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localllm
日本語

Discrete GPU

GeForce RTX 5060 Ti

Data as of

Memory bandwidth
448 GB/s
Source
Checked:

With 8 GB

One entry per model, up to 30, sorted by popularity. For each model we show the largest (most precise) quantization that fits in this memory with a context of at least 8K tokens. The context length is the longest one that quantization fits (for models whose maximum is under 8K, such as embedding models, that maximum). Models that are not for chat or text generation are labelled with their use. "Left" is the memory minus the estimate; under 5% of the memory is marked "tight" (not a guarantee that it fits).

  • Qwen3.8-27B UD-IQ1_M
    Context length 8,192 Estimated 8.47 GB 0.12 GB left (tight) Speed 40–53
  • Ornith-1.5-9B Q5_K_M
    Context length 16,384 Estimated 8.49 GB 0.10 GB left (tight) Speed 39–52
  • gemma-4-12B-it IQ4_XS Image input
    Context length 8,192 Estimated 8.49 GB 0.10 GB left (tight) Speed 40–53
  • Ornith-1.0-9B Q5_K_M
    Context length 16,384 Estimated 8.13 GB 0.46 GB left Speed 42–55
  • mxbai-embed-large-v1 F32 Embedding (not for chat)
    Context length 512 Estimated 2.41 GB 6.18 GB left Speed 201–268
  • Qwen3.5-9B-The-Defiant-Fable-Uncensored-Heretic-NEO-IMATRIX-MAX-MTP Q4_K_M Image input
    Context length 8,192 Estimated 8.35 GB 0.24 GB left (tight) Speed 39–51
  • MOSS-Music-8B-Instruct Q4_K_M
    Context length 16,384 Estimated 8.45 GB 0.14 GB left (tight) Speed 52–69
  • Qwen3-VL-8B-Instruct UD-Q5_K_XL Image input
    Context length 8,192 Estimated 7.94 GB 0.65 GB left Speed 46–61
  • Qwen3.5-9B Q5_K_M Image input
    Context length 8,192 Estimated 8.48 GB 0.11 GB left (tight) Speed 38–50
  • Ornith-1.5-9B-uncensored Q5_K_M
    Context length 16,384 Estimated 8.10 GB 0.49 GB left Speed 42–55
  • Qwen3.5-4B UD-Q8_K_XL Image input
    Context length 32,768 Estimated 8.12 GB 0.47 GB left Speed 45–60
  • Wan2.1 Q4_K_M
    Context length 16,384 Estimated 8.08 GB 0.51 GB left Speed 47–62
  • Qwen3-ASR-1.7B F16 Speech / audio
    Context length 16,384 Estimated 6.82 GB 1.77 GB left Speed 66–88
  • gemma-4-E4B-it-qat-q4_0 Q4_0 Image input
    Context length 131,072 Estimated 8.42 GB 0.17 GB left (tight) Speed 52–70
  • Ternary-Bonsai-2-9B Q8_0 Image input
    Context length 131,072 Estimated 8.07 GB 0.52 GB left Speed 100–134
  • HyperCLOVAX-SEED-Text-Instruct-1.5B-Q4_K_M Q4_K_M
    Context length 65,536 Estimated 8.34 GB 0.25 GB left (tight) Speed 237–316
  • Hy-MT2-7B Q6_K
    Context length 8,192 Estimated 8.04 GB 0.55 GB left Speed 44–58
  • Ternary-Bonsai-2-2B Q2_0 Image input
    Context length 262,144 Estimated 4.83 GB 3.76 GB left Speed 492–656
  • MiMo-V2.6-Distill-Qwen-9B Q5_K_M Image input
    Context length 16,384 Estimated 8.51 GB 0.08 GB left (tight) Speed 39–52
  • Cyber-Ornith-1.5-9B-OBLITERATED Q5_K_M
    Context length 16,384 Estimated 8.10 GB 0.49 GB left Speed 42–55
  • Sharp-Spark-X2.5-4B Q6_K_XL
    Context length 65,536 Estimated 6.95 GB 1.64 GB left Speed 74–99
  • AdaVaR-3B F16
    Context length 32,768 Estimated 8.23 GB 0.36 GB left (tight) Speed 44–58
  • Qwen3-8B Q5_K_L
    Context length 8,192 Estimated 8.29 GB 0.30 GB left (tight) Speed 43–57
  • Qwen3.5-9B-Kimi-k3-Distilled Q5_K_M
    Context length 16,384 Estimated 8.28 GB 0.31 GB left (tight) Speed 40–54
  • Qwen3-4B-Instruct-2507 UD-Q8_K_XL
    Context length 16,384 Estimated 8.32 GB 0.27 GB left (tight) Speed 53–71
  • B1-9B Q5_K_M
    Context length 16,384 Estimated 8.28 GB 0.31 GB left (tight) Speed 40–54
  • Qwen3-VL-4B-Instruct UD-Q8_K_XL Image input
    Context length 16,384 Estimated 8.32 GB 0.27 GB left (tight) Speed 53–71
  • Qwen2.5-7B-Instruct Q6_K_L
    Context length 16,384 Estimated 8.31 GB 0.28 GB left (tight) Speed 41–55
  • Qwen3-4B UD-Q8_K_XL
    Context length 16,384 Estimated 8.32 GB 0.27 GB left (tight) Speed 53–71
  • Qwen-Image-2.1-Turbo-Uncensored Q5_K Image / video generation
    Context length 8,192 Estimated 8.34 GB 0.25 GB left (tight) Speed 43–57

With 16 GB

One entry per model, up to 30, sorted by popularity. For each model we show the largest (most precise) quantization that fits in this memory with a context of at least 8K tokens. The context length is the longest one that quantization fits (for models whose maximum is under 8K, such as embedding models, that maximum). Models that are not for chat or text generation are labelled with their use. "Left" is the memory minus the estimate; under 5% of the memory is marked "tight" (not a guarantee that it fits).

Frequently asked questions

Which local LLMs run on GeForce RTX 5060 Ti?
On this site, 834 models have a quantization that fits in 16 GB at 8,192 tokens (estimated). Popular ones include Qwen3.8-27B, Ornith-1.5-9B, Huihui-Qwen3.6-35B-A3B-abliterated-MTP, Ornith-1.5-35B-A3B, Huihui-Qwen3.8-27B-abliterated.
What is the largest model that runs on GeForce RTX 5060 Ti?
Among the models listed here, Qwen3.8-Flash-Next-FP4-Local-Strata (about 51.2B); BF16 fits in 16 GB (estimated at 8,192 tokens).
How fast does GeForce RTX 5060 Ti generate text?
With 448 GB/s of memory bandwidth, Qwen3.8-27B at UD-Q4_K_S (15.4 GB) runs at an estimated 18–23 tokens per second (60–80% of bandwidth ÷ file size; prompt processing not included).