Your rig

GeForce RTX 3060 12 GB · 12 GB

32 GB system RAM · Ampere · 360 GB/s · 10.6 GB usable VRAM
Edit hardware Export as JSON

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 3060 12 GB

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 9B
Alibaba · Apache 2.0
The 8–12 GB default of 2026 — beats every older 8B, with vision. Q5_K_M · 8.0 GB 34 Runs great
Best for coding Qwen3.5 9B
Alibaba · Apache 2.0
The best coding model for 8–12 GB cards. Q5_K_M · 8.0 GB 34 Runs great
Best reasoning Qwen3.5 9B
Alibaba · Apache 2.0
Thinking mode on a 12 GB card — ahead of the 2025 R1 distills. Q5_K_M · 8.0 GB 34 Runs great
Best for writing Gemma 4 E4B
Google · Apache 2.0
Readable prose on a laptop. Q5_K_M · 6.4 GB 41 Runs great
Best vision Qwen3.5 9B
Alibaba · Apache 2.0
Vision on an 8–12 GB card. Q5_K_M · 8.0 GB 34 Runs great
Best for agents Fara 7B
Microsoft · MIT
Web computer-use only — clicks and fills forms from screenshots, and stops to ask before anything irreversible. Q5_K_M · 7.8 GB 40 Runs great
Best translation Qwen3.5 9B
Alibaba · Apache 2.0
Strong CJK and European translation in 8–12 GB. Q5_K_M · 8.0 GB 34 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 85 Runs great
Best long context Qwen3.5 4B
Alibaba · Apache 2.0
262K on 8 GB. Q5_K_M · 7.7 GB
at 128K context
71 Runs great

Everything that fits

Runs great

23 of 76 · fits with headroom for a longer prompt
ModelParamsQuantWeights +KV 32KTotal VRAM headroom Tok/sRuntime
Qwen3.5 9B 9.65B Q5_K_M 6.4 GB 1.00 GB 8.0 GB
2.6 GB free
34 Ollama Run
Ornith 1.5 9B New this week 9.41B Q5_K_M 6.2 GB 1.00 GB 7.8 GB
2.8 GB free
35 Ollama Run
LFM2.5 8B-A1B 8.47B MoE / 1.5B act Q5_K_M 5.6 GB 0.38 GB 6.6 GB
4.0 GB free
85 Ollama Run
Fara 7B 8.29B Q5_K_M 5.5 GB 1.75 GB 7.8 GB
2.8 GB free
40 llama.cpp Run
Gemma 4 E4B 8.0B Q5_K_M 5.3 GB 0.47 GB 6.4 GB
4.2 GB free
41 Ollama 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
4.6 GB free
98 llama.cpp Run
DeepSeek-R1-Distill-Qwen 7B 7.62B Q5_K_M 5.0 GB 1.75 GB 7.4 GB
3.2 GB free
43 Ollama Run
Qwen2.5-Coder 7B 7.62B Q5_K_M 5.0 GB 1.75 GB 7.4 GB
3.2 GB free
43 Ollama Run
Gemma 4 E2B 5.1B Q5_K_M 3.4 GB 0.23 GB 4.2 GB
6.4 GB free
65 Ollama Run
Qwen3.5 4B 4.66B Q5_K_M 3.1 GB 1.00 GB 4.7 GB
5.9 GB free
71 Ollama Run
Gemma 3 4B 4.3B Q5_K_M 2.8 GB 0.86 GB 4.3 GB
6.3 GB free
77 Ollama Run
Qwen3 4B 4.02B Q5_K_M 2.7 GB 4.50 GB 7.8 GB
2.8 GB free
82 Ollama Run
Ministral 3 3B 3.85B Q5_K_M 2.5 GB 3.25 GB 6.4 GB
4.2 GB free
86 Ollama Run
Phi-4-mini 3.8B 3.84B Q5_K_M 2.5 GB 4.00 GB 7.1 GB
3.5 GB free
86 Ollama Run
Granite 4.1 3B 3.4B Q5_K_M 2.2 GB 2.50 GB 5.3 GB
5.3 GB free
97 Ollama Run
Llama 3.2 3B Instruct 3.21B Q5_K_M 2.1 GB 3.50 GB 6.2 GB
4.4 GB free
103 Ollama Run
LFM2.5 2.6B New 2.7B Q5_K_M 1.8 GB 0.50 GB 2.9 GB
7.7 GB free
122 llama.cpp Run
Qwen3.5 2B 2.27B Q5_K_M 1.5 GB 0.38 GB 2.5 GB
8.1 GB free
145 Ollama Run
Qwen3 1.7B 1.72B Q5_K_M 1.1 GB 3.50 GB 5.2 GB
5.4 GB free
192 Ollama Run
Llama 3.2 1B Instruct 1.24B Q5_K_M 0.8 GB 1.00 GB 2.4 GB
8.2 GB free
266 Ollama Run
Gemma 3 1B 1.0B Q5_K_M 0.7 GB 0.14 GB 1.4 GB
9.2 GB free
330 Ollama Run
Qwen3.5 0.8B 0.87B Q5_K_M 0.6 GB 0.38 GB 1.5 GB
9.1 GB free
379 Ollama Run
Qwen3 0.6B 0.6B Q5_K_M 0.4 GB 3.50 GB 4.5 GB
6.1 GB free
550 Ollama Run

Runs — tight

3 models · fits at 32K, drop context or quant to go longer
ModelParamsQuantWeights +KV 32KTotal VRAM headroom Tok/sRuntime
Qwen3 8B 8.19B Q5_K_M 5.4 GB 4.50 GB 10.5 GB
0.1 GB free
40 llama.cpp Run
Llama 3.1 8B Instruct 8.03B Q5_K_M 5.3 GB 4.00 GB 9.9 GB
0.7 GB free
41 llama.cpp Run
Mistral 7B Instruct v0.3 7.25B Q5_K_M 4.8 GB 4.00 GB 9.4 GB
1.2 GB free
46 llama.cpp Run

Won't fit in VRAM

50 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 +14.3 GB ~9.6 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 +14.3 GB ~9.6 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 +19.9 GB ~1.8 llama.cpp Why
Qwen3 32B 32.8B Q5_K_M 21.7 GB 8.00 GB 30.3 GB +19.7 GB ~1.8 llama.cpp Why
DeepSeek-R1-Distill-Qwen 32B 32.8B Q5_K_M 21.7 GB 8.00 GB 30.3 GB +19.7 GB ~1.8 llama.cpp Why
Qwen2.5-Coder 32B 32.8B Q5_K_M 21.7 GB 8.00 GB 30.3 GB +19.7 GB ~1.8 llama.cpp Why
Olmo 3.1 32B Instruct 32.2B Q5_K_M 21.3 GB 2.75 GB 24.6 GB +14.0 GB ~2.4 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 +11.0 GB ~11 llama.cpp Why
Gemma 4 31B 31.3B Q5_K_M 20.7 GB 5.78 GB 27.0 GB +16.4 GB ~2.1 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 +12.2 GB ~11 llama.cpp Why
Qwen3 30B-A3B 30.5B MoE / 3.3B act Q5_K_M 20.1 GB 3.00 GB 23.7 GB +13.1 GB ~9.0 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 +13.1 GB ~9.0 llama.cpp Why
Muse Glimmer 30B New 29.8B Q5_K_M 19.7 GB 0.48 GB 20.8 GB +10.2 GB ~3.1 llama.cpp Why
Granite 4.1 30B 28.9B Q5_K_M 19.1 GB 8.00 GB 27.7 GB +17.1 GB ~2.1 llama.cpp Why
Qwen3.8 27B New this week 27.8B Q5_K_M 18.4 GB 2.00 GB 21.0 GB +10.4 GB ~3.1 llama.cpp Why
Qwen3.6 27B 27.8B Q5_K_M 18.4 GB 2.00 GB 21.0 GB +10.4 GB ~3.1 llama.cpp Why
Gemma 3 27B 27.4B Q5_K_M 18.1 GB 2.91 GB 21.6 GB +11.0 GB ~3.0 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 +8.9 GB ~9.4 llama.cpp Why
Devstral Small 2 24B 24B Q5_K_M 15.8 GB 5.00 GB 21.4 GB +10.8 GB ~3.1 llama.cpp Why
Mistral Small 3.2 24B 23.6B Q5_K_M 15.6 GB 5.00 GB 21.2 GB +10.6 GB ~3.2 llama.cpp Why
gpt-oss 20B 20.9B MoE / 3.6B act MXFP4 10.8 GB 0.75 GB 12.2 GB +1.6 GB ~26 llama.cpp Why
Qwen3 14B 14.8B Q5_K_M 9.8 GB 5.00 GB 15.4 GB +4.8 GB ~6.5 llama.cpp Why
DeepSeek-R1-Distill-Qwen 14B 14.8B Q5_K_M 9.8 GB 6.00 GB 16.4 GB +5.8 GB ~5.6 llama.cpp Why
Qwen2.5-Coder 14B 14.8B Q5_K_M 9.8 GB 6.00 GB 16.4 GB +5.8 GB ~5.6 llama.cpp Why
Phi-4 14B 14.7B Q5_K_M 9.7 GB 3.13 GB 13.4 GB +2.8 GB ~9.1 llama.cpp Why
Ministral 3 14B 13.9B Q5_K_M 9.2 GB 5.00 GB 14.8 GB +4.2 GB ~7.3 llama.cpp Why
Gemma 3 12B 12.2B Q5_K_M 8.1 GB 2.31 GB 11.0 GB +0.4 GB ~22 llama.cpp Why
Mistral NeMo 12B 12.2B Q5_K_M 8.1 GB 5.00 GB 13.7 GB +3.1 GB ~9.3 llama.cpp Why
Gemma 4 12B 12B Q5_K_M 7.9 GB 2.31 GB 10.8 GB +0.2 GB ~24 llama.cpp Why
Ministral 3 8B 8.92B Q5_K_M 5.9 GB 4.25 GB 10.7 GB +0.1 GB ~33 llama.cpp Why
Granite 4.1 8B 8.79B Q5_K_M 5.8 GB 5.00 GB 11.4 GB +0.8 GB ~22 llama.cpp Why
Olmo 3 7B Instruct 7.3B Q5_K_M 4.8 GB 5.50 GB 10.9 GB +0.3 GB ~34 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 +1825.9 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 +1607.4 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 +1081.3 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 +670.0 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 +489.8 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 +435.1 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 +256.9 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 +253.0 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 +179.0 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 +151.0 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 +73.3 GB ~2.3 llama.cpp Why
Nemotron 3 Super 120B-A12B 124B MoE / 12B act Q5_K_M 81.8 GB 0.25 GB 82.7 GB +72.1 GB ~2.0 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 +72.1 GB ~4.6 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 +69.3 GB ~3.6 llama.cpp Why
gpt-oss 120B 117B MoE / 5.1B act MXFP4 60.5 GB 1.13 GB 62.2 GB +51.6 GB ~6.0 llama.cpp Why
Llama 4 Scout 109B-A17B 109B MoE / 17B act Q5_K_M 71.9 GB 2.63 GB 75.2 GB +64.6 GB ~1.4 llama.cpp Why
Llama 3.3 70B Instruct 70.6B Q5_K_M 46.6 GB 10.00 GB 57.2 GB +46.6 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 +46.6 GB ~0.8 llama.cpp Why

Totals = quantised weights + f16 KV cache at 32K tokens + 0.6 GB runtime overhead, against 10.6 GB usable VRAM (12 GB less display and driver reserve). Tokens per second are estimated from 360 GB/s peak memory bandwidth at batch 1 — not measured. Read the method.