Your rig

GeForce RTX 3080 Ti · 12 GB

64 GB system RAM · Ampere · 912 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 3080 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 Q2_K and 4K. The ordering is editorial; the sizes and speeds are computed. How the shortlists work.

RecommendationModelWhyQuant · totalTok/s est.
Best overall Gemma 4 12B
Google · Apache 2.0
The 12 GB generalist: text, image and audio in, 140+ languages. Q2_K · 5.8 GB 118 Runs great
Best for coding Devstral Small 2 24B
Mistral AI · Apache 2.0
Tuned for software-engineering agents like OpenHands and Cline. Q2_K · 10.6 GB 59 Tight fit
Best reasoning Qwen3.5 9B
Alibaba · Apache 2.0
Thinking mode on a 12 GB card — ahead of the 2025 R1 distills. Q2_K · 4.5 GB 147 Runs great
Best for writing Gemma 4 12B
Google · Apache 2.0
The 12 GB writing pick; 140+ languages. Q2_K · 5.8 GB 118 Runs great
Best vision Gemma 4 12B
Google · Apache 2.0
Image and audio understanding on 12 GB. Q2_K · 5.8 GB 118 Runs great
Best for agents Granite 4.1 8B
IBM · Apache 2.0
Enterprise-grade tool calling in a dense 8B, no thinking overhead. Q2_K · 4.7 GB 161 Runs great
Best translation Gemma 4 12B
Google · Apache 2.0
Broad language coverage on a 12 GB card. Q2_K · 5.8 GB 118 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. Q2_K · 4.0 GB 363 Runs great
Best long context Qwen3.5 9B
Alibaba · Apache 2.0
262K native in 8–12 GB. Q2_K · 8.4 GB
at 128K context
147 Runs great

Everything that fits

Runs great

37 of 76 · fits with headroom for a longer prompt
ModelParamsQuantWeights +KV 4KTotal VRAM headroom Tok/sRuntime
Qwen3 14B 14.8B Q2_K 5.8 GB 0.63 GB 7.0 GB
3.6 GB free
96 Ollama Run
DeepSeek-R1-Distill-Qwen 14B 14.8B Q2_K 5.8 GB 0.75 GB 7.1 GB
3.5 GB free
96 Ollama Run
Qwen2.5-Coder 14B 14.8B Q2_K 5.8 GB 0.75 GB 7.1 GB
3.5 GB free
96 Ollama Run
Phi-4 14B 14.7B Q2_K 5.7 GB 0.78 GB 7.1 GB
3.5 GB free
96 Ollama Run
Ministral 3 14B 13.9B Q2_K 5.4 GB 0.63 GB 6.6 GB
4.0 GB free
102 Ollama Run
Gemma 3 12B 12.2B Q2_K 4.8 GB 0.56 GB 5.9 GB
4.7 GB free
116 Ollama Run
Mistral NeMo 12B 12.2B Q2_K 4.8 GB 0.63 GB 6.0 GB
4.6 GB free
116 Ollama Run
Gemma 4 12B 12B Q2_K 4.7 GB 0.56 GB 5.8 GB
4.8 GB free
118 Ollama Run
Qwen3.5 9B 9.65B Q2_K 3.8 GB 0.13 GB 4.5 GB
6.1 GB free
147 Ollama Run
Ornith 1.5 9B New this week 9.41B Q2_K 3.7 GB 0.13 GB 4.4 GB
6.2 GB free
150 Ollama Run
Ministral 3 8B 8.92B Q2_K 3.5 GB 0.53 GB 4.6 GB
6.0 GB free
159 Ollama Run
Granite 4.1 8B 8.79B Q2_K 3.4 GB 0.63 GB 4.7 GB
5.9 GB free
161 Ollama Run
LFM2.5 8B-A1B 8.47B MoE / 1.5B act Q2_K 3.3 GB 0.05 GB 4.0 GB
6.6 GB free
363 Ollama Run
Fara 7B 8.29B Q2_K 3.2 GB 0.22 GB 4.1 GB
6.5 GB free
171 llama.cpp Run
Qwen3 8B 8.19B Q2_K 3.2 GB 0.56 GB 4.4 GB
6.2 GB free
173 Ollama Run
Llama 3.1 8B Instruct 8.03B Q2_K 3.1 GB 0.50 GB 4.2 GB
6.4 GB free
176 Ollama Run
Gemma 4 E4B 8.0B Q2_K 3.1 GB 0.09 GB 3.8 GB
6.8 GB free
177 Ollama Run
Ling 3.0 Tiny 7.9B-A1.3B New 7.9B MoE / 1.3B act Q2_K 3.1 GB 0.03 GB 3.7 GB
6.9 GB free
419 llama.cpp Run
DeepSeek-R1-Distill-Qwen 7B 7.62B Q2_K 3.0 GB 0.22 GB 3.8 GB
6.8 GB free
186 Ollama Run
Qwen2.5-Coder 7B 7.62B Q2_K 3.0 GB 0.22 GB 3.8 GB
6.8 GB free
186 Ollama Run
Olmo 3 7B Instruct 7.3B Q2_K 2.8 GB 2.00 GB 5.4 GB
5.2 GB free
194 Ollama Run
Mistral 7B Instruct v0.3 7.25B Q2_K 2.8 GB 0.50 GB 3.9 GB
6.7 GB free
195 Ollama Run
Gemma 4 E2B 5.1B Q2_K 2.0 GB 0.04 GB 2.6 GB
8.0 GB free
278 Ollama Run
Qwen3.5 4B 4.66B Q2_K 1.8 GB 0.13 GB 2.5 GB
8.1 GB free
304 Ollama Run
Gemma 3 4B 4.3B Q2_K 1.7 GB 0.20 GB 2.5 GB
8.1 GB free
329 Ollama Run
Qwen3 4B 4.02B Q2_K 1.6 GB 0.56 GB 2.7 GB
7.9 GB free
352 Ollama Run
Ministral 3 3B 3.85B Q2_K 1.5 GB 0.41 GB 2.5 GB
8.1 GB free
368 Ollama Run
Phi-4-mini 3.8B 3.84B Q2_K 1.5 GB 0.50 GB 2.6 GB
8.0 GB free
369 Ollama Run
Granite 4.1 3B 3.4B Q2_K 1.3 GB 0.31 GB 2.2 GB
8.4 GB free
416 Ollama Run
Llama 3.2 3B Instruct 3.21B Q2_K 1.3 GB 0.44 GB 2.3 GB
8.3 GB free
441 Ollama Run
LFM2.5 2.6B New 2.7B Q2_K 1.1 GB 0.06 GB 1.7 GB
8.9 GB free
524 llama.cpp Run
Qwen3.5 2B 2.27B Q2_K 0.9 GB 0.05 GB 1.5 GB
9.1 GB free
624 Ollama Run
Qwen3 1.7B 1.72B Q2_K 0.7 GB 0.44 GB 1.7 GB
8.9 GB free
823 Ollama Run
Llama 3.2 1B Instruct 1.24B Q2_K 0.5 GB 0.13 GB 1.2 GB
9.4 GB free
1142 Ollama Run
Gemma 3 1B 1.0B Q2_K 0.4 GB 0.03 GB 1.0 GB
9.6 GB free
1416 Ollama Run
Qwen3.5 0.8B 0.87B Q2_K 0.3 GB 0.05 GB 1.0 GB
9.6 GB free
1627 Ollama Run
Qwen3 0.6B 0.6B Q2_K 0.2 GB 0.44 GB 1.3 GB
9.3 GB free
2359 Ollama Run

Runs — tight

2 models · fits at 4K, drop context or quant to go longer
ModelParamsQuantWeights +KV 4KTotal VRAM headroom Tok/sRuntime
Devstral Small 2 24B 24B Q2_K 9.4 GB 0.63 GB 10.6 GB
0.0 GB free
59 llama.cpp Run
Mistral Small 3.2 24B 23.6B Q2_K 9.2 GB 0.63 GB 10.4 GB
0.2 GB free
60 llama.cpp Run

Won't fit in VRAM

37 models · some are possible with CPU offload
ModelParamsQuantWeights +KV 4KTotal Over budget Tok/sRuntime
Qwen3.5 122B-A10B 125B MoE / 10B act Q2_K 48.7 GB 0.09 GB 49.4 GB +38.8 GB ~4.4 llama.cpp Why
Nemotron 3 Super 120B-A12B 124B MoE / 12B act Q2_K 48.4 GB 0.03 GB 49.0 GB +38.4 GB ~3.7 llama.cpp Why
Ling 3.0 Flash 124B-A5B New 124B MoE / 5.1B act Q2_K 48.4 GB 0.03 GB 49.0 GB +38.4 GB ~8.7 llama.cpp Why
Mistral Small 4 119B-A6B 119B MoE / 6.5B act Q2_K 46.4 GB 0.09 GB 47.1 GB +36.5 GB ~6.9 llama.cpp Why
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 4 Scout 109B-A17B 109B MoE / 17B act Q2_K 42.5 GB 0.75 GB 43.9 GB +33.3 GB ~2.6 llama.cpp Why
Llama 3.3 70B Instruct 70.6B Q2_K 27.5 GB 1.25 GB 29.4 GB +18.8 GB ~1.9 llama.cpp Why
DeepSeek-R1-Distill-Llama 70B 70.6B Q2_K 27.5 GB 1.25 GB 29.4 GB +18.8 GB ~1.9 llama.cpp Why
Qwen3.6 35B-A3B 35.9B MoE / 3.3B act Q2_K 14.0 GB 0.08 GB 14.7 GB +4.1 GB ~32 llama.cpp Why
Ornith 1.5 35B-A3B New this week 35.9B MoE / 3.3B act Q2_K 14.0 GB 0.08 GB 14.7 GB +4.1 GB ~32 llama.cpp Why
LLM-jp 4 33B Thinking New this week 33.2B Q2_K 12.9 GB 1.00 GB 14.5 GB +3.9 GB ~8.0 llama.cpp Why
Qwen3 32B 32.8B Q2_K 12.8 GB 1.00 GB 14.4 GB +3.8 GB ~8.3 llama.cpp Why
DeepSeek-R1-Distill-Qwen 32B 32.8B Q2_K 12.8 GB 1.00 GB 14.4 GB +3.8 GB ~8.3 llama.cpp Why
Qwen2.5-Coder 32B 32.8B Q2_K 12.8 GB 1.00 GB 14.4 GB +3.8 GB ~8.3 llama.cpp Why
Olmo 3.1 32B Instruct 32.2B Q2_K 12.6 GB 1.00 GB 14.2 GB +3.6 GB ~8.8 llama.cpp Why
Nemotron 3.5 Lightning 30B-A3B New 31.6B MoE / 3.2B act Q2_K 12.3 GB 0.02 GB 12.9 GB +2.3 GB ~46 llama.cpp Why
Gemma 4 31B 31.3B Q2_K 12.2 GB 1.41 GB 14.2 GB +3.6 GB ~8.7 llama.cpp Why
GLM-4.7-Flash 30B-A3B 31.2B MoE / 3B act Q2_K 12.2 GB 0.21 GB 13.0 GB +2.4 GB ~48 llama.cpp Why
Qwen3 30B-A3B 30.5B MoE / 3.3B act Q2_K 11.9 GB 0.38 GB 12.9 GB +2.3 GB ~44 llama.cpp Why
Qwen3 Coder 30B-A3B 30.5B MoE / 3.3B act Q2_K 11.9 GB 0.38 GB 12.9 GB +2.3 GB ~44 llama.cpp Why
Muse Glimmer 30B New 29.8B Q2_K 11.6 GB 0.13 GB 12.3 GB +1.7 GB ~15 llama.cpp Why
Granite 4.1 30B 28.9B Q2_K 11.3 GB 1.00 GB 12.9 GB +2.3 GB ~13 llama.cpp Why
Qwen3.8 27B New this week 27.8B Q2_K 10.8 GB 0.25 GB 11.7 GB +1.1 GB ~21 llama.cpp Why
Qwen3.6 27B 27.8B Q2_K 10.8 GB 0.25 GB 11.7 GB +1.1 GB ~21 llama.cpp Why
Gemma 3 27B 27.4B Q2_K 10.7 GB 0.72 GB 12.0 GB +1.4 GB ~18 llama.cpp Why
Gemma 4 26B-A4B 26.5B MoE / 3.8B act Q2_K 10.3 GB 0.35 GB 11.3 GB +0.7 GB ~74 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 ~51 llama.cpp Why
Kimi K3 2.8T-A104B New 2780B MoE / 104B act Q2_K 1084.2 GB 0.11 GB 1084.9 GB +1074.3 GB ~0.3 llama.cpp Why
Qwen3.8 2.4T-A95B New 2446B MoE / 95B act Q2_K 953.9 GB 0.36 GB 954.9 GB +944.3 GB ~0.4 llama.cpp Why
DeepSeek V4 Pro 1.6T-A49B New 1650B MoE / 49B act Q2_K 643.5 GB 0.27 GB 644.4 GB +633.8 GB ~0.7 llama.cpp Why
Kimi K2.6 1T-A32B 1027B MoE / 32B act Q2_K 400.5 GB 0.27 GB 401.4 GB +390.8 GB ~1.1 llama.cpp Why
GLM-5.2 744B-A40B 753B MoE / 40B act Q2_K 293.7 GB 0.34 GB 294.6 GB +284.0 GB ~0.9 llama.cpp Why
DeepSeek-R1 671B 671B MoE / 37B act Q2_K 261.7 GB 0.27 GB 262.6 GB +252.0 GB ~1.0 llama.cpp Why
Qwen3.5 397B-A17B 403B MoE / 17B act Q2_K 157.2 GB 0.12 GB 157.9 GB +147.3 GB ~2.2 llama.cpp Why
Ornith 1.5 397B-A17B New this week 397B MoE / 17B act Q2_K 154.8 GB 0.12 GB 155.5 GB +144.9 GB ~2.2 llama.cpp Why
DeepSeek V4 Flash 284B-A13B New 284B MoE / 13B act Q2_K 110.8 GB 0.19 GB 111.5 GB +100.9 GB ~3.0 llama.cpp Why
Qwen3 235B-A22B 235B MoE / 22B act Q2_K 91.6 GB 0.73 GB 93.0 GB +82.4 GB ~1.8 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 912 GB/s peak memory bandwidth at batch 1 — not measured. Read the method.