Can Desktop PC · 2× GeForce RTX 3090 (48 GB) · 128 GB RAM run Gemma 4 26B-A4B?
48 GB VRAM + 128 GB RAM · 936 GB/s memory bandwidth · Gemma 4 26B-A4B has 25.8B parameters (3.8B active per token).
Short answer
Yes, excellent for chat and comfortable or better for every workload we test.
Best quantization for chat: Q6_K (20 GB of weights) on Ollama. Generation: 110–180 tok/s, leaving about 26 GB free for your other apps.
How it rates for each workload
Same model and machine, different jobs. Agents and long documents send far bigger prompts than chat, so they need much more speed and memory.
| Workload | Verdict | Quant | Generation | First reply | Context | |
|---|---|---|---|---|---|---|
| Chatwith Open WebUI | Excellent | Q6_K | 110–180 tok/s | under 1 s | 8K | Details |
| Coding questionswith Continue | Excellent | Q6_K | 110–180 tok/s | ≈1 s | 16K | Details |
| Coding in a repositorywith Aider | Comfortable | Q6_K | 100–170 tok/s | ≈3 s | 32K | Details |
| Agentic codingwith OpenCode | Comfortable | Q6_K | 95–160 tok/s | ≈3 s | 32K | Details |
| Long documents (64K)with Open WebUI | Excellent | Q6_K | 80–140 tok/s | ≈9 s | 64K | Details |
Speeds are bandwidth-based estimates; no direct benchmark exists for this pair. “First reply” is the time to read the workload’s opening prompt. How we calculate
Get it running
Copy-paste commands for the Q6_K build with a 64K context. Ollama and llama.cpp download the file straight from Hugging Face.
ollama run hf.co/unsloth/gemma-4-26B-A4B-it-GGUF:UD-Q6_K_XL
Downloads 23.3 GB (UD-Q6_K_XL). Ollama's default context is small: set OLLAMA_CONTEXT_LENGTH=65536 before `ollama serve` for long prompts.
Other models for Desktop PC · 2× GeForce RTX 3090 (48 GB) · 128 GB RAM
The best-rated models for chat on this machine.
- Qwen3.6 35B-A3B140–230 tok/sExcellent
- Qwen3.5 35B-A3B140–230 tok/sExcellent
- LFM2.5 24B-A2B270–450 tok/sExcellent
- gpt-oss-20b160–270 tok/sExcellent
- GLM-4.7-Flash (30B-A3B)130–220 tok/sExcellent
- Qwen3 30B-A3B Instruct 2507120–190 tok/sExcellent
Cheapest machines for Gemma 4 26B-A4B
Hardware rated comfortable or better for chat, lowest price first.
- Mac mini M4 24 GB$999 · 25–35 tok/sComfortable
- Mac mini M6 24 GB$1,299 · 30–50 tok/sComfortable
- Laptop · Core Ultra 7 258V (Arc 140V) · 32 GB$1,300 · 15–25 tok/sExcellent
- Laptop · Ryzen AI 9 HX 370 (Radeon 890M) · 32 GB$1,300 · 16–25 tok/sComfortable
- Mac mini M4 32 GB$1,399 · 25–35 tok/sExcellent
- MacBook Air M4 24 GB$1,399 · 25–35 tok/sComfortable
Different tool, context size or workload?
These pages use typical settings. The full check models your exact setup.