Your rig

GeForce RTX 5060 · 8 GB

32 GB system RAM · Blackwell · 448 GB/s · 7.0 GB usable VRAM
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Context length

KV cache at f16, 32K tokens

Quality floor
Q8_0 — near-lossless Q6_K Q5_K_M Q4_K_M — recommended Q3_K_M Q2_K — damaged
KV cache type
System RAM (GB)
Runtime
Ollamallama.cppLM StudiovLLM

4 of 5 runtimes drive this device.

Allow CPU offload Include partial-offload fits

Offloaded layers run at 60 GB/s host bandwidth — expect single-digit tokens per second.

Which one should I actually run?

Best models for your GeForce RTX 5060

Updated 21 Aug 2026 5 new this week, 14 this month

What do you want to do? Each row is the best-ranked model on that use case's shortlist that fits at Q5_K_M and 32K. The ordering is editorial; the sizes and speeds are computed. How the shortlists work.

RecommendationModelWhyQuant · totalTok/s est.
Best overall Qwen3.5 4B
Alibaba · Apache 2.0
The 6–8 GB pick: a real assistant in 3.4 GB of weights. Q5_K_M · 4.7 GB 88 Runs great
Best for coding Qwen3.5 4B
Alibaba · Apache 2.0
A coding agent in 3.4 GB — the 6–8 GB answer. Q5_K_M · 4.7 GB 88 Runs great
Best reasoning Qwen3.5 4B
Alibaba · Apache 2.0
Step-by-step reasoning in 8 GB. Q5_K_M · 4.7 GB 88 Runs great
Best for writing Qwen3.5 4B
Alibaba · Apache 2.0
Competent drafting in 8 GB. Q5_K_M · 4.7 GB 88 Runs great
Best vision Qwen3.5 4B
Alibaba · Apache 2.0
Reads screenshots in 8 GB. Q5_K_M · 4.7 GB 88 Runs great
Best for agents Qwen3.5 4B
Alibaba · Apache 2.0
Function calling in 8 GB. Q5_K_M · 4.7 GB 88 Runs great
Best translation Qwen3.5 4B
Alibaba · Apache 2.0
Usable translation in 8 GB. Q5_K_M · 4.7 GB 88 Runs great
Fastest good model LFM2.5 8B-A1B
Liquid AI · LFM Open License v1.0
1.5B active; designed for laptops without a GPU. Q5_K_M · 6.6 GB 105 Tight fit
Best long context Qwen3.5 2B
Alibaba · Apache 2.0
Long documents on 4 GB. Q5_K_M · 3.6 GB
at 128K context
181 Runs great

Everything that fits

Runs great

11 of 76 · fits with headroom for a longer prompt
ModelParamsQuantWeights +KV 32KTotal VRAM headroom Tok/sRuntime
Gemma 4 E2B 5.1B Q5_K_M 3.4 GB 0.23 GB 4.2 GB
2.8 GB free
81 Ollama Run
Qwen3.5 4B 4.66B Q5_K_M 3.1 GB 1.00 GB 4.7 GB
2.3 GB free
88 Ollama Run
Gemma 3 4B 4.3B Q5_K_M 2.8 GB 0.86 GB 4.3 GB
2.7 GB free
96 Ollama Run
Granite 4.1 3B 3.4B Q5_K_M 2.2 GB 2.50 GB 5.3 GB
1.7 GB free
121 Ollama Run
LFM2.5 2.6B New 2.7B Q5_K_M 1.8 GB 0.50 GB 2.9 GB
4.1 GB free
152 llama.cpp Run
Qwen3.5 2B 2.27B Q5_K_M 1.5 GB 0.38 GB 2.5 GB
4.5 GB free
181 Ollama Run
Qwen3 1.7B 1.72B Q5_K_M 1.1 GB 3.50 GB 5.2 GB
1.8 GB free
239 Ollama Run
Llama 3.2 1B Instruct 1.24B Q5_K_M 0.8 GB 1.00 GB 2.4 GB
4.6 GB free
331 Ollama Run
Gemma 3 1B 1.0B Q5_K_M 0.7 GB 0.14 GB 1.4 GB
5.6 GB free
411 Ollama Run
Qwen3.5 0.8B 0.87B Q5_K_M 0.6 GB 0.38 GB 1.5 GB
5.5 GB free
472 Ollama Run
Qwen3 0.6B 0.6B Q5_K_M 0.4 GB 3.50 GB 4.5 GB
2.5 GB free
685 Ollama Run

Runs — tight

5 models · fits at 32K, drop context or quant to go longer
ModelParamsQuantWeights +KV 32KTotal VRAM headroom Tok/sRuntime
LFM2.5 8B-A1B 8.47B MoE / 1.5B act Q5_K_M 5.6 GB 0.38 GB 6.6 GB
0.4 GB free
105 llama.cpp Run
Gemma 4 E4B 8.0B Q5_K_M 5.3 GB 0.47 GB 6.4 GB
0.6 GB free
51 llama.cpp Run
Ling 3.0 Tiny 7.9B-A1.3B New 7.9B MoE / 1.3B act Q5_K_M 5.2 GB 0.21 GB 6.0 GB
1.0 GB free
122 llama.cpp Run
Ministral 3 3B 3.85B Q5_K_M 2.5 GB 3.25 GB 6.4 GB
0.6 GB free
107 llama.cpp Run
Llama 3.2 3B Instruct 3.21B Q5_K_M 2.1 GB 3.50 GB 6.2 GB
0.8 GB free
128 llama.cpp Run

Won't fit in VRAM

60 models · some are possible with CPU offload
ModelParamsQuantWeights +KV 32KTotal Over budget Tok/sRuntime
Qwen3.6 35B-A3B 35.9B MoE / 3.3B act Q5_K_M 23.7 GB 0.63 GB 24.9 GB +17.9 GB ~8.1 llama.cpp Why
Ornith 1.5 35B-A3B New this week 35.9B MoE / 3.3B act Q5_K_M 23.7 GB 0.63 GB 24.9 GB +17.9 GB ~8.1 llama.cpp Why
LLM-jp 4 33B Thinking New this week 33.2B Q5_K_M 21.9 GB 8.00 GB 30.5 GB +23.5 GB ~1.7 llama.cpp Why
Qwen3 32B 32.8B Q5_K_M 21.7 GB 8.00 GB 30.3 GB +23.3 GB ~1.7 llama.cpp Why
DeepSeek-R1-Distill-Qwen 32B 32.8B Q5_K_M 21.7 GB 8.00 GB 30.3 GB +23.3 GB ~1.7 llama.cpp Why
Qwen2.5-Coder 32B 32.8B Q5_K_M 21.7 GB 8.00 GB 30.3 GB +23.3 GB ~1.7 llama.cpp Why
Olmo 3.1 32B Instruct 32.2B Q5_K_M 21.3 GB 2.75 GB 24.6 GB +17.6 GB ~2.0 llama.cpp Why
Nemotron 3.5 Lightning 30B-A3B New 31.6B MoE / 3.2B act Q5_K_M 20.9 GB 0.19 GB 21.6 GB +14.6 GB ~8.9 llama.cpp Why
Gemma 4 31B 31.3B Q5_K_M 20.7 GB 5.78 GB 27.0 GB +20.0 GB ~1.8 llama.cpp Why
GLM-4.7-Flash 30B-A3B 31.2B MoE / 3B act Q5_K_M 20.6 GB 1.65 GB 22.8 GB +15.8 GB ~8.8 llama.cpp Why
Qwen3 30B-A3B 30.5B MoE / 3.3B act Q5_K_M 20.1 GB 3.00 GB 23.7 GB +16.7 GB ~7.5 llama.cpp Why
Qwen3 Coder 30B-A3B 30.5B MoE / 3.3B act Q5_K_M 20.1 GB 3.00 GB 23.7 GB +16.7 GB ~7.5 llama.cpp Why
Muse Glimmer 30B New 29.8B Q5_K_M 19.7 GB 0.48 GB 20.8 GB +13.8 GB ~2.5 llama.cpp Why
Granite 4.1 30B 28.9B Q5_K_M 19.1 GB 8.00 GB 27.7 GB +20.7 GB ~1.9 llama.cpp Why
Qwen3.8 27B New this week 27.8B Q5_K_M 18.4 GB 2.00 GB 21.0 GB +14.0 GB ~2.5 llama.cpp Why
Qwen3.6 27B 27.8B Q5_K_M 18.4 GB 2.00 GB 21.0 GB +14.0 GB ~2.5 llama.cpp Why
Gemma 3 27B 27.4B Q5_K_M 18.1 GB 2.91 GB 21.6 GB +14.6 GB ~2.4 llama.cpp Why
Gemma 4 26B-A4B 26.5B MoE / 3.8B act Q5_K_M 17.5 GB 1.45 GB 19.5 GB +12.5 GB ~7.4 llama.cpp Why
Devstral Small 2 24B 24B Q5_K_M 15.8 GB 5.00 GB 21.4 GB +14.4 GB ~2.5 llama.cpp Why
Mistral Small 3.2 24B 23.6B Q5_K_M 15.6 GB 5.00 GB 21.2 GB +14.2 GB ~2.5 llama.cpp Why
gpt-oss 20B 20.9B MoE / 3.6B act MXFP4 10.8 GB 0.75 GB 12.2 GB +5.2 GB ~14 llama.cpp Why
Qwen3 14B 14.8B Q5_K_M 9.8 GB 5.00 GB 15.4 GB +8.4 GB ~4.2 llama.cpp Why
DeepSeek-R1-Distill-Qwen 14B 14.8B Q5_K_M 9.8 GB 6.00 GB 16.4 GB +9.4 GB ~3.9 llama.cpp Why
Qwen2.5-Coder 14B 14.8B Q5_K_M 9.8 GB 6.00 GB 16.4 GB +9.4 GB ~3.9 llama.cpp Why
Phi-4 14B 14.7B Q5_K_M 9.7 GB 3.13 GB 13.4 GB +6.4 GB ~5.3 llama.cpp Why
Ministral 3 14B 13.9B Q5_K_M 9.2 GB 5.00 GB 14.8 GB +7.8 GB ~4.6 llama.cpp Why
Gemma 3 12B 12.2B Q5_K_M 8.1 GB 2.31 GB 11.0 GB +4.0 GB ~8.0 llama.cpp Why
Mistral NeMo 12B 12.2B Q5_K_M 8.1 GB 5.00 GB 13.7 GB +6.7 GB ~5.3 llama.cpp Why
Gemma 4 12B 12B Q5_K_M 7.9 GB 2.31 GB 10.8 GB +3.8 GB ~8.3 llama.cpp Why
Qwen3.5 9B 9.65B Q5_K_M 6.4 GB 1.00 GB 8.0 GB +1.0 GB ~21 llama.cpp Why
Ornith 1.5 9B New this week 9.41B Q5_K_M 6.2 GB 1.00 GB 7.8 GB +0.8 GB ~24 llama.cpp Why
Ministral 3 8B 8.92B Q5_K_M 5.9 GB 4.25 GB 10.7 GB +3.7 GB ~9.0 llama.cpp Why
Granite 4.1 8B 8.79B Q5_K_M 5.8 GB 5.00 GB 11.4 GB +4.4 GB ~7.9 llama.cpp Why
Fara 7B 8.29B Q5_K_M 5.5 GB 1.75 GB 7.8 GB +0.8 GB ~25 llama.cpp Why
Qwen3 8B 8.19B Q5_K_M 5.4 GB 4.50 GB 10.5 GB +3.5 GB ~9.7 llama.cpp Why
Llama 3.1 8B Instruct 8.03B Q5_K_M 5.3 GB 4.00 GB 9.9 GB +2.9 GB ~11 llama.cpp Why
DeepSeek-R1-Distill-Qwen 7B 7.62B Q5_K_M 5.0 GB 1.75 GB 7.4 GB +0.4 GB ~36 llama.cpp Why
Qwen2.5-Coder 7B 7.62B Q5_K_M 5.0 GB 1.75 GB 7.4 GB +0.4 GB ~36 llama.cpp Why
Olmo 3 7B Instruct 7.3B Q5_K_M 4.8 GB 5.50 GB 10.9 GB +3.9 GB ~9.0 llama.cpp Why
Mistral 7B Instruct v0.3 7.25B Q5_K_M 4.8 GB 4.00 GB 9.4 GB +2.4 GB ~13 llama.cpp Why
Qwen3 4B 4.02B Q5_K_M 2.7 GB 4.50 GB 7.8 GB +0.8 GB ~36 llama.cpp Why
Phi-4-mini 3.8B 3.84B Q5_K_M 2.5 GB 4.00 GB 7.1 GB +0.1 GB ~80 llama.cpp Why
Kimi K3 2.8T-A104B New 2780B MoE / 104B act Q5_K_M 1835.0 GB 0.84 GB 1836.5 GB +1829.5 GB ~0.2 llama.cpp Why
Qwen3.8 2.4T-A95B New 2446B MoE / 95B act Q5_K_M 1614.5 GB 2.88 GB 1618.0 GB +1611.0 GB ~0.2 llama.cpp Why
DeepSeek V4 Pro 1.6T-A49B New 1650B MoE / 49B act Q5_K_M 1089.1 GB 2.14 GB 1091.9 GB +1084.9 GB ~0.4 llama.cpp Why
Kimi K2.6 1T-A32B 1027B MoE / 32B act Q5_K_M 677.9 GB 2.14 GB 680.6 GB +673.6 GB ~0.7 llama.cpp Why
GLM-5.2 744B-A40B 753B MoE / 40B act Q5_K_M 497.0 GB 2.74 GB 500.4 GB +493.4 GB ~0.5 llama.cpp Why
DeepSeek-R1 671B 671B MoE / 37B act Q5_K_M 442.9 GB 2.14 GB 445.7 GB +438.7 GB ~0.6 llama.cpp Why
Qwen3.5 397B-A17B 403B MoE / 17B act Q5_K_M 266.0 GB 0.94 GB 267.5 GB +260.5 GB ~1.3 llama.cpp Why
Ornith 1.5 397B-A17B New this week 397B MoE / 17B act Q5_K_M 262.0 GB 0.94 GB 263.6 GB +256.6 GB ~1.3 llama.cpp Why
DeepSeek V4 Flash 284B-A13B New 284B MoE / 13B act Q5_K_M 187.5 GB 1.51 GB 189.6 GB +182.6 GB ~1.7 llama.cpp Why
Qwen3 235B-A22B 235B MoE / 22B act Q5_K_M 155.1 GB 5.88 GB 161.6 GB +154.6 GB ~1.0 llama.cpp Why
Qwen3.5 122B-A10B 125B MoE / 10B act Q5_K_M 82.5 GB 0.75 GB 83.9 GB +76.9 GB ~2.2 llama.cpp Why
Nemotron 3 Super 120B-A12B 124B MoE / 12B act Q5_K_M 81.8 GB 0.25 GB 82.7 GB +75.7 GB ~1.9 llama.cpp Why
Ling 3.0 Flash 124B-A5B New 124B MoE / 5.1B act Q5_K_M 81.8 GB 0.25 GB 82.7 GB +75.7 GB ~4.4 llama.cpp Why
Mistral Small 4 119B-A6B 119B MoE / 6.5B act Q5_K_M 78.5 GB 0.70 GB 79.9 GB +72.9 GB ~3.5 llama.cpp Why
gpt-oss 120B 117B MoE / 5.1B act MXFP4 60.5 GB 1.13 GB 62.2 GB +55.2 GB ~5.7 llama.cpp Why
Llama 4 Scout 109B-A17B 109B MoE / 17B act Q5_K_M 71.9 GB 2.63 GB 75.2 GB +68.2 GB ~1.3 llama.cpp Why
Llama 3.3 70B Instruct 70.6B Q5_K_M 46.6 GB 10.00 GB 57.2 GB +50.2 GB ~0.8 llama.cpp Why
DeepSeek-R1-Distill-Llama 70B 70.6B Q5_K_M 46.6 GB 10.00 GB 57.2 GB +50.2 GB ~0.8 llama.cpp Why

Totals = quantised weights + f16 KV cache at 32K tokens + 0.6 GB runtime overhead, against 7.0 GB usable VRAM (8 GB less display and driver reserve). Tokens per second are estimated from 448 GB/s peak memory bandwidth at batch 1 — not measured. Read the method.