NVIDIA · Blackwell

What runs on a RTX 5060 Ti 8GB

8 GB at 448 GB/s. The largest model that fits at Q4_K_M is GLM-4 9B, at roughly 52.6 tokens per second.

Fits, but tight

6.4 GB of 6.7 GB · 96%
07 GB
Weights 4.6 GB
KV cache 1.0 GB
Runtime overhead 0.8 GB

This fits with almost nothing to spare. A background application claiming VRAM will push it over. Drop to the next quantisation down, or quantise the KV cache to Q8_0 — that halves the cache for no meaningful quality loss.

Generation57.3tok/s
Prompt processing1229tok/s
Max context10Ktokens
KV per 1K tokens0GB

Every quantisation of Llama 3.1 8B on a RTX 5060 Ti 8GB

Highlighted row is the highest quality that still fits at 8K context.

QuantisationbpwWeights TotalVerdictMax ctxtok/s
FP16 / BF16 16.00 15.0 GB 16.8 GB Won't fit 3.73
INT8 / W8A8 8.50 7.7 GB 9.5 GB Won't fit 11.1
Q8_0 (GGUF) 8.50 7.7 GB 9.5 GB Won't fit 11.1
FP8 (E4M3) 8.00 7.5 GB 9.3 GB Won't fit 11.4
Q6_K 6.56 6.1 GB 8.0 GB Won't fit 19.2
AWQ 4-bit 4.25 5.4 GB 7.2 GB Won't fit 4K 28.4
GPTQ 4-bit 4.25 5.4 GB 7.2 GB Won't fit 4K 28.4
MXFP4 4.25 5.4 GB 7.2 GB Won't fit 4K 28.4
Q5_K_M 5.67 5.3 GB 7.1 GB Won't fit 5K 32.4
Q5_K_S 5.52 5.2 GB 7.0 GB Won't fit 6K 37.7
Q4_K_M 4.85 4.6 GB 6.4 GB Fits, but tight 10K 57.3
Q4_K_S 4.58 4.4 GB 6.2 GB Fits, but tight 12K 59.8
Q4_0 4.55 4.4 GB 6.2 GB Fits, but tight 12K 60.1
IQ4_XS 4.25 4.1 GB 5.9 GB Runs comfortably 14K 63.2
Q3_K_M 3.91 3.8 GB 5.7 GB Runs comfortably 16K 67.2
IQ3_M 3.70 3.7 GB 5.5 GB Runs comfortably 18K 69.9
IQ3_XXS 3.06 3.2 GB 5.0 GB Runs comfortably 22K 79.7
Q2_K 2.63 2.8 GB 4.6 GB Runs comfortably 25K 88.0
IQ2_XXS 2.06 2.3 GB 4.2 GB Runs comfortably 28K 102
IQ1_M 1.75 2.1 GB 3.9 GB Runs comfortably 30K 112

Models on a RTX 5060 Ti 8GB

Q4_K_M at 8K context. Bandwidth sets the speed; capacity sets the ceiling.

ModelParamsWeightsVerdictMax ctxtok/s
DeepSeek-R1 671B-A37B 671B 379.0 GB Won't fit 1.97
Qwen3 235B-A22B 235.1B 132.8 GB Won't fit 3.19
gpt-oss 120B-A5.1B 116.8B 66.0 GB Won't fit 13.7
Llama 4 Scout 109B-A17B 109B 61.7 GB Won't fit 4.28
Qwen2.5 72B 72.7B 41.2 GB Won't fit 1.06
Llama 3.1 70B 70.5B 40.0 GB Won't fit 1.09
Mixtral 8x7B 46.7B 26.4 GB Won't fit 6.20
Command R 35B 35.0B 20.1 GB Won't fit 1.68
Yi-1.5 34B 34.4B 19.5 GB Won't fit 2.49
Qwen3 32B 32.8B 18.6 GB Won't fit 2.60
Qwen2.5-Coder 32B 32.8B 18.6 GB Won't fit 2.60
DeepSeek-R1-Distill-Qwen 32B 32.8B 18.6 GB Won't fit 2.60
Qwen3 30B-A3B 30.5B 17.3 GB Won't fit 22.4
Gemma 3 27B 27.4B 15.6 GB Won't fit 3.50
Mistral Small 24B 23.6B 13.4 GB Won't fit 4.16
gpt-oss 20B-A3.6B 20.9B 11.9 GB Won't fit 29.6
Qwen3 14B 14.8B 8.5 GB Won't fit 8.43
Phi-4 14B 14.7B 8.4 GB Won't fit 8.05
Mistral NeMo 12B 12.3B 7.0 GB Won't fit 12.4
Gemma 3 12B 12.2B 7.0 GB Won't fit 14.9
GLM-4 9B 9.4B 5.4 GB Fits, but tight 13K 52.6
Qwen3 8B 8.2B 4.7 GB Fits, but tight 8K 55.4
Llama 3.1 8B 8.0B 4.6 GB Fits, but tight 10K 57.3
DeepSeek-R1-Distill-Llama 8B 8.0B 4.6 GB Fits, but tight 10K 57.3
Qwen2.5 7B 7.6B 4.4 GB Runs comfortably 28K 63.6
Mistral 7B v0.3 7.3B 4.1 GB Runs comfortably 14K 63.4
Gemma 3 4B 4.3B 2.5 GB Runs comfortably 128K 108
Qwen3 4B 4.0B 2.3 GB Runs comfortably 26K 101
Llama 3.2 3B 3.2B 1.8 GB Runs comfortably 37K 127
Llama 3.2 1B 1.2B 0.7 GB Runs comfortably 128K 339

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