Your rig

GeForce RTX 4070 Ti · 12 GB

64 GB system RAM · Ada Lovelace · 504 GB/s · 10.6 GB usable VRAM
Edit hardware Export as JSON

Context length

KV cache at f16, 4K 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 4070 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 Q6_K and 4K. 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. Q6_K · 8.1 GB 41 Runs great
Best for coding Qwen3.5 9B
Alibaba · Apache 2.0
The best coding model for 8–12 GB cards. Q6_K · 8.1 GB 41 Runs great
Best reasoning Qwen3.5 9B
Alibaba · Apache 2.0
Thinking mode on a 12 GB card — ahead of the 2025 R1 distills. Q6_K · 8.1 GB 41 Runs great
Best for writing Ministral 3 8B
Mistral AI · Apache 2.0
Mistral's voice in 8B, Apache 2.0. Q6_K · 7.9 GB 45 Runs great
Best vision Qwen3.5 9B
Alibaba · Apache 2.0
Vision on an 8–12 GB card. Q6_K · 8.1 GB 41 Runs great
Best for agents Granite 4.1 8B
IBM · Apache 2.0
Enterprise-grade tool calling in a dense 8B, no thinking overhead. Q6_K · 7.9 GB 45 Runs great
Best translation Qwen3.5 9B
Alibaba · Apache 2.0
Strong CJK and European translation in 8–12 GB. Q6_K · 8.1 GB 41 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. Q6_K · 7.1 GB 102 Runs great
Best long context Qwen3.5 4B
Alibaba · Apache 2.0
262K on 8 GB. Q6_K · 8.2 GB
at 128K context
86 Runs great

Everything that fits

Runs great

29 of 76 · fits with headroom for a longer prompt
ModelParamsQuantWeights +KV 4KTotal VRAM headroom Tok/sRuntime
Qwen3.5 9B 9.65B Q6_K 7.4 GB 0.13 GB 8.1 GB
2.5 GB free
41 Ollama Run
Ornith 1.5 9B New this week 9.41B Q6_K 7.2 GB 0.13 GB 7.9 GB
2.7 GB free
42 Ollama Run
Ministral 3 8B 8.92B Q6_K 6.8 GB 0.53 GB 7.9 GB
2.7 GB free
45 Ollama Run
Granite 4.1 8B 8.79B Q6_K 6.7 GB 0.63 GB 7.9 GB
2.7 GB free
45 Ollama Run
LFM2.5 8B-A1B 8.47B MoE / 1.5B act Q6_K 6.5 GB 0.05 GB 7.1 GB
3.5 GB free
102 Ollama Run
Fara 7B 8.29B Q6_K 6.3 GB 0.22 GB 7.1 GB
3.5 GB free
48 llama.cpp Run
Qwen3 8B 8.19B Q6_K 6.3 GB 0.56 GB 7.4 GB
3.2 GB free
49 Ollama Run
Llama 3.1 8B Instruct 8.03B Q6_K 6.1 GB 0.50 GB 7.2 GB
3.4 GB free
50 Ollama Run
Gemma 4 E4B 8.0B Q6_K 6.1 GB 0.09 GB 6.8 GB
3.8 GB free
50 Ollama Run
Ling 3.0 Tiny 7.9B-A1.3B New 7.9B MoE / 1.3B act Q6_K 6.0 GB 0.03 GB 6.7 GB
3.9 GB free
118 llama.cpp Run
DeepSeek-R1-Distill-Qwen 7B 7.62B Q6_K 5.8 GB 0.22 GB 6.6 GB
4.0 GB free
52 Ollama Run
Qwen2.5-Coder 7B 7.62B Q6_K 5.8 GB 0.22 GB 6.6 GB
4.0 GB free
52 Ollama Run
Olmo 3 7B Instruct 7.3B Q6_K 5.6 GB 2.00 GB 8.2 GB
2.4 GB free
55 Ollama Run
Mistral 7B Instruct v0.3 7.25B Q6_K 5.5 GB 0.50 GB 6.6 GB
4.0 GB free
55 Ollama Run
Gemma 4 E2B 5.1B Q6_K 3.9 GB 0.04 GB 4.5 GB
6.1 GB free
78 Ollama Run
Qwen3.5 4B 4.66B Q6_K 3.6 GB 0.13 GB 4.3 GB
6.3 GB free
86 Ollama Run
Gemma 3 4B 4.3B Q6_K 3.3 GB 0.20 GB 4.1 GB
6.5 GB free
93 Ollama Run
Qwen3 4B 4.02B Q6_K 3.1 GB 0.56 GB 4.2 GB
6.4 GB free
99 Ollama Run
Ministral 3 3B 3.85B Q6_K 2.9 GB 0.41 GB 3.9 GB
6.7 GB free
104 Ollama Run
Phi-4-mini 3.8B 3.84B Q6_K 2.9 GB 0.50 GB 4.0 GB
6.6 GB free
104 Ollama Run
Granite 4.1 3B 3.4B Q6_K 2.6 GB 0.31 GB 3.5 GB
7.1 GB free
118 Ollama Run
Llama 3.2 3B Instruct 3.21B Q6_K 2.5 GB 0.44 GB 3.5 GB
7.1 GB free
124 Ollama Run
LFM2.5 2.6B New 2.7B Q6_K 2.1 GB 0.06 GB 2.7 GB
7.9 GB free
148 llama.cpp Run
Qwen3.5 2B 2.27B Q6_K 1.7 GB 0.05 GB 2.4 GB
8.2 GB free
176 Ollama Run
Qwen3 1.7B 1.72B Q6_K 1.3 GB 0.44 GB 2.4 GB
8.2 GB free
232 Ollama Run
Llama 3.2 1B Instruct 1.24B Q6_K 0.9 GB 0.13 GB 1.7 GB
8.9 GB free
322 Ollama Run
Gemma 3 1B 1.0B Q6_K 0.8 GB 0.03 GB 1.4 GB
9.2 GB free
400 Ollama Run
Qwen3.5 0.8B 0.87B Q6_K 0.7 GB 0.05 GB 1.3 GB
9.3 GB free
459 Ollama Run
Qwen3 0.6B 0.6B Q6_K 0.5 GB 0.44 GB 1.5 GB
9.1 GB free
666 Ollama Run

Runs — tight

3 models · fits at 4K, drop context or quant to go longer
ModelParamsQuantWeights +KV 4KTotal VRAM headroom Tok/sRuntime
Gemma 3 12B 12.2B Q6_K 9.3 GB 0.56 GB 10.5 GB
0.1 GB free
33 llama.cpp Run
Mistral NeMo 12B 12.2B Q6_K 9.3 GB 0.63 GB 10.5 GB
0.1 GB free
33 llama.cpp Run
Gemma 4 12B 12B Q6_K 9.2 GB 0.56 GB 10.3 GB
0.3 GB free
33 llama.cpp Run

Won't fit in VRAM

44 models · some are possible with CPU offload
ModelParamsQuantWeights +KV 4KTotal Over budget Tok/sRuntime
gpt-oss 120B 117B MoE / 5.1B act MXFP4 60.5 GB 0.15 GB 61.3 GB +50.7 GB ~6.2 llama.cpp Why
Llama 3.3 70B Instruct 70.6B Q6_K 53.9 GB 1.25 GB 55.8 GB +45.2 GB ~0.8 llama.cpp Why
DeepSeek-R1-Distill-Llama 70B 70.6B Q6_K 53.9 GB 1.25 GB 55.8 GB +45.2 GB ~0.8 llama.cpp Why
Qwen3.6 35B-A3B 35.9B MoE / 3.3B act Q6_K 27.4 GB 0.08 GB 28.1 GB +17.5 GB ~8.1 llama.cpp Why
Ornith 1.5 35B-A3B New this week 35.9B MoE / 3.3B act Q6_K 27.4 GB 0.08 GB 28.1 GB +17.5 GB ~8.1 llama.cpp Why
LLM-jp 4 33B Thinking New this week 33.2B Q6_K 25.4 GB 1.00 GB 27.0 GB +16.4 GB ~2.1 llama.cpp Why
Qwen3 32B 32.8B Q6_K 25.0 GB 1.00 GB 26.6 GB +16.0 GB ~2.1 llama.cpp Why
DeepSeek-R1-Distill-Qwen 32B 32.8B Q6_K 25.0 GB 1.00 GB 26.6 GB +16.0 GB ~2.1 llama.cpp Why
Qwen2.5-Coder 32B 32.8B Q6_K 25.0 GB 1.00 GB 26.6 GB +16.0 GB ~2.1 llama.cpp Why
Olmo 3.1 32B Instruct 32.2B Q6_K 24.6 GB 1.00 GB 26.2 GB +15.6 GB ~2.2 llama.cpp Why
Nemotron 3.5 Lightning 30B-A3B New 31.6B MoE / 3.2B act Q6_K 24.1 GB 0.02 GB 24.8 GB +14.2 GB ~9.0 llama.cpp Why
Gemma 4 31B 31.3B Q6_K 23.9 GB 1.41 GB 25.9 GB +15.3 GB ~2.2 llama.cpp Why
GLM-4.7-Flash 30B-A3B 31.2B MoE / 3B act Q6_K 23.8 GB 0.21 GB 24.6 GB +14.0 GB ~9.6 llama.cpp Why
Qwen3 30B-A3B 30.5B MoE / 3.3B act Q6_K 23.3 GB 0.38 GB 24.3 GB +13.7 GB ~8.7 llama.cpp Why
Qwen3 Coder 30B-A3B 30.5B MoE / 3.3B act Q6_K 23.3 GB 0.38 GB 24.3 GB +13.7 GB ~8.7 llama.cpp Why
Muse Glimmer 30B New 29.8B Q6_K 22.8 GB 0.13 GB 23.5 GB +12.9 GB ~2.6 llama.cpp Why
Granite 4.1 30B 28.9B Q6_K 22.1 GB 1.00 GB 23.7 GB +13.1 GB ~2.6 llama.cpp Why
Qwen3.8 27B New this week 27.8B Q6_K 21.2 GB 0.25 GB 22.1 GB +11.5 GB ~2.9 llama.cpp Why
Qwen3.6 27B 27.8B Q6_K 21.2 GB 0.25 GB 22.1 GB +11.5 GB ~2.9 llama.cpp Why
Gemma 3 27B 27.4B Q6_K 20.9 GB 0.72 GB 22.2 GB +11.6 GB ~2.8 llama.cpp Why
Gemma 4 26B-A4B 26.5B MoE / 3.8B act Q6_K 20.2 GB 0.35 GB 21.2 GB +10.6 GB ~8.3 llama.cpp Why
Devstral Small 2 24B 24B Q6_K 18.3 GB 0.63 GB 19.6 GB +9.0 GB ~3.6 llama.cpp Why
Mistral Small 3.2 24B 23.6B Q6_K 18.0 GB 0.63 GB 19.2 GB +8.6 GB ~3.7 llama.cpp Why
gpt-oss 20B 20.9B MoE / 3.6B act MXFP4 10.8 GB 0.10 GB 11.5 GB +0.9 GB ~39 llama.cpp Why
Qwen3 14B 14.8B Q6_K 11.3 GB 0.63 GB 12.5 GB +1.9 GB ~12 llama.cpp Why
DeepSeek-R1-Distill-Qwen 14B 14.8B Q6_K 11.3 GB 0.75 GB 12.7 GB +2.1 GB ~12 llama.cpp Why
Qwen2.5-Coder 14B 14.8B Q6_K 11.3 GB 0.75 GB 12.7 GB +2.1 GB ~12 llama.cpp Why
Phi-4 14B 14.7B Q6_K 11.2 GB 0.78 GB 12.6 GB +2.0 GB ~12 llama.cpp Why
Ministral 3 14B 13.9B Q6_K 10.6 GB 0.63 GB 11.8 GB +1.2 GB ~15 llama.cpp Why
Kimi K3 2.8T-A104B New 2780B MoE / 104B act Q6_K 2123.0 GB 0.11 GB 2123.7 GB +2113.1 GB ~0.2 llama.cpp Why
Qwen3.8 2.4T-A95B New 2446B MoE / 95B act Q6_K 1868.0 GB 0.36 GB 1868.9 GB +1858.3 GB ~0.2 llama.cpp Why
DeepSeek V4 Pro 1.6T-A49B New 1650B MoE / 49B act Q6_K 1260.1 GB 0.27 GB 1260.9 GB +1250.3 GB ~0.4 llama.cpp Why
Kimi K2.6 1T-A32B 1027B MoE / 32B act Q6_K 784.3 GB 0.27 GB 785.2 GB +774.6 GB ~0.6 llama.cpp Why
GLM-5.2 744B-A40B 753B MoE / 40B act Q6_K 575.1 GB 0.34 GB 576.0 GB +565.4 GB ~0.5 llama.cpp Why
DeepSeek-R1 671B 671B MoE / 37B act Q6_K 512.4 GB 0.27 GB 513.3 GB +502.7 GB ~0.5 llama.cpp Why
Qwen3.5 397B-A17B 403B MoE / 17B act Q6_K 307.8 GB 0.12 GB 308.5 GB +297.9 GB ~1.1 llama.cpp Why
Ornith 1.5 397B-A17B New this week 397B MoE / 17B act Q6_K 303.2 GB 0.12 GB 303.9 GB +293.3 GB ~1.1 llama.cpp Why
DeepSeek V4 Flash 284B-A13B New 284B MoE / 13B act Q6_K 216.9 GB 0.19 GB 217.7 GB +207.1 GB ~1.5 llama.cpp Why
Qwen3 235B-A22B 235B MoE / 22B act Q6_K 179.5 GB 0.73 GB 180.8 GB +170.2 GB ~0.9 llama.cpp Why
Qwen3.5 122B-A10B 125B MoE / 10B act Q6_K 95.5 GB 0.09 GB 96.2 GB +85.6 GB ~2.0 llama.cpp Why
Nemotron 3 Super 120B-A12B 124B MoE / 12B act Q6_K 94.7 GB 0.03 GB 95.3 GB +84.7 GB ~1.7 llama.cpp Why
Ling 3.0 Flash 124B-A5B New 124B MoE / 5.1B act Q6_K 94.7 GB 0.03 GB 95.3 GB +84.7 GB ~4.0 llama.cpp Why
Mistral Small 4 119B-A6B 119B MoE / 6.5B act Q6_K 90.9 GB 0.09 GB 91.6 GB +81.0 GB ~3.1 llama.cpp Why
Llama 4 Scout 109B-A17B 109B MoE / 17B act Q6_K 83.2 GB 0.75 GB 84.6 GB +74.0 GB ~1.2 llama.cpp Why

Totals = quantised weights + f16 KV cache at 4K 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 504 GB/s peak memory bandwidth at batch 1 — not measured. Read the method.