Your rig

GeForce RTX 4060 Ti · 8 GB

256 GB system RAM · Ada Lovelace · 288 GB/s · 7.0 GB usable VRAM
Edit hardware Export as JSON

Context length

KV cache at f16, 8K 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 4060 Ti

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 Q4_K_M. The ordering is editorial; the sizes and speeds are computed. How the shortlists work.

RecommendationModelWhyQuant · totalTok/s est.
Best vision
Your pick
Gemma 4 E4B
Google · Apache 2.0
Laptop vision, audio too. Q4_K_M · 5.2 GB 39 Runs great
Best overall Gemma 4 E4B
Google · Apache 2.0
Laptop class with images and audio in. Q4_K_M · 5.2 GB 39 Runs great
Best for coding Qwen3.5 4B
Alibaba · Apache 2.0
A coding agent in 3.4 GB — the 6–8 GB answer. Q4_K_M · 3.5 GB 67 Runs great
Best reasoning Qwen3.5 4B
Alibaba · Apache 2.0
Step-by-step reasoning in 8 GB. Q4_K_M · 3.5 GB 67 Runs great
Best for writing Gemma 4 E4B
Google · Apache 2.0
Readable prose on a laptop. Q4_K_M · 5.2 GB 39 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. Q4_K_M · 5.7 GB 37 Runs great
Best translation Gemma 4 E4B
Google · Apache 2.0
140+ languages on a laptop. Q4_K_M · 5.2 GB 39 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. Q4_K_M · 5.5 GB 80 Runs great
Best long context Qwen3.5 2B
Alibaba · Apache 2.0
Long documents on 4 GB. Q4_K_M · 3.4 GB
at 128K context
137 Runs great

Everything that fits

Runs great

22 of 76 · fits with headroom for a longer prompt
ModelParamsQuantWeights +KV 8KTotal VRAM headroom Tok/sRuntime
LFM2.5 8B-A1B 8.47B MoE / 1.5B act Q4_K_M 4.8 GB 0.09 GB 5.5 GB
1.5 GB free
80 Ollama Run
Fara 7B 8.29B Q4_K_M 4.7 GB 0.44 GB 5.7 GB
1.3 GB free
37 llama.cpp Run
Gemma 4 E4B 8.0B Q4_K_M 4.5 GB 0.14 GB 5.2 GB
1.8 GB free
39 Ollama Run
Ling 3.0 Tiny 7.9B-A1.3B New 7.9B MoE / 1.3B act Q4_K_M 4.4 GB 0.05 GB 5.1 GB
1.9 GB free
92 llama.cpp Run
DeepSeek-R1-Distill-Qwen 7B 7.62B Q4_K_M 4.3 GB 0.44 GB 5.3 GB
1.7 GB free
41 Ollama Run
Qwen2.5-Coder 7B 7.62B Q4_K_M 4.3 GB 0.44 GB 5.3 GB
1.7 GB free
41 Ollama Run
Mistral 7B Instruct v0.3 7.25B Q4_K_M 4.1 GB 1.00 GB 5.7 GB
1.3 GB free
43 Ollama Run
Gemma 4 E2B 5.1B Q4_K_M 2.9 GB 0.07 GB 3.5 GB
3.5 GB free
61 Ollama Run
Qwen3.5 4B 4.66B Q4_K_M 2.6 GB 0.25 GB 3.5 GB
3.5 GB free
67 Ollama Run
Gemma 3 4B 4.3B Q4_K_M 2.4 GB 0.30 GB 3.3 GB
3.7 GB free
72 Ollama Run
Qwen3 4B 4.02B Q4_K_M 2.3 GB 1.13 GB 4.0 GB
3.0 GB free
77 Ollama Run
Ministral 3 3B 3.85B Q4_K_M 2.2 GB 0.81 GB 3.6 GB
3.4 GB free
81 Ollama Run
Phi-4-mini 3.8B 3.84B Q4_K_M 2.2 GB 1.00 GB 3.8 GB
3.2 GB free
81 Ollama Run
Granite 4.1 3B 3.4B Q4_K_M 1.9 GB 0.63 GB 3.1 GB
3.9 GB free
91 Ollama Run
Llama 3.2 3B Instruct 3.21B Q4_K_M 1.8 GB 0.88 GB 3.3 GB
3.7 GB free
97 Ollama Run
LFM2.5 2.6B New 2.7B Q4_K_M 1.5 GB 0.13 GB 2.2 GB
4.8 GB free
115 llama.cpp Run
Qwen3.5 2B 2.27B Q4_K_M 1.3 GB 0.09 GB 2.0 GB
5.0 GB free
137 Ollama Run
Qwen3 1.7B 1.72B Q4_K_M 1.0 GB 0.88 GB 2.4 GB
4.6 GB free
180 Ollama Run
Llama 3.2 1B Instruct 1.24B Q4_K_M 0.7 GB 0.25 GB 1.5 GB
5.5 GB free
250 Ollama Run
Gemma 3 1B 1.0B Q4_K_M 0.6 GB 0.04 GB 1.2 GB
5.8 GB free
310 Ollama Run
Qwen3.5 0.8B 0.87B Q4_K_M 0.5 GB 0.09 GB 1.2 GB
5.8 GB free
356 Ollama Run
Qwen3 0.6B 0.6B Q4_K_M 0.3 GB 0.88 GB 1.8 GB
5.2 GB free
517 Ollama Run

Runs — tight

6 models · fits at 8K, drop context or quant to go longer
ModelParamsQuantWeights +KV 8KTotal VRAM headroom Tok/sRuntime
Qwen3.5 9B 9.65B Q4_K_M 5.4 GB 0.25 GB 6.3 GB
0.7 GB free
32 llama.cpp Run
Ornith 1.5 9B New this week 9.41B Q4_K_M 5.3 GB 0.25 GB 6.1 GB
0.9 GB free
33 llama.cpp Run
Ministral 3 8B 8.92B Q4_K_M 5.0 GB 1.06 GB 6.7 GB
0.3 GB free
35 llama.cpp Run
Granite 4.1 8B 8.79B Q4_K_M 4.9 GB 1.25 GB 6.8 GB
0.2 GB free
35 llama.cpp Run
Qwen3 8B 8.19B Q4_K_M 4.6 GB 1.13 GB 6.3 GB
0.7 GB free
38 llama.cpp Run
Llama 3.1 8B Instruct 8.03B Q4_K_M 4.5 GB 1.00 GB 6.1 GB
0.9 GB free
39 llama.cpp Run

Won't fit in VRAM

48 models · some are possible with CPU offload
ModelParamsQuantWeights +KV 8KTotal Over budget Tok/sRuntime
Ornith 1.5 397B-A17B New this week 397B MoE / 17B act Q4_K_M 223.2 GB 0.23 GB 224.1 GB +217.1 GB ~1.5 llama.cpp Why
DeepSeek V4 Flash 284B-A13B New 284B MoE / 13B act Q4_K_M 159.7 GB 0.38 GB 160.7 GB +153.7 GB ~2.0 llama.cpp Why
Qwen3 235B-A22B 235B MoE / 22B act Q4_K_M 132.1 GB 1.47 GB 134.2 GB +127.2 GB ~1.2 llama.cpp Why
Qwen3.5 122B-A10B 125B MoE / 10B act Q4_K_M 70.3 GB 0.19 GB 71.1 GB +64.1 GB ~2.7 llama.cpp Why
Nemotron 3 Super 120B-A12B 124B MoE / 12B act Q4_K_M 69.7 GB 0.06 GB 70.4 GB +63.4 GB ~2.2 llama.cpp Why
Ling 3.0 Flash 124B-A5B New 124B MoE / 5.1B act Q4_K_M 69.7 GB 0.06 GB 70.4 GB +63.4 GB ~5.2 llama.cpp Why
Mistral Small 4 119B-A6B 119B MoE / 6.5B act Q4_K_M 66.9 GB 0.18 GB 67.7 GB +60.7 GB ~4.1 llama.cpp Why
gpt-oss 120B 117B MoE / 5.1B act MXFP4 60.5 GB 0.29 GB 61.4 GB +54.4 GB ~5.7 llama.cpp Why
Llama 4 Scout 109B-A17B 109B MoE / 17B act Q4_K_M 61.3 GB 1.50 GB 63.4 GB +56.4 GB ~1.6 llama.cpp Why
Llama 3.3 70B Instruct 70.6B Q4_K_M 39.7 GB 2.50 GB 42.8 GB +35.8 GB ~1.0 llama.cpp Why
DeepSeek-R1-Distill-Llama 70B 70.6B Q4_K_M 39.7 GB 2.50 GB 42.8 GB +35.8 GB ~1.0 llama.cpp Why
Qwen3.6 35B-A3B 35.9B MoE / 3.3B act Q4_K_M 20.2 GB 0.16 GB 20.9 GB +13.9 GB ~10 llama.cpp Why
Ornith 1.5 35B-A3B New this week 35.9B MoE / 3.3B act Q4_K_M 20.2 GB 0.16 GB 20.9 GB +13.9 GB ~10 llama.cpp Why
LLM-jp 4 33B Thinking New this week 33.2B Q4_K_M 18.7 GB 2.00 GB 21.3 GB +14.3 GB ~2.4 llama.cpp Why
Qwen3 32B 32.8B Q4_K_M 18.4 GB 2.00 GB 21.0 GB +14.0 GB ~2.4 llama.cpp Why
DeepSeek-R1-Distill-Qwen 32B 32.8B Q4_K_M 18.4 GB 2.00 GB 21.0 GB +14.0 GB ~2.4 llama.cpp Why
Qwen2.5-Coder 32B 32.8B Q4_K_M 18.4 GB 2.00 GB 21.0 GB +14.0 GB ~2.4 llama.cpp Why
Olmo 3.1 32B Instruct 32.2B Q4_K_M 18.1 GB 1.25 GB 20.0 GB +13.0 GB ~2.6 llama.cpp Why
Nemotron 3.5 Lightning 30B-A3B New 31.6B MoE / 3.2B act Q4_K_M 17.8 GB 0.05 GB 18.4 GB +11.4 GB ~11 llama.cpp Why
Gemma 4 31B 31.3B Q4_K_M 17.6 GB 2.03 GB 20.2 GB +13.2 GB ~2.6 llama.cpp Why
GLM-4.7-Flash 30B-A3B 31.2B MoE / 3B act Q4_K_M 17.5 GB 0.41 GB 18.6 GB +11.6 GB ~11 llama.cpp Why
Qwen3 30B-A3B 30.5B MoE / 3.3B act Q4_K_M 17.1 GB 0.75 GB 18.5 GB +11.5 GB ~10 llama.cpp Why
Qwen3 Coder 30B-A3B 30.5B MoE / 3.3B act Q4_K_M 17.1 GB 0.75 GB 18.5 GB +11.5 GB ~10 llama.cpp Why
Muse Glimmer 30B New 29.8B Q4_K_M 16.8 GB 0.18 GB 17.5 GB +10.5 GB ~3.1 llama.cpp Why
Granite 4.1 30B 28.9B Q4_K_M 16.3 GB 2.00 GB 18.9 GB +11.9 GB ~2.8 llama.cpp Why
Qwen3.8 27B New this week 27.8B Q4_K_M 15.6 GB 0.50 GB 16.7 GB +9.7 GB ~3.3 llama.cpp Why
Qwen3.6 27B 27.8B Q4_K_M 15.6 GB 0.50 GB 16.7 GB +9.7 GB ~3.3 llama.cpp Why
Gemma 3 27B 27.4B Q4_K_M 15.4 GB 1.03 GB 17.0 GB +10.0 GB ~3.3 llama.cpp Why
Gemma 4 26B-A4B 26.5B MoE / 3.8B act Q4_K_M 14.9 GB 0.51 GB 16.0 GB +9.0 GB ~9.5 llama.cpp Why
Devstral Small 2 24B 24B Q4_K_M 13.5 GB 1.25 GB 15.3 GB +8.3 GB ~3.9 llama.cpp Why
Mistral Small 3.2 24B 23.6B Q4_K_M 13.3 GB 1.25 GB 15.1 GB +8.1 GB ~4.0 llama.cpp Why
gpt-oss 20B 20.9B MoE / 3.6B act MXFP4 10.8 GB 0.19 GB 11.6 GB +4.6 GB ~14 llama.cpp Why
Qwen3 14B 14.8B Q4_K_M 8.3 GB 1.25 GB 10.2 GB +3.2 GB ~8.6 llama.cpp Why
DeepSeek-R1-Distill-Qwen 14B 14.8B Q4_K_M 8.3 GB 1.50 GB 10.4 GB +3.4 GB ~8.2 llama.cpp Why
Qwen2.5-Coder 14B 14.8B Q4_K_M 8.3 GB 1.50 GB 10.4 GB +3.4 GB ~8.2 llama.cpp Why
Phi-4 14B 14.7B Q4_K_M 8.3 GB 1.56 GB 10.4 GB +3.4 GB ~8.2 llama.cpp Why
Ministral 3 14B 13.9B Q4_K_M 7.8 GB 1.25 GB 9.7 GB +2.7 GB ~9.7 llama.cpp Why
Gemma 3 12B 12.2B Q4_K_M 6.9 GB 0.81 GB 8.3 GB +1.3 GB ~15 llama.cpp Why
Mistral NeMo 12B 12.2B Q4_K_M 6.9 GB 1.25 GB 8.7 GB +1.7 GB ~13 llama.cpp Why
Gemma 4 12B 12B Q4_K_M 6.7 GB 0.81 GB 8.2 GB +1.2 GB ~16 llama.cpp Why
Olmo 3 7B Instruct 7.3B Q4_K_M 4.1 GB 2.50 GB 7.2 GB +0.2 GB ~36 llama.cpp Why
Kimi K3 2.8T-A104B New 2780B MoE / 104B act Q4_K_M 1563.2 GB 0.21 GB 1564.0 GB +1557.0 GB ~0.2 llama.cpp Why
Qwen3.8 2.4T-A95B New 2446B MoE / 95B act Q4_K_M 1375.4 GB 0.72 GB 1376.7 GB +1369.7 GB ~0.3 llama.cpp Why
DeepSeek V4 Pro 1.6T-A49B New 1650B MoE / 49B act Q4_K_M 927.8 GB 0.54 GB 928.9 GB +921.9 GB ~0.5 llama.cpp Why
Kimi K2.6 1T-A32B 1027B MoE / 32B act Q4_K_M 577.5 GB 0.54 GB 578.6 GB +571.6 GB ~0.8 llama.cpp Why
GLM-5.2 744B-A40B 753B MoE / 40B act Q4_K_M 423.4 GB 0.69 GB 424.7 GB +417.7 GB ~0.6 llama.cpp Why
DeepSeek-R1 671B 671B MoE / 37B act Q4_K_M 377.3 GB 0.54 GB 378.4 GB +371.4 GB ~0.7 llama.cpp Why
Qwen3.5 397B-A17B 403B MoE / 17B act Q4_K_M 226.6 GB 0.23 GB 227.4 GB +220.4 GB ~1.5 llama.cpp Why

Totals = quantised weights + f16 KV cache at 8K 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 288 GB/s peak memory bandwidth at batch 1 — not measured. Read the method.