Can Surface Laptop Ultra · RTX Spark N1X (20-core) · 128 GB run DeepSeek-R1-0528-Qwen3-8B?
128 GB unified · 300 GB/s memory bandwidth · DeepSeek-R1-0528-Qwen3-8B has 8.2B parameters.
Short answer
Yes, excellent for chat and acceptable or better for every workload we test.
Best quantization for chat: Q6_K (6.5 GB of weights) on Ollama. Generation: 20–35 tok/s, leaving about 108 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 | 20–35 tok/s | under 1 s | 8K | Details |
| Coding questionswith Continue | Comfortable | Q6_K | 19–30 tok/s | ≈1 s | 16K | Details |
| Coding in a repositorywith Aider | Acceptable | Q8_0 | 13–20 tok/s | ≈3 s | 32K | Details |
| Agentic codingwith OpenCode | Acceptable | Q8_0 | 13–20 tok/s | ≈4 s | 32K | Details |
| Long documents (64K)with Open WebUI | Acceptable | Q6_K | 10–17 tok/s | ≈15 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/DeepSeek-R1-0528-Qwen3-8B-GGUF:Q6_K
Downloads 6.73 GB (Q6_K). Ollama's default context is small: set OLLAMA_CONTEXT_LENGTH=65536 before `ollama serve` for long prompts.
Other models for Surface Laptop Ultra · RTX Spark N1X (20-core) · 128 GB
The best-rated models for chat on this machine.
- gpt-oss-120b40–65 tok/sExcellent
- Qwen3.6 35B-A3B45–75 tok/sExcellent
- Qwen3-Next 80B-A3B Instruct45–75 tok/sExcellent
- Gemma 4 26B-A4B35–60 tok/sExcellent
- LFM2.5 24B-A2B85–150 tok/sExcellent
- Qwen3.5 35B-A3B45–75 tok/sExcellent
Cheapest machines for DeepSeek-R1-0528-Qwen3-8B
Hardware rated comfortable or better for chat, lowest price first.
- Mac mini M4 16 GB$599 · 15–20 tok/sComfortable
- Mac mini M6 16 GB$899 · 16–25 tok/sExcellent
- Mac mini M4 24 GB$999 · 10–14 tok/sComfortable
- MacBook Air M4 16 GB$999 · 15–20 tok/sComfortable
- Mac mini M2 16 GB$999 · 13–17 tok/sComfortable
- MacBook Air M5 16 GB$1,099 · 15–25 tok/sComfortable
Same chip, other memory: 24 GB
Different tool, context size or workload?
These pages use typical settings. The full check models your exact setup.