Every open model in our directory, ranked by how well it runs on Origin PC L-CLASS v2 (48GB) at 4-bit. Grades weigh whether the model fits in memory and how fast it should run.
Origin PC L-CLASS v2 has 48 GB of VRAM, enough to run 238 of the 297 open models we track at 4-bit. The largest that still fits well is Qwen3-235B-A22B (235B), and the top-rated is K2-Horizon-MoVA-36B-A4B at about 39 tok/s.
238 of 297 models run comfortably on Origin PC L-CLASS v2.
See full Origin PC L-CLASS v2 specs and pricingThe top models this device can run at 4-bit, ranked by fit and speed.
| Model | Grade | Speed | VRAM |
|---|---|---|---|
| K2-Horizon-MoVA-36B-A4BInstitute of Foundation Models | SS | 39.4 tok/s | 19.6 GB |
| Holo4-27BHcompany | SS | 45.3 tok/s | 17.0 GB |
| minimax-m2.5MiniMax | SS | 34.0 tok/s | 22.7 GB |
| Mixtral 8x7B InstructMistral AI | SS | 68.0 tok/s | 11.4 GB |
| AliceAI-Foundation-80B-A3B-Baseyandex | SS | 90.6 tok/s | 8.5 GB |
| Xing4.0-29B-A4BChina Telecom AI | SS | 68.9 tok/s | 11.2 GB |
| Gemma 4 26B-A4B ITGoogle | SS | 70.2 tok/s | 11.0 GB |
| DiffusionGemma 26B-A4BGoogle | SS | 73.7 tok/s | 10.5 GB |
| Nemotron 3 Nano OmniNVIDIA | SS | 90.6 tok/s | 8.5 GB |
| Qwen3.6 35B-A3BAlibaba | SS | 90.6 tok/s | 8.5 GB |
| Qwen3.5-35B-A3BAlibaba | SS | 90.6 tok/s | 8.5 GB |
| KolibriAleph Alpha | SS | 29.5 tok/s | 26.2 GB |
K2-Horizon-MoVA-36B-A4BInstitute of Foundation Models | 36B(4B active) | SS | 39.4 tok/s | 19.6 GB | |
Holo4-27BHcompany | 27B | SS | 45.3 tok/s | 17.0 GB | |
minimax-m2.5MiniMax | 230B(10B active) | SS | 34.0 tok/s | 22.7 GB | |
Mixtral 8x7B InstructMistral AI | 46.7B(12.9B active) | SS | 68.0 tok/s | 11.4 GB | |
| 81.29B(3B active) | SS | 90.6 tok/s | 8.5 GB | ||
Xing4.0-29B-A4BChina Telecom AI | 29B(4B active) | SS | 68.9 tok/s | 11.2 GB | |
Gemma 4 26B-A4B ITGoogle | 26B(4B active) | SS | 70.2 tok/s | 11.0 GB | |
DiffusionGemma 26B-A4BGoogle | 25.2B(3.8B active) | SS | 73.7 tok/s | 10.5 GB | |
| Ad | |||||
Nemotron 3 Nano OmniNVIDIA | 30B(3B active) | SS | 90.6 tok/s | 8.5 GB | |
Qwen3.6 35B-A3BAlibaba | 35B(3B active) | SS | 90.6 tok/s | 8.5 GB | |
Qwen3.5-35B-A3BAlibaba | 35B(3B active) | SS | 90.6 tok/s | 8.5 GB | |
KolibriAleph Alpha | 78B(3B active) | SS | 29.5 tok/s | 26.2 GB | |
North Mini CodeCohere | 30B(3B active) | SS | 92.2 tok/s | 8.4 GB | |
Qwen3.5-122B-A10BAlibaba | 122B(10B active) | SS | 28.3 tok/s | 27.3 GB | |
| 8B | SS | 58.0 tok/s | 13.3 GB | ||
Qwen3-30B-A3BAlibaba | 30B(3B active) | SS | 143.5 tok/s | 5.4 GB | |
| Ad | |||||
Llama 2 13B ChatMeta | 13B | SS | 91.3 tok/s | 8.5 GB | |
Falcon 40B InstructTechnology Innovation Institute | 40B | SS | 31.7 tok/s | 24.4 GB | |
Holo4-35B-A3BHcompany | 35B(3B active) | SS | 330.5 tok/s | 2.3 GB | |
Qwen3.5-9BAlibaba | 9B | SS | 31.4 tok/s | 24.6 GB | |
LensVLM-9BApple | 9B | AA | 128.5 tok/s | 6.0 GB | |
| 9B | AA | 128.5 tok/s | 6.0 GB | ||
| 8B | AA | 136.4 tok/s | 5.7 GB | ||
Mellum2.1JetBrains | 12B(2.5B active) | AA | 380.3 tok/s | 2.0 GB | |
| Ad | |||||
Apertus 8BEPFL, ETH Zurich, CSCS | 8B | AA | 143.1 tok/s | 5.4 GB | |

Model Compatibility
Use the calculator to weigh this device against any other, model by model, with speed and fit scores.
Straight answers to the questions we hear most often.
Can't find what you're looking for? Book a Discovery Call
K2-Horizon-MoVA-36B-A4B is the highest-rated model that runs on Origin PC L-CLASS v2 at 4-bit, at about 39 tok/s. In total, Origin PC L-CLASS v2 can run 238 of the 297 open models we track.
We size each model at 4-bit (Q4_K_M), add the KV cache for its context length and a fixed runtime overhead, then compare that to this device VRAM. Each model is graded on how comfortably it fits and how fast it should run on this card.
It is an estimate of decode speed in tokens per second at 4-bit, based on this device memory bandwidth and each model size. Real speed depends on your runtime, batch size, and context length, so use it to compare models, not as a hard promise.
Lower-bit quantization shrinks a model so more of them fit. These grades already assume 4-bit, which is the common local default. Going below 4-bit can squeeze a larger model in at some quality cost; going above needs more VRAM and may not fit.
Mixture-of-experts models only activate a fraction of their parameters at a time, so their runtime memory is closer to the active size than the headline size. We score fit on the active parameters, which is why some very large models still fit.