Can Laptop · Core Ultra 7 258V (Arc 140V) · 32 GB run Gemma 4 12B?
32 GB unified · 136 GB/s memory bandwidth · Gemma 4 12B has 12B parameters.
Short answer
Yes, acceptable for chat; borderline for coding in a repository.
Best quantization for chat: Q5_K_M (8.0 GB of weights) on LM Studio. Generation: 6–10 tok/s, leaving about 14 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 | Acceptable | Q5_K_M | 6–10 tok/s | ≈7 s | 8K | Details |
| Coding questionswith Continue | Acceptable | Q4_K_M | 7–12 tok/s | ≈45 s | 16K | Details |
| Coding in a repositorywith Aider | Borderline | Q4_K_M | 7–12 tok/s | ≈2 min | 32K | Details |
| Agentic codingwith OpenCode | Borderline | Q5_K_M | 6–10 tok/s | ≈3 min | 32K | Details |
| Long documents (64K)with Open WebUI | Acceptable | Q4_K_M | 7–11 tok/s | ≈9 min | 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 Q4_K_M build with a 64K context. Ollama and llama.cpp download the file straight from Hugging Face.
ollama run hf.co/unsloth/gemma-4-12B-it-GGUF:Q4_K_M
Downloads 7.12 GB (Q4_K_M). Ollama's default context is small: set OLLAMA_CONTEXT_LENGTH=65536 before `ollama serve` for long prompts.
Other models for Laptop · Core Ultra 7 258V (Arc 140V) · 32 GB
The best-rated models for chat on this machine.
- LFM2.5 24B-A2B30–50 tok/sExcellent
- gpt-oss-20b18–30 tok/sExcellent
- Gemma 4 26B-A4B15–25 tok/sExcellent
- Qwen3.6 35B-A3B25–45 tok/sExcellent
- Qwen3.5 35B-A3B25–45 tok/sExcellent
- MiniCPM5 2B19–30 tok/sExcellent
Cheapest machines for Gemma 4 12B
Hardware rated comfortable or better for chat, lowest price first.
- Mac mini M4 24 GB$999 · 11–15 tok/sComfortable
- Desktop PC · Intel Arc B580 · 32 GB RAM$1,150 · 25–35 tok/sExcellent
- Desktop PC · GeForce RTX 3060 12GB · 32 GB RAM$1,200 · 25–40 tok/sExcellent
- Mac mini M6 24 GB$1,299 · 10–17 tok/sComfortable
- Desktop PC · GeForce RTX 5060 Ti 16GB · 32 GB RAM$1,330 · 30–40 tok/sExcellent
- Desktop PC · GeForce RTX 4060 Ti 16GB · 32 GB RAM$1,350 · 16–25 tok/sExcellent
Different tool, context size or workload?
These pages use typical settings. The full check models your exact setup.