Image models for the Intel Arc A370M

Quality Model Quant Memory Speed Runs
76Great quality (A) · 76 of 100: how capable the model is at FP8, whatever it runs on. Match score 71/100 (quality, fit, speed and memory use) sets the ranking. FLUX.2 [klein] 4BBlack Forest Labs FP8 3.5 GB 15 s Runs welltight fit · CPU offload
42Fair quality (C) · 42 of 100: how capable the model is at FP16, whatever it runs on. Match score 71/100 (quality, fit, speed and memory use) sets the ranking. Realistic Vision V5.1SG161222 FP16 2.8 GB 15 s Runs well
40Fair quality (C) · 40 of 100: how capable the model is at FP16, whatever it runs on. Match score 70/100 (quality, fit, speed and memory use) sets the ranking. DreamShaper 8Lykon FP16 2.8 GB 15 s Runs well
84Great quality (A) · 84 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 69/100 (quality, fit, speed and memory use) sets the ranking. FLUX 3 Image KleinBlack Forest Labs Q4 GGUF 3.4 GB 1.8 min SlowCPU offload
30Basic quality (D) · 30 of 100: how capable the model is at FP16, whatever it runs on. Match score 68/100 (quality, fit, speed and memory use) sets the ranking. LCM DreamShaper v7Tsinghua (LCM) FP16 2.8 GB 3.1 s Runs great
50Fair quality (C) · 50 of 100: how capable the model is at FP16, whatever it runs on. Match score 68/100 (quality, fit, speed and memory use) sets the ranking. PixArt-Σ XL 1024PixArt FP16 3.3 GB 20 s Runs wellencoder in RAM

Best Video models for the Intel Arc A370M

Quality Model Quant Memory Speed Runs
35Basic quality (D) · 35 of 100: how capable the model is at FP16, whatever it runs on. Match score 53/100 (quality, fit, speed and memory use) sets the ranking. AnimateDiff v3 (SD 1.5)Shanghai AI Lab FP16 2.6 GB 5.4 min Runs wellCPU offload

Best Decision models for the Intel Arc A370M

Quality Model Quant Memory Speed Runs
86Excellent quality (A+) · 86 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 93/100 (quality, fit, speed and memory use) sets the ranking. Jina Reranker v3.5Jina AI Q8_0 1.7 GB 104 ms Runs great
84Great quality (A) · 84 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking. Jina Reranker v3Jina AI Q8_0 1.7 GB 104 ms Runs great
80Great quality (A) · 80 of 100: how capable the model is at F16, whatever it runs on. Match score 91/100 (quality, fit, speed and memory use) sets the ranking. FRIDA-DecisionsSber AI F16 2.4 GB 80 ms Runs great
80Great quality (A) · 80 of 100: how capable the model is at F16, whatever it runs on. Match score 91/100 (quality, fit, speed and memory use) sets the ranking. GLiNER2.5 DecideFastino F16 1.7 GB 49 ms Runs great
80Great quality (A) · 80 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 90/100 (quality, fit, speed and memory use) sets the ranking. Qwen3 Reranker 0.6BAlibaba Q8_0 1.7 GB 104 ms Runs great
76Great quality (A) · 76 of 100: how capable the model is at F16, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking. Llama Prompt Guard 2 86MMeta F16 1.2 GB 56 ms Runs great
76Great quality (A) · 76 of 100: how capable the model is at F16, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking. mxbai-rerank-base v2Mixedbread F16 1.8 GB 96 ms Runs great
74Great quality (A) · 74 of 100: how capable the model is at F16, whatever it runs on. Match score 88/100 (quality, fit, speed and memory use) sets the ranking. GLiClass ModernBERT Large v3Knowledgator F16 1.5 GB 41 ms Runs great

Best LLMs by task on this hardware Open in Model Finder

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.

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