Your rig

GeForce RTX 3090 Ti · 24 GB

64 GB system RAM · Ampere · 1008 GB/s · 22.4 GB usable VRAM
Edit hardware Export as JSON

Context length

KV cache at f16, 128K 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 3090 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 Q3_K_M and 128K. The ordering is editorial; the sizes and speeds are computed. How the shortlists work.

RecommendationModelWhyQuant · totalTok/s est.
Best overall Qwen3.8 27B New this week
Alibaba · Apache 2.0
Best capability per gigabyte: a current-generation dense 27B with vision and 262K context. Q3_K_M · 21.3 GB 48 Tight fit
Best for coding Qwen3.8 27B New this week
Alibaba · Apache 2.0
Terminal-Bench 73, DeepSWE 42 — a generation ahead of anything else that fits 24 GB. Q3_K_M · 21.3 GB 48 Tight fit
Best reasoning Qwen3.8 27B New this week
Alibaba · Apache 2.0
Thinking mode plus the best agentic reasoning at 24 GB. Q3_K_M · 21.3 GB 48 Tight fit
Best for writing Gemma 4 26B-A4B
Google · Apache 2.0
Gemma 4 prose at MoE speed, with room for a long draft in context. Q3_K_M · 17.9 GB 136 Runs great
Best vision Qwen3.8 27B New this week
Alibaba · Apache 2.0
Image and video in, OSWorld 84 — the strongest local vision-language model at 24 GB. Q3_K_M · 21.3 GB 48 Tight fit
Best for agents Muse Glimmer 30B New
Meta · Apache 2.0
Distilled specifically for always-on local agent workflows. Q3_K_M · 15.9 GB 45 Runs great
Best translation Qwen3.8 27B New this week
Alibaba · Apache 2.0
119 languages, and Qwen translations read as idiomatic rather than literal. Q3_K_M · 21.3 GB 48 Tight fit
Fastest good model Gemma 4 26B-A4B
Google · Apache 2.0
3.8B active and a small file — the quickest Gemma 4 with vision. Q3_K_M · 17.9 GB 136 Runs great
Best long context Qwen3.8 27B New this week
Alibaba · Apache 2.0
262K native, and only 16 of 64 blocks keep a KV cache — long context is cheap here. Q3_K_M · 21.3 GB
at 128K context
48 Tight fit

Everything that fits

Runs great

32 of 76 · fits with headroom for a longer prompt
ModelParamsQuantWeights +KV 128KTotal VRAM headroom Tok/sRuntime
Nemotron 3.5 Lightning 30B-A3B New 31.6B MoE / 3.2B act Q3_K_M 14.4 GB 0.75 GB 15.7 GB
6.7 GB free
161 Ollama Run
Muse Glimmer 30B New 29.8B Q3_K_M 13.6 GB 1.70 GB 15.9 GB
6.5 GB free
45 Ollama Run
Gemma 4 26B-A4B 26.5B MoE / 3.8B act Q3_K_M 12.1 GB 5.20 GB 17.9 GB
4.5 GB free
136 Ollama Run
gpt-oss 20B 20.9B MoE / 3.6B act MXFP4 10.8 GB 3.00 GB 14.4 GB
8.0 GB free
126 Ollama Run
Phi-4 14B 14.7B Q3_K_M 6.7 GB 3.13 GB 10.4 GB
12.0 GB free
91 Ollama Run
Gemma 3 12B 12.2B Q3_K_M 5.6 GB 8.31 GB 14.5 GB
7.9 GB free
110 Ollama Run
Gemma 4 12B 12B Q3_K_M 5.5 GB 8.31 GB 14.4 GB
8.0 GB free
112 Ollama Run
Qwen3.5 9B 9.65B Q3_K_M 4.4 GB 4.00 GB 9.0 GB
13.4 GB free
139 Ollama Run
Ornith 1.5 9B New this week 9.41B Q3_K_M 4.3 GB 4.00 GB 8.9 GB
13.5 GB free
142 Ollama Run
LFM2.5 8B-A1B 8.47B MoE / 1.5B act Q3_K_M 3.9 GB 1.46 GB 5.9 GB
16.5 GB free
344 Ollama Run
Fara 7B 8.29B Q3_K_M 3.8 GB 6.84 GB 11.2 GB
11.2 GB free
162 llama.cpp Run
Gemma 4 E4B 8.0B Q3_K_M 3.6 GB 1.78 GB 6.0 GB
16.4 GB free
168 Ollama Run
Ling 3.0 Tiny 7.9B-A1.3B New 7.9B MoE / 1.3B act Q3_K_M 3.6 GB 0.84 GB 5.0 GB
17.4 GB free
397 llama.cpp Run
DeepSeek-R1-Distill-Qwen 7B 7.62B Q3_K_M 3.5 GB 7.00 GB 11.1 GB
11.3 GB free
176 Ollama Run
Qwen2.5-Coder 7B 7.62B Q3_K_M 3.5 GB 7.00 GB 11.1 GB
11.3 GB free
176 Ollama Run
Olmo 3 7B Instruct 7.3B Q3_K_M 3.3 GB 9.50 GB 13.4 GB
9.0 GB free
184 Ollama Run
Mistral 7B Instruct v0.3 7.25B Q3_K_M 3.3 GB 4.00 GB 7.9 GB
14.5 GB free
185 Ollama Run
Gemma 4 E2B 5.1B Q3_K_M 2.3 GB 0.89 GB 3.8 GB
18.6 GB free
263 Ollama Run
Qwen3.5 4B 4.66B Q3_K_M 2.1 GB 4.00 GB 6.7 GB
15.7 GB free
288 Ollama Run
Gemma 3 4B 4.3B Q3_K_M 2.0 GB 3.11 GB 5.7 GB
16.7 GB free
312 Ollama Run
Qwen3 4B 4.02B Q3_K_M 1.8 GB 4.50 GB 6.9 GB
15.5 GB free
333 Ollama Run
Ministral 3 3B 3.85B Q3_K_M 1.8 GB 13.00 GB 15.4 GB
7.0 GB free
348 Ollama Run
Phi-4-mini 3.8B 3.84B Q3_K_M 1.7 GB 16.00 GB 18.3 GB
4.1 GB free
349 Ollama Run
Granite 4.1 3B 3.4B Q3_K_M 1.5 GB 10.00 GB 12.1 GB
10.3 GB free
394 Ollama Run
Llama 3.2 3B Instruct 3.21B Q3_K_M 1.5 GB 14.00 GB 16.1 GB
6.3 GB free
418 Ollama Run
LFM2.5 2.6B New 2.7B Q3_K_M 1.2 GB 2.00 GB 3.8 GB
18.6 GB free
497 llama.cpp Run
Qwen3.5 2B 2.27B Q3_K_M 1.0 GB 1.50 GB 3.1 GB
19.3 GB free
591 Ollama Run
Qwen3 1.7B 1.72B Q3_K_M 0.8 GB 3.50 GB 4.9 GB
17.5 GB free
779 Ollama Run
Llama 3.2 1B Instruct 1.24B Q3_K_M 0.6 GB 4.00 GB 5.2 GB
17.2 GB free
1081 Ollama Run
Gemma 3 1B 1.0B Q3_K_M 0.5 GB 0.14 GB 1.2 GB
21.2 GB free
1341 Ollama Run
Qwen3.5 0.8B 0.87B Q3_K_M 0.4 GB 1.50 GB 2.5 GB
19.9 GB free
1541 Ollama Run
Qwen3 0.6B 0.6B Q3_K_M 0.3 GB 3.50 GB 4.4 GB
18.0 GB free
2234 Ollama Run

Runs — tight

9 models · fits at 128K, drop context or quant to go longer
ModelParamsQuantWeights +KV 128KTotal VRAM headroom Tok/sRuntime
Qwen3.6 35B-A3B 35.9B MoE / 3.3B act Q3_K_M 16.3 GB 2.50 GB 19.4 GB
3.0 GB free
156 llama.cpp Run
Ornith 1.5 35B-A3B New this week 35.9B MoE / 3.3B act Q3_K_M 16.3 GB 2.50 GB 19.4 GB
3.0 GB free
156 llama.cpp Run
Olmo 3.1 32B Instruct 32.2B Q3_K_M 14.7 GB 4.75 GB 20.0 GB
2.4 GB free
42 llama.cpp Run
GLM-4.7-Flash 30B-A3B 31.2B MoE / 3B act Q3_K_M 14.2 GB 6.61 GB 21.4 GB
1.0 GB free
172 llama.cpp Run
Qwen3.8 27B New this week 27.8B Q3_K_M 12.7 GB 8.00 GB 21.3 GB
1.1 GB free
48 llama.cpp Run
Qwen3.6 27B 27.8B Q3_K_M 12.7 GB 8.00 GB 21.3 GB
1.1 GB free
48 llama.cpp Run
Ministral 3 8B 8.92B Q3_K_M 4.1 GB 17.00 GB 21.7 GB
0.7 GB free
150 llama.cpp Run
Qwen3 8B 8.19B Q3_K_M 3.7 GB 18.00 GB 22.3 GB
0.1 GB free
164 llama.cpp Run
Llama 3.1 8B Instruct 8.03B Q3_K_M 3.7 GB 16.00 GB 20.3 GB
2.1 GB free
167 llama.cpp Run

Won't fit in VRAM

35 models · some are possible with CPU offload
ModelParamsQuantWeights +KV 128KTotal Over budget Tok/sRuntime
Qwen3.5 122B-A10B 125B MoE / 10B act Q3_K_M 56.9 GB 3.00 GB 60.5 GB +38.1 GB ~4.5 llama.cpp Why
Nemotron 3 Super 120B-A12B 124B MoE / 12B act Q3_K_M 56.4 GB 1.00 GB 58.0 GB +35.6 GB ~3.9 llama.cpp Why
Ling 3.0 Flash 124B-A5B New 124B MoE / 5.1B act Q3_K_M 56.4 GB 0.98 GB 58.0 GB +35.6 GB ~9.2 llama.cpp Why
Mistral Small 4 119B-A6B 119B MoE / 6.5B act Q3_K_M 54.2 GB 2.81 GB 57.6 GB +35.2 GB ~7.0 llama.cpp Why
gpt-oss 120B 117B MoE / 5.1B act MXFP4 60.5 GB 4.50 GB 65.6 GB +43.2 GB ~7.2 llama.cpp Why
Llama 4 Scout 109B-A17B 109B MoE / 17B act Q3_K_M 49.6 GB 7.13 GB 57.3 GB +34.9 GB ~2.5 llama.cpp Why
Llama 3.3 70B Instruct 70.6B Q3_K_M 32.1 GB 40.00 GB 72.7 GB +50.3 GB ~1.1 llama.cpp Why
DeepSeek-R1-Distill-Llama 70B 70.6B Q3_K_M 32.1 GB 40.00 GB 72.7 GB +50.3 GB ~1.1 llama.cpp Why
LLM-jp 4 33B Thinking New this week 33.2B Q3_K_M 15.1 GB 16.00 GB 31.7 GB +9.3 GB ~3.8 llama.cpp Why
Qwen3 32B 32.8B Q3_K_M 14.9 GB 32.00 GB 47.5 GB +25.1 GB ~2.4 llama.cpp Why
DeepSeek-R1-Distill-Qwen 32B 32.8B Q3_K_M 14.9 GB 32.00 GB 47.5 GB +25.1 GB ~2.4 llama.cpp Why
Qwen2.5-Coder 32B 32.8B Q3_K_M 14.9 GB 32.00 GB 47.5 GB +25.1 GB ~2.4 llama.cpp Why
Gemma 4 31B 31.3B Q3_K_M 14.2 GB 20.78 GB 35.6 GB +13.2 GB ~2.7 llama.cpp Why
Qwen3 30B-A3B 30.5B MoE / 3.3B act Q3_K_M 13.9 GB 12.00 GB 26.5 GB +4.1 GB ~28 llama.cpp Why
Qwen3 Coder 30B-A3B 30.5B MoE / 3.3B act Q3_K_M 13.9 GB 12.00 GB 26.5 GB +4.1 GB ~28 llama.cpp Why
Granite 4.1 30B 28.9B Q3_K_M 13.2 GB 32.00 GB 45.8 GB +23.4 GB ~2.8 llama.cpp Why
Gemma 3 27B 27.4B Q3_K_M 12.5 GB 10.41 GB 23.5 GB +1.1 GB ~21 llama.cpp Why
Devstral Small 2 24B 24B Q3_K_M 10.9 GB 20.00 GB 31.5 GB +9.1 GB ~3.9 llama.cpp Why
Mistral Small 3.2 24B 23.6B Q3_K_M 10.7 GB 20.00 GB 31.3 GB +8.9 GB ~4.0 llama.cpp Why
Qwen3 14B 14.8B Q3_K_M 6.7 GB 20.00 GB 27.3 GB +4.9 GB ~7.2 llama.cpp Why
DeepSeek-R1-Distill-Qwen 14B 14.8B Q3_K_M 6.7 GB 24.00 GB 31.3 GB +8.9 GB ~5.4 llama.cpp Why
Qwen2.5-Coder 14B 14.8B Q3_K_M 6.7 GB 24.00 GB 31.3 GB +8.9 GB ~5.4 llama.cpp Why
Ministral 3 14B 13.9B Q3_K_M 6.3 GB 20.00 GB 26.9 GB +4.5 GB ~7.8 llama.cpp Why
Mistral NeMo 12B 12.2B Q3_K_M 5.6 GB 20.00 GB 26.2 GB +3.8 GB ~9.4 llama.cpp Why
Granite 4.1 8B 8.79B Q3_K_M 4.0 GB 20.00 GB 24.6 GB +2.2 GB ~16 llama.cpp Why
Kimi K3 2.8T-A104B New 2780B MoE / 104B act Q3_K_M 1265.4 GB 3.38 GB 1269.4 GB +1247.0 GB ~0.3 llama.cpp Why
Qwen3.8 2.4T-A95B New 2446B MoE / 95B act Q3_K_M 1113.4 GB 11.50 GB 1125.5 GB +1103.1 GB ~0.3 llama.cpp Why
DeepSeek V4 Pro 1.6T-A49B New 1650B MoE / 49B act Q3_K_M 751.1 GB 8.58 GB 760.2 GB +737.8 GB ~0.6 llama.cpp Why
Kimi K2.6 1T-A32B 1027B MoE / 32B act Q3_K_M 467.5 GB 8.58 GB 476.7 GB +454.3 GB ~1.0 llama.cpp Why
GLM-5.2 744B-A40B 753B MoE / 40B act Q3_K_M 342.8 GB 10.97 GB 354.3 GB +331.9 GB ~0.8 llama.cpp Why
DeepSeek-R1 671B 671B MoE / 37B act Q3_K_M 305.4 GB 8.58 GB 314.6 GB +292.2 GB ~0.9 llama.cpp Why
Qwen3.5 397B-A17B 403B MoE / 17B act Q3_K_M 183.4 GB 3.75 GB 187.8 GB +165.4 GB ~2.0 llama.cpp Why
Ornith 1.5 397B-A17B New this week 397B MoE / 17B act Q3_K_M 180.7 GB 3.75 GB 185.1 GB +162.7 GB ~2.0 llama.cpp Why
DeepSeek V4 Flash 284B-A13B New 284B MoE / 13B act Q3_K_M 129.3 GB 6.05 GB 135.9 GB +113.5 GB ~2.7 llama.cpp Why
Qwen3 235B-A22B 235B MoE / 22B act Q3_K_M 107.0 GB 23.50 GB 131.1 GB +108.7 GB ~1.4 llama.cpp Why

Totals = quantised weights + f16 KV cache at 128K tokens + 0.6 GB runtime overhead, against 22.4 GB usable VRAM (24 GB less display and driver reserve). Tokens per second are estimated from 1008 GB/s peak memory bandwidth at batch 1 — not measured. Read the method.