Intel · workstation
Arc Pro A40 6GB
Arc Pro A40 6GB has 6 GB of VRAM at 192 GB/s — about 5.58 GiB usable after driver and compositor overhead. 937 of 2118 indexed models fit at 64K context with q4_0 KV.
Spec sheet· bandwidth, theoreticalFrom the file· fit from summed bytesPredicted· speed
Memory
6 GB
GDDR6
Bandwidth
192 GB/s
96-bit bus
Tensor FP16
—
dense
TDP
50 W
text 771audio asr 38audio tts 19vision language 81embedding 25video 3
What fits at 64K context
largest quantization that fits, per model · 937 of 2118 indexed
| Model | Best quant | Params | Weights● | KV● | Total in memory◐ | Headroom◐ | tok/s◐ |
|---|---|---|---|---|---|---|---|
| granite-3.3-8b-instruct | UD-IQ1_M | 8.2B | 1.93 GiB | 2.81 GiB | 5.57 GiB | 0.01 GiB | 22±30% |
| gemma-4-E4B-uncensored | I1-Q3_K_M | 7.9B | 4.49 GiB | 0.27 GiB | 5.57 GiB | 0.01 GiB | 22±30% |
| gemma-4-E4B-it-qat-q4_0-unquantized-heretic | I1-Q3_K_M | 7.9B | 4.49 GiB | 0.27 GiB | 5.57 GiB | 0.01 GiB | 22±30% |
| gemma-4-E4B-it-qat-heretic_decensored | I1-Q3_K_M | 7.9B | 4.49 GiB | 0.27 GiB | 5.57 GiB | 0.01 GiB | 22±30% |
| gemma-4-E4B-it-QAT-SOMPOA-heresy | I1-Q3_K_M | 7.9B | 4.49 GiB | 0.27 GiB | 5.57 GiB | 0.01 GiB | 22±30% |
| gemma4-e4b-mahou-nsfw | I1-Q3_K_M | 7.9B | 4.49 GiB | 0.27 GiB | 5.57 GiB | 0.01 GiB | 22±30% |
| gemma-4-E4B-it-mentalchat16k | I1-Q3_K_M | 7.9B | 4.49 GiB | 0.27 GiB | 5.57 GiB | 0.01 GiB | 22±30% |
| gemma4-E4B-it-abliterated | I1-Q3_K_M | 7.9B | 4.49 GiB | 0.27 GiB | 5.57 GiB | 0.01 GiB | 22±30% |
| gemma-4-E4B-it-OBLITERATED | I1-Q3_K_M | 8.0B | 4.49 GiB | 0.27 GiB | 5.57 GiB | 0.01 GiB | 22±30% |
| Teuken-7B-instruct-research-v0.4 | I1-Q4_0 | 7.5B | 4.17 GiB | 0.56 GiB | 5.57 GiB | 0.01 GiB | 22±30% |
| canary-qwen-2.5b | BF16 | 2.6B | 4.73 GiB | 0.00 GiB | 5.57 GiB | 0.01 GiB | 22±30% |
| EXAONE-Deep-7.8B | Q4_K_L | 7.8B | 4.73 GiB | 0.00 GiB | 5.57 GiB | 0.01 GiB | 22±30% |
| EXAONE-3.5-7.8B-Instruct | Q4_K_L | 7.8B | 4.73 GiB | 0.00 GiB | 5.57 GiB | 0.01 GiB | 22±30% |
| Qwen3-TTS-12Hz-0.6B-Base | Q4_K_M | 915M | 4.72 GiB | 0.00 GiB | 5.57 GiB | 0.01 GiB | 22±30% |
| VoxCPM2 | F16 | 2.3B | 4.72 GiB | 0.00 GiB | 5.57 GiB | 0.01 GiB | 22±30% |
| Qwen3.5-9B-Coder | I1-IQ3_S | 9.7B | 4.17 GiB | 0.56 GiB | 5.57 GiB | 0.01 GiB | 22±30% |
| Qwythos-9B-Claude-Mythos-5-1M-MTP | I1-IQ3_S | 9.7B | 4.17 GiB | 0.56 GiB | 5.57 GiB | 0.01 GiB | 22±30% |
| Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated | I1-IQ3_S | 9.7B | 4.17 GiB | 0.56 GiB | 5.57 GiB | 0.01 GiB | 22±30% |
| Qwen3.5-9B-Fable-5-v1 | I1-IQ3_S | 9.7B | 4.17 GiB | 0.56 GiB | 5.57 GiB | 0.01 GiB | 22±30% |
| Qwythos-9B-v2 | I1-IQ3_S | 9.7B | 4.17 GiB | 0.56 GiB | 5.57 GiB | 0.01 GiB | 22±30% |
| PINQWEN-3.5-9B-1M-BF16 | I1-IQ3_S | 9.7B | 4.17 GiB | 0.56 GiB | 5.57 GiB | 0.01 GiB | 22±30% |
| Openprose-2-Flash | I1-IQ3_S | 9.7B | 4.17 GiB | 0.56 GiB | 5.57 GiB | 0.01 GiB | 22±30% |
| Qwen3.5-9B-Nikusui-v1 | I1-IQ3_S | 9.7B | 4.17 GiB | 0.56 GiB | 5.57 GiB | 0.01 GiB | 22±30% |
| Ornstein-3.5-9B-V1.5 | I1-IQ3_S | 9.7B | 4.17 GiB | 0.56 GiB | 5.57 GiB | 0.01 GiB | 22±30% |
| Ornith-1.0-9B-heretic-MTP | I1-IQ3_S | 9.4B | 4.17 GiB | 0.56 GiB | 5.57 GiB | 0.01 GiB | 22±30% |
| Tess-4-9B | I1-IQ3_S | 9.7B | 4.17 GiB | 0.56 GiB | 5.57 GiB | 0.01 GiB | 22±30% |
| dotwebs-1 | I1-IQ3_S | 9.7B | 4.17 GiB | 0.56 GiB | 5.57 GiB | 0.01 GiB | 22±30% |
| Hemlock-Qwopus3.5-9B-Coder | I1-IQ3_S | 9.7B | 4.17 GiB | 0.56 GiB | 5.57 GiB | 0.01 GiB | 22±30% |
| gemma-4-E4B-it-heretic | Q4_K_S | 8.0B | 4.48 GiB | 0.27 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
| Luna-7B-A4BMoE | I1-IQ2_M | 6.7B | 2.22 GiB | 2.53 GiB | 5.56 GiB | 0.02 GiB | 16±37% |
| t5-v1_1-xxl | Q2_K | 4.8B | 4.72 GiB | 0.00 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
| Qwen3-VL-4B-Instruct-Unredacted-MAX | I1-Q4_K_S | 4.4B | 2.22 GiB | 2.53 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
| Qwen3-VL-4B-Thinking | Q4_K_S | 4.4B | 2.22 GiB | 2.53 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
| Qwen3-VL-4B-Thinking-Unredacted-MAX | I1-Q4_K_S | 4.4B | 2.22 GiB | 2.53 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
| Zubr1.0-VL-4B | I1-Q4_K_S | 4.4B | 2.22 GiB | 2.53 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
| Qwen3-VL-4B-Instruct-Uncensored-abliterated | Q4_K_S | 4.4B | 2.22 GiB | 2.53 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
| PopiT-Qwen3-4B-Medical-SFT-1128 | Q4_K_S | 4.0B | 2.22 GiB | 2.53 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
| Huihui-Qwen3-VL-4B-Instruct-abliterated | I1-Q4_K_S | 4.4B | 2.22 GiB | 2.53 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
| Qwen3-VL-4B-Instruct-Uncensored | I1-Q4_K_S | 4.4B | 2.22 GiB | 2.53 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
| Qwen3-VL-4B-Instruct | Q4_K_S | 4.4B | 2.22 GiB | 2.53 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
| OpenCaption-4B-VL-SFT-v1.0 | I1-Q4_K_S | 4.4B | 2.22 GiB | 2.53 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
| Parable-Qwen3-4B-Claude-Fable-5 | I1-Q4_K_S | 4.0B | 2.22 GiB | 2.53 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
| Logics-Parsing-v2 | Q4_K_S | 4.4B | 2.22 GiB | 2.53 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
| Jan-v1-4B | Q4_K_S | 4.0B | 2.22 GiB | 2.53 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
| Qwen3-4b-Z-Image-Turbo-AbliteratedV1 | I1-Q4_K_S | 4.0B | 2.22 GiB | 2.53 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
| Z-Image-Engineer-V6 | Q4_K_S | 4.0B | 2.22 GiB | 2.53 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
| Qwen3-4B | Q4_K_S | 4.0B | 2.22 GiB | 2.53 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
| Huihui-Qwen3-4B-Instruct-2507-abliterated | Q4_K_S | 4.0B | 2.22 GiB | 2.53 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
| Josiefied-Qwen3-4B-abliterated-v2 | Q4_K_S | 4.0B | 2.22 GiB | 2.53 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
| Qwen3-4B-Thinking-2507 | Q4_K_S | 4.0B | 2.22 GiB | 2.53 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
| Jan-nano-128k | Q4_K_S | 4.0B | 2.22 GiB | 2.53 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
| Qwen3-4B-Instruct-2507 | Q4_K_S | 4.0B | 2.22 GiB | 2.53 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
| Jan-nano | Q4_K_S | 4.0B | 2.22 GiB | 2.53 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
| Qwen3-4B-abliterated | Q4_K_S | 4.0B | 2.22 GiB | 2.53 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
| Neuron-4B-Instruct | I1-Q4_K_S | 4.0B | 2.22 GiB | 2.53 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
| ChineseErrorCorrector4-4B | I1-Q4_K_S | 4.0B | 2.22 GiB | 2.53 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
| FastContext-1.0-4B-SFT-abliterated | I1-Q4_K_S | 4.0B | 2.22 GiB | 2.53 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
| Qwen3-4B-Instruct_NSFW-V2.1 | I1-Q4_K_S | 4.0B | 2.22 GiB | 2.53 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
| FastContext-1.0-4B-SFT | I1-Q4_K_S | 4.0B | 2.22 GiB | 2.53 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
| fable-traces-abliterated | I1-Q4_K_S | 4.0B | 2.22 GiB | 2.53 GiB | 5.56 GiB | 0.02 GiB | 22±30% |
Speed is modeled, not measured: decode is memory-bandwidth bound, so tokens per second is bytes read per token against achievable bandwidth. Mixture-of-experts models carry a wider band because only the routed experts are read each step, and few have been measured publicly.
Questions people ask
- What AI models can a Arc Pro A40 6GB run?
- 937 of 2118 indexed open-weight models fit a Arc Pro A40 6GB at 65,536 context with q4_0 KV cache, the largest being granite-3.3-8b-instruct at UD-IQ1_M. That covers text, vision-language, image, video and speech models.
- How much usable memory does a Arc Pro A40 6GB actually have?
- Its nameplate is 6 GB, but about 5.58 GiB is available to a model once driver and compositor overhead is accounted for.
- Is a Arc Pro A40 6GB fast for local AI?
- Its memory bandwidth is 192 GB/s, and that figure — not teraflops — is what governs token generation speed. Capacity decides what you can run; bandwidth decides how fast it runs.