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RTX 4090 for local LLMs

24 measured results from 9 builds, each linked to its source.

Memory24 GB per card
Memory bandwidth1,008 GB/s (memory bandwidth as listed on llamabench)
Typical EU price≈€3,955 new (ASUS TUF Gaming RTX 4090 OG OC 24 GB, billiger.de, 2026-10-16)

Can it run? Flint 40B-A2.5B on RTX 4090 GLM 4.7 Flash on RTX 4090 Gemma 4 12B on RTX 4090 Gemma 4 26B-A4B on RTX 4090 Gemma 4 31B on RTX 4090 LFM2.5 24B-A2B on RTX 4090 Muse Glimmer 30B on RTX 4090 Nemotron 3.5 Bolt 74B-A9B on RTX 4090 Qwen3.5 9B on RTX 4090 Qwen3.6 27B on RTX 4090 Qwen3.6 35B-A3B on RTX 4090 gpt-oss 20B on RTX 4090

All builds with the RTX 4090

BuildGPU(s)Memory GB (total)Results
EPYC 7F52 jank rig: 4x3090 + 4090 + 4080 (136 GB VRAM) ⚠ unchecked4x RTX 3090, RTX 4090, RTX 40801361
Single RTX 4090 (llama.cpp CUDA scoreboard)RTX 4090 24GB241
RTX 4090 desktop (speed comparison vs Macs)RTX 4090 24GB242
Intel Core Ultra 265K + RTX 4090RTX 4090243
Ryzen 9 7900X + RTX 4090RTX 4090242
RTX 4090: 2026 models (llamabench community)RTX 4090248
RTX 4090 (llm-speed signed runs, Oct 2026): Qwen3.6 35B-A3B 161 tok/s, Gemma 4 12B QAT 98 tok/sRTX 4090243
RTX 4090 (llm-speed signed run, Oct 2026): Flint 40B-A2.5B at 169-179 tok/s on llama.cppRTX 4090242
RTX 4090: Nemotron 3.5 Bolt (IQ2) and Muse Glimmer 30BRTX 4090242

All measured results

(MTP, DFlash, DSpark and similar draft-and-verify methods give much higher tok/s on predictable text and are not comparable 1:1 with plain decode)

ModelBuildRan onQuantEnginetok/sDetails
Flint 40B-A2.5BRTX 4090 (llm-speed signed run, Oct 2026): Flint 40B-A2.5B at 169-179 tok/s on llama.cppRTX 4090NVFP4llama.cpp 0.7.0-dev (build 11803)179.4
Flint 40B-A2.5BRTX 4090 (llm-speed signed run, Oct 2026): Flint 40B-A2.5B at 169-179 tok/s on llama.cppRTX 4090UD-Q3_K_XLllama.cpp 0.7.0-dev (build 11803)169.2
Gemma 4 12BRTX 4090: 2026 models (llamabench community)RTX 4090llama-bench tg128 (quant per result)llama.cpp98.1
Gemma 4 12BRTX 4090 (llm-speed signed runs, Oct 2026): Qwen3.6 35B-A3B 161 tok/s, Gemma 4 12B QAT 98 tok/sRTX 4090QAT Q4_0llama.cpp b893197.7
Gemma 4 26B-A4BRTX 4090: 2026 models (llamabench community)RTX 4090llama-bench tg128 (quant per result)llama.cpp164
Gemma 4 31BRTX 4090: 2026 models (llamabench community)RTX 4090llama-bench tg128 (quant per result)llama.cpp43.8
LFM2.5 24B-A2BRTX 4090: 2026 models (llamabench community)RTX 4090llama-bench tg128 (quant per result)llama.cpp261-339
Muse Glimmer 30BRTX 4090: Nemotron 3.5 Bolt (IQ2) and Muse Glimmer 30BRTX 4090UD-Q4_K_XLllama.cpp a37cc461053.7context: 8K📏 llm-speed can-run page, runs on 2026-10-22, peak 15.1 GiB
Nemotron 3.5 Bolt 74B-A9BRTX 4090: 2026 models (llamabench community)RTX 4090llama-bench tg128 (quant per result)llama.cpp108partly in system RAM
Nemotron 3.5 Bolt 74B-A9BRTX 4090: Nemotron 3.5 Bolt (IQ2) and Muse Glimmer 30BRTX 4090NVIDIA mixed 2-bit IQ2 GGUF (22.0 GB)llama.cpp build 11669107.3prefill 1,814.7 tok/s📏 Measured decode, llm-speed runpartly in system RAM
Qwen3.5 9BRTX 4090: 2026 models (llamabench community)RTX 4090llama-bench tg128 (quant per result)llama.cpp137
Qwen3.6 35B-A3BRTX 4090 (llm-speed signed runs, Oct 2026): Qwen3.6 35B-A3B 161 tok/s, Gemma 4 12B QAT 98 tok/sRTX 4090Q4_K_Mllama.cpp b8931160.6
gpt-oss 20BIntel Core Ultra 265K + RTX 4090RTX 4090llama.cpp279.65
gpt-oss 20BRTX 4090: 2026 models (llamabench community)RTX 4090llama-bench tg128 (quant per result)llama.cpp203
DeepSeek R1 Distill 14B legacyIntel Core Ultra 265K + RTX 4090RTX 4090llama.cpp92.49
GLM 4.7 Flash legacyRTX 4090 (llm-speed signed runs, Oct 2026): Qwen3.6 35B-A3B 161 tok/s, Gemma 4 12B QAT 98 tok/sRTX 4090Q4_K_M (EPYC 75F3 host)Ollama 0.31.1164.9
Llama 2 7B legacySingle RTX 4090 (llama.cpp CUDA scoreboard)RTX 4090Q4_0llama.cpp CUDA (FA)188.96
Llama 3.1 70B legacyEPYC 7F52 jank rig: 4x3090 + 4090 + 4080 (136 GB VRAM) ⚠ uncheckedmixed / see buildQ8_0Oobabooga9
Llama 3.1 70B legacyRyzen 9 7900X + RTX 4090RTX 4090GPU+CPU offload3.1
Llama 3.1 8B legacyRTX 4090 desktop (speed comparison vs Macs)RTX 4090Q8llama.cpp-based52.99
Llama 3.2 3B legacyIntel Core Ultra 265K + RTX 4090RTX 4090llama.cpp334.67
Llama 3.2 3B legacyRyzen 9 7900X + RTX 4090RTX 4090llama.cpp237.05
Mistral Small 22B legacyRTX 4090 desktop (speed comparison vs Macs)RTX 4090Q6_Kllama.cpp-based26.72
Qwen3.6 27B legacyRTX 4090: 2026 models (llamabench community)RTX 4090llama-bench tg128 (quant per result)llama.cpp47.0

All RTX 4090 builds: see also all GPUs · best LLMs by memory size · download the dataset.

FAQ

How fast is the RTX 4090 for local LLMs?

The fastest plain-decode result we have is 334.67 tok/s on Llama 3.2 3B (, llama.cpp) in Intel Core Ultra 265K + RTX 4090. Speed depends heavily on the model, quant and engine, so compare like with like in the table. RigBase lists 24 measured results from 9 builds.

How much memory does the RTX 4090 have?

24 GB per card. Memory bandwidth: 1,008 GB/s (memory bandwidth as listed on llamabench).

Which models have been measured on the RTX 4090?

DeepSeek R1 Distill 14B, Flint 40B-A2.5B, GLM 4.7 Flash, Gemma 4 12B, Gemma 4 26B-A4B, Gemma 4 31B, LFM2.5 24B-A2B, Llama 2 7B, Llama 3.1 70B, Llama 3.1 8B, Llama 3.2 3B, Mistral Small 22B, Muse Glimmer 30B, Nemotron 3.5 Bolt 74B-A9B, Qwen3.5 9B, Qwen3.6 27B, Qwen3.6 35B-A3B, gpt-oss 20B.

Where do these numbers come from?

Every row links to a build page with its original public source (benchmark logs, READMEs, forum posts). RigBase does not re-run the benchmarks. Results marked ⚡ use speculative decoding and are not comparable 1:1 with plain decode.

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