RunsLocalGPU checkerLocal AI toolsv1.8 · data Oct 14, 2026

All hardware / RTX 5050

What AI models can the RTX 5050 run?

With 8 GB of VRAM, the RTX 5050 runs 4 of 22 popular open models fully in fast memory at Q4_K_M or better (8K context, assuming 32 GB of DDR5 system RAM). The largest that fit are Qwen3.5 9B (Q4_K_M), Gemma 4 E4B (Q6_K), Gemma 4 E2B (Q8_0). Fastest: Gemma 4 E2B at about 79 tokens/sec and Gemma 4 E4B at about 52 tokens/sec. 10 more run with offload to system RAM, but slower.

Check with your own RAM and context length
ModelResultBest quantMemory neededEst. speed
Gemma 4 E2B
small
Runs on GPUQ8_06.1 GB79 tok/s
Gemma 4 E4B
small · audio
Runs on GPUQ6_K7.4 GB52 tok/s
Ministral 3 3B
small
Runs on GPUQ8_04.8 GB48 tok/s
Qwen3.5 9B
general
Runs on GPUQ4_K_M6.9 GB33 tok/s
gpt-oss-20b
MoE · reasoning
Needs offloadQ4_K_M13.6 GB33 tok/s
Gemma 4 12B
general · audio
Lower quality fitQ3_K_M6.9 GB33 tok/s
Qwen3.6 35B-A3B
MoE · coding
Needs offloadQ4_K_M22.2 GB31 tok/s
Gemma 4 26B A4B
MoE · vision
Needs offloadQ4_K_M16.4 GB28 tok/s
Phi-4 14B
reasoning
Needs offloadQ4_K_M11.0 GB9.9 tok/s
Mistral Small 3.1 24B
general
Needs offloadQ4_K_M16.4 GB4.5 tok/s
Qwen3.6 27B
coding
Needs offloadQ4_K_M17.5 GB3.8 tok/s
Qwen3.8 27B
coding
Needs offloadQ4_K_M18.0 GB3.7 tok/s
Granite 4.2 30B
general
Needs offloadQ4_K_M18.6 GB3.4 tok/s
Gemma 4 31B
general · vision
Needs offloadQ4_K_M19.8 GB3.2 tok/s
Hermes 4.3 36B
general
Needs offloadQ4_K_M23.9 GB2.5 tok/s
Llama 3.3 70B
general
Too bigQ4_K_M45.9 GB—
Llama 4 Scout
MoE · vision
Too bigQ4_K_M68.1 GB—
gpt-oss-120b
MoE · reasoning
Too bigQ4_K_M72.0 GB—
Qwen3.5 122B-A10B
MoE
Too bigQ4_K_M75.3 GB—
Qwen3.8-Flash-Next
MoE
Too bigQ4_K_M107.8 GB—
GLM-5.3-Flash
MoE · coding
Too bigQ4_K_M196.0 GB—
DeepSeek V4.1-Flash
MoE · coding
Too bigQ4_K_M335.8 GB—

Specs used: 8 GB of VRAM, 320 GB/s memory bandwidth. Speeds are estimates for generating text with llama.cpp-style runtimes; real numbers usually land within about 20%.

Apps that support the RTX 5050