Your rig

Arc A750 · 8 GB

16 GB system RAM · Alchemist · 512 GB/s · 7.0 GB usable VRAM
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Context length

KV cache at f16, 128K tokens

Quality floor
Q8_0 — near-lossless Q6_K Q5_K_M Q4_K_M — recommended Q3_K_M Q2_K — damaged
KV cache type
System RAM (GB)
Runtime
Ollamallama.cppLM Studio

3 of 5 runtimes drive this device.

Allow CPU offload Include partial-offload fits

Offloaded layers run at 60 GB/s host bandwidth — expect single-digit tokens per second.

Which one should I actually run?

Best models for your Arc A750

Updated 21 Aug 2026 5 new this week, 14 this month

What do you want to do? Each row is the best-ranked model on that use case's shortlist that fits at Q3_K_M and 128K. The ordering is editorial; the sizes and speeds are computed. How the shortlists work.

RecommendationModelWhyQuant · totalTok/s est.
Best overall Qwen3.5 2B
Alibaba · Apache 2.0
Runs on 4 GB, and still multimodal. Q3_K_M · 3.1 GB 300 Runs great
Best for coding Qwen3.5 2B
Alibaba · Apache 2.0
Autocomplete on 4 GB. Q3_K_M · 3.1 GB 300 Runs great
Best reasoning Qwen3.5 2B
Alibaba · Apache 2.0
Reasoning traces on 4 GB; expect long outputs. Q3_K_M · 3.1 GB 300 Runs great
Best for writing Gemma 4 E4B
Google · Apache 2.0
Readable prose on a laptop. Q3_K_M · 6.0 GB 85 Tight fit
Best vision Gemma 4 E2B
Google · Apache 2.0
Phone-class vision. Q3_K_M · 3.8 GB 134 Runs great
Best for agents Ling 3.0 Tiny 7.9B-A1.3B New
inclusionAI · MIT
Tool use and reasoning at 1.3B active, sized for edge boxes. Q3_K_M · 5.0 GB 201 Runs great
Best translation Gemma 4 E4B
Google · Apache 2.0
140+ languages on a laptop. Q3_K_M · 6.0 GB 85 Tight fit
Fastest good model LFM2.5 8B-A1B
Liquid AI · LFM Open License v1.0
1.5B active; designed for laptops without a GPU. Q3_K_M · 5.9 GB 175 Runs great
Best long context Qwen3.5 2B
Alibaba · Apache 2.0
Long documents on 4 GB. Q3_K_M · 3.1 GB
at 128K context
300 Runs great

Everything that fits

Runs great

11 of 76 · fits with headroom for a longer prompt
ModelParamsQuantWeights +KV 128KTotal VRAM headroom Tok/sRuntime
LFM2.5 8B-A1B 8.47B MoE / 1.5B act Q3_K_M 3.9 GB 1.46 GB 5.9 GB
1.1 GB free
175 Ollama Run
Ling 3.0 Tiny 7.9B-A1.3B New 7.9B MoE / 1.3B act Q3_K_M 3.6 GB 0.84 GB 5.0 GB
2.0 GB free
201 llama.cpp Run
Gemma 4 E2B 5.1B Q3_K_M 2.3 GB 0.89 GB 3.8 GB
3.2 GB free
134 Ollama Run
Gemma 3 4B 4.3B Q3_K_M 2.0 GB 3.11 GB 5.7 GB
1.3 GB free
158 Ollama Run
LFM2.5 2.6B New 2.7B Q3_K_M 1.2 GB 2.00 GB 3.8 GB
3.2 GB free
252 llama.cpp Run
Qwen3.5 2B 2.27B Q3_K_M 1.0 GB 1.50 GB 3.1 GB
3.9 GB free
300 Ollama Run
Qwen3 1.7B 1.72B Q3_K_M 0.8 GB 3.50 GB 4.9 GB
2.1 GB free
396 Ollama Run
Llama 3.2 1B Instruct 1.24B Q3_K_M 0.6 GB 4.00 GB 5.2 GB
1.8 GB free
549 Ollama Run
Gemma 3 1B 1.0B Q3_K_M 0.5 GB 0.14 GB 1.2 GB
5.8 GB free
681 Ollama Run
Qwen3.5 0.8B 0.87B Q3_K_M 0.4 GB 1.50 GB 2.5 GB
4.5 GB free
783 Ollama Run
Qwen3 0.6B 0.6B Q3_K_M 0.3 GB 3.50 GB 4.4 GB
2.6 GB free
1135 Ollama Run

Runs — tight

3 models · fits at 128K, drop context or quant to go longer
ModelParamsQuantWeights +KV 128KTotal VRAM headroom Tok/sRuntime
Gemma 4 E4B 8.0B Q3_K_M 3.6 GB 1.78 GB 6.0 GB
1.0 GB free
85 llama.cpp Run
Qwen3.5 4B 4.66B Q3_K_M 2.1 GB 4.00 GB 6.7 GB
0.3 GB free
146 llama.cpp Run
Qwen3 4B 4.02B Q3_K_M 1.8 GB 4.50 GB 6.9 GB
0.1 GB free
169 llama.cpp Run

Won't fit in VRAM

62 models · some are possible with CPU offload
ModelParamsQuantWeights +KV 128KTotal Over budget Tok/sRuntime
Qwen3.6 35B-A3B 35.9B MoE / 3.3B act Q3_K_M 16.3 GB 2.50 GB 19.4 GB +12.4 GB ~12 llama.cpp Why
Ornith 1.5 35B-A3B New this week 35.9B MoE / 3.3B act Q3_K_M 16.3 GB 2.50 GB 19.4 GB +12.4 GB ~12 llama.cpp Why
Olmo 3.1 32B Instruct 32.2B Q3_K_M 14.7 GB 4.75 GB 20.0 GB +13.0 GB ~2.8 llama.cpp Why
Nemotron 3.5 Lightning 30B-A3B New 31.6B MoE / 3.2B act Q3_K_M 14.4 GB 0.75 GB 15.7 GB +8.7 GB ~15 llama.cpp Why
Muse Glimmer 30B New 29.8B Q3_K_M 13.6 GB 1.70 GB 15.9 GB +8.9 GB ~3.9 llama.cpp Why
Granite 4.1 30B 28.9B Q3_K_M 13.2 GB 32.00 GB 45.8 GB +38.8 GB ~2.8 llama.cpp Why
Qwen3.8 27B New this week 27.8B Q3_K_M 12.7 GB 8.00 GB 21.3 GB +14.3 GB ~2.9 llama.cpp Why
Qwen3.6 27B 27.8B Q3_K_M 12.7 GB 8.00 GB 21.3 GB +14.3 GB ~2.9 llama.cpp Why
Gemma 3 27B 27.4B Q3_K_M 12.5 GB 10.41 GB 23.5 GB +16.5 GB ~2.9 llama.cpp Why
Gemma 4 26B-A4B 26.5B MoE / 3.8B act Q3_K_M 12.1 GB 5.20 GB 17.9 GB +10.9 GB ~8.9 llama.cpp Why
Devstral Small 2 24B 24B Q3_K_M 10.9 GB 20.00 GB 31.5 GB +24.5 GB ~3.3 llama.cpp Why
Mistral Small 3.2 24B 23.6B Q3_K_M 10.7 GB 20.00 GB 31.3 GB +24.3 GB ~3.4 llama.cpp Why
gpt-oss 20B 20.9B MoE / 3.6B act MXFP4 10.8 GB 3.00 GB 14.4 GB +7.4 GB ~10 llama.cpp Why
Qwen3 14B 14.8B Q3_K_M 6.7 GB 20.00 GB 27.3 GB +20.3 GB ~5.4 llama.cpp Why
DeepSeek-R1-Distill-Qwen 14B 14.8B Q3_K_M 6.7 GB 24.00 GB 31.3 GB +24.3 GB ~5.4 llama.cpp Why
Qwen2.5-Coder 14B 14.8B Q3_K_M 6.7 GB 24.00 GB 31.3 GB +24.3 GB ~5.4 llama.cpp Why
Phi-4 14B 14.7B Q3_K_M 6.7 GB 3.13 GB 10.4 GB +3.4 GB ~9.6 llama.cpp Why
Ministral 3 14B 13.9B Q3_K_M 6.3 GB 20.00 GB 26.9 GB +19.9 GB ~5.7 llama.cpp Why
Gemma 3 12B 12.2B Q3_K_M 5.6 GB 8.31 GB 14.5 GB +7.5 GB ~6.5 llama.cpp Why
Mistral NeMo 12B 12.2B Q3_K_M 5.6 GB 20.00 GB 26.2 GB +19.2 GB ~6.5 llama.cpp Why
Gemma 4 12B 12B Q3_K_M 5.5 GB 8.31 GB 14.4 GB +7.4 GB ~6.6 llama.cpp Why
Qwen3.5 9B 9.65B Q3_K_M 4.4 GB 4.00 GB 9.0 GB +2.0 GB ~16 llama.cpp Why
Ornith 1.5 9B New this week 9.41B Q3_K_M 4.3 GB 4.00 GB 8.9 GB +1.9 GB ~17 llama.cpp Why
Ministral 3 8B 8.92B Q3_K_M 4.1 GB 17.00 GB 21.7 GB +14.7 GB ~8.9 llama.cpp Why
Granite 4.1 8B 8.79B Q3_K_M 4.0 GB 20.00 GB 24.6 GB +17.6 GB ~9.1 llama.cpp Why
Fara 7B 8.29B Q3_K_M 3.8 GB 6.84 GB 11.2 GB +4.2 GB ~9.6 llama.cpp Why
Qwen3 8B 8.19B Q3_K_M 3.7 GB 18.00 GB 22.3 GB +15.3 GB ~9.7 llama.cpp Why
Llama 3.1 8B Instruct 8.03B Q3_K_M 3.7 GB 16.00 GB 20.3 GB +13.3 GB ~9.9 llama.cpp Why
DeepSeek-R1-Distill-Qwen 7B 7.62B Q3_K_M 3.5 GB 7.00 GB 11.1 GB +4.1 GB ~10 llama.cpp Why
Qwen2.5-Coder 7B 7.62B Q3_K_M 3.5 GB 7.00 GB 11.1 GB +4.1 GB ~10 llama.cpp Why
Olmo 3 7B Instruct 7.3B Q3_K_M 3.3 GB 9.50 GB 13.4 GB +6.4 GB ~11 llama.cpp Why
Mistral 7B Instruct v0.3 7.25B Q3_K_M 3.3 GB 4.00 GB 7.9 GB +0.9 GB ~31 llama.cpp Why
Ministral 3 3B 3.85B Q3_K_M 1.8 GB 13.00 GB 15.4 GB +8.4 GB ~21 llama.cpp Why
Phi-4-mini 3.8B 3.84B Q3_K_M 1.7 GB 16.00 GB 18.3 GB +11.3 GB ~21 llama.cpp Why
Granite 4.1 3B 3.4B Q3_K_M 1.5 GB 10.00 GB 12.1 GB +5.1 GB ~23 llama.cpp Why
Llama 3.2 3B Instruct 3.21B Q3_K_M 1.5 GB 14.00 GB 16.1 GB +9.1 GB ~25 llama.cpp Why
Kimi K3 2.8T-A104B New 2780B MoE / 104B act Q3_K_M 1265.4 GB 3.38 GB 1269.4 GB +1262.4 GB ~0.3 llama.cpp Why
Qwen3.8 2.4T-A95B New 2446B MoE / 95B act Q3_K_M 1113.4 GB 11.50 GB 1125.5 GB +1118.5 GB ~0.3 llama.cpp Why
DeepSeek V4 Pro 1.6T-A49B New 1650B MoE / 49B act Q3_K_M 751.1 GB 8.58 GB 760.2 GB +753.2 GB ~0.6 llama.cpp Why
Kimi K2.6 1T-A32B 1027B MoE / 32B act Q3_K_M 467.5 GB 8.58 GB 476.7 GB +469.7 GB ~1.0 llama.cpp Why
GLM-5.2 744B-A40B 753B MoE / 40B act Q3_K_M 342.8 GB 10.97 GB 354.3 GB +347.3 GB ~0.8 llama.cpp Why
DeepSeek-R1 671B 671B MoE / 37B act Q3_K_M 305.4 GB 8.58 GB 314.6 GB +307.6 GB ~0.8 llama.cpp Why
Qwen3.5 397B-A17B 403B MoE / 17B act Q3_K_M 183.4 GB 3.75 GB 187.8 GB +180.8 GB ~1.8 llama.cpp Why
Ornith 1.5 397B-A17B New this week 397B MoE / 17B act Q3_K_M 180.7 GB 3.75 GB 185.1 GB +178.1 GB ~1.8 llama.cpp Why
DeepSeek V4 Flash 284B-A13B New 284B MoE / 13B act Q3_K_M 129.3 GB 6.05 GB 135.9 GB +128.9 GB ~2.4 llama.cpp Why
Qwen3 235B-A22B 235B MoE / 22B act Q3_K_M 107.0 GB 23.50 GB 131.1 GB +124.1 GB ~1.4 llama.cpp Why
Qwen3.5 122B-A10B 125B MoE / 10B act Q3_K_M 56.9 GB 3.00 GB 60.5 GB +53.5 GB ~3.2 llama.cpp Why
Nemotron 3 Super 120B-A12B 124B MoE / 12B act Q3_K_M 56.4 GB 1.00 GB 58.0 GB +51.0 GB ~2.8 llama.cpp Why
Ling 3.0 Flash 124B-A5B New 124B MoE / 5.1B act Q3_K_M 56.4 GB 0.98 GB 58.0 GB +51.0 GB ~6.6 llama.cpp Why
Mistral Small 4 119B-A6B 119B MoE / 6.5B act Q3_K_M 54.2 GB 2.81 GB 57.6 GB +50.6 GB ~5.0 llama.cpp Why
gpt-oss 120B 117B MoE / 5.1B act MXFP4 60.5 GB 4.50 GB 65.6 GB +58.6 GB ~5.4 llama.cpp Why
Llama 4 Scout 109B-A17B 109B MoE / 17B act Q3_K_M 49.6 GB 7.13 GB 57.3 GB +50.3 GB ~1.8 llama.cpp Why
Llama 3.3 70B Instruct 70.6B Q3_K_M 32.1 GB 40.00 GB 72.7 GB +65.7 GB ~1.1 llama.cpp Why
DeepSeek-R1-Distill-Llama 70B 70.6B Q3_K_M 32.1 GB 40.00 GB 72.7 GB +65.7 GB ~1.1 llama.cpp Why
LLM-jp 4 33B Thinking New this week 33.2B Q3_K_M 15.1 GB 16.00 GB 31.7 GB +24.7 GB ~2.4 llama.cpp Why
Qwen3 32B 32.8B Q3_K_M 14.9 GB 32.00 GB 47.5 GB +40.5 GB ~2.4 llama.cpp Why
DeepSeek-R1-Distill-Qwen 32B 32.8B Q3_K_M 14.9 GB 32.00 GB 47.5 GB +40.5 GB ~2.4 llama.cpp Why
Qwen2.5-Coder 32B 32.8B Q3_K_M 14.9 GB 32.00 GB 47.5 GB +40.5 GB ~2.4 llama.cpp Why
Gemma 4 31B 31.3B Q3_K_M 14.2 GB 20.78 GB 35.6 GB +28.6 GB ~2.5 llama.cpp Why
GLM-4.7-Flash 30B-A3B 31.2B MoE / 3B act Q3_K_M 14.2 GB 6.61 GB 21.4 GB +14.4 GB ~10 llama.cpp Why
Qwen3 30B-A3B 30.5B MoE / 3.3B act Q3_K_M 13.9 GB 12.00 GB 26.5 GB +19.5 GB ~9.3 llama.cpp Why
Qwen3 Coder 30B-A3B 30.5B MoE / 3.3B act Q3_K_M 13.9 GB 12.00 GB 26.5 GB +19.5 GB ~9.3 llama.cpp Why

Totals = quantised weights + f16 KV cache at 128K tokens + 0.6 GB runtime overhead, against 7.0 GB usable VRAM (8 GB less display and driver reserve). Tokens per second are estimated from 512 GB/s peak memory bandwidth at batch 1 — not measured. Read the method.