MacBook Pro M4 Max 36GBOpción económica
36 GB Unified (+12)
B
Este setup está bastante equilibrado para este modelo.62 tok/s decodificación
~$2,499 MSRP
Can DeepSeek R1 Distill 8B run on Intel Arc Pro B60 24GB?
YES — Runs Great
B66Good
Estimated from fit model
DeepSeek R1 Distill 8B needs ~10.1 GB VRAM. Intel Arc Pro B60 24GB has 24.0 GB. With Q4_K_M quantization, expect ~54 tok/s.
Runtime: llama.cppCapacity: RoomyBandwidth: MediumStack: StandardBottleneck: Balanced
Operating mode
Choose the run profile you care about
Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Select quantization to explore
Q4_K_M (Medium quality) — 10.1 GB, 54.2 tok/s, Runs well
10.1 GB required24.0 GB available
42% VRAM used
Fit status
Runs well
Decode
54.2 tok/s
TTFT
3569 ms
Safe context
33K
Memory
10.1 GB / 24.0 GB
Memory breakdown
Weights4.9 GB
KV Cache2.0 GB
Runtime0.9 GB
Headroom2.4 GB
See how fast it feels
See how fast it feelsDeepSeek R1 Distill 8B on Intel Arc Pro B60 24GB
1st promptCold start — includes initialization
>Solve: If a train travels at 60 mph for 2.5 hours, how far does it go?
Let me work through this step by step.
Given information:
- Speed = 60 mph (miles per hour)
- Time = 2.5 hours
Formula: Distance = Speed x Time
Calculation:
Distance = 60 mph x 2.5 h
= 150 miles
The train travels 150 miles.
Double-check: at 60 mph the train covers 60 miles each hour. In half an hour it covers 30 miles. So in 2.5 hours: 60 + 60 + 30 = 150 miles. Confirmed.
2nd promptWarm — model ready, no init overhead
>What if the train stops for 20 minutes halfway?
The stop doesn't change the total distance covered while moving, but it affects total trip time.
Breakdown:
- First half: 1.25 hours at 60 mph = 75 miles
- Stop: 20 minutes (no distance)
- Second half: 1.25 hours at 60 mph = 75 miles
Total distance: 150 miles (same)
Total time: 2.5 h + 0.33 h = 2.83 hours
Average speed: 150 / 2.83 = 53 mph
The distance stays the same but average speed drops to 53 mph because of the stop.
Estimated: 54.2 tok/s decode · 3.6s TTFT (warm) · 136 tok/s prefill
What limits this setup
The raw memory story may look fine, but the software ecosystem is still a constraint here.
Runtime ecosystem is narrower than CUDA
Intel GPUs can look attractive on memory per dollar, but local AI tooling, kernels, and model coverage are still broader and easier on CUDA today.
Best improvement path
Prefer CUDA if you want the path of least resistance
If your goal is maximum runtime coverage, easier troubleshooting, and better support for new local AI releases, CUDA is usually still the safer upgrade path.
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | B | Runs well | 54.2 tok/s | 1947 ms | 33K |
| Coding | B | Runs well | 54.2 tok/s | 3569 ms | 33K |
| Agentic Coding | B | Runs well | 54.2 tok/s | 5191 ms | 33K |
| Reasoning | B | Runs well | 54.2 tok/s | 4218 ms | 33K |
| RAG | B | Runs well | 54.2 tok/s | 6489 ms | 33K |
Quantization options
How DeepSeek R1 Distill 8B (8B params) fits at each quantization level on Intel Arc Pro B60 24GB (24.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | B61 |
Q3_K_S | 3 | 3.9 GB | Low | B61 |
NVFP4 | 4 | 4.5 GB | Medium | B62 |
Q4_K_M | 4 | 4.9 GB | Medium | B62 |
Q5_K_M | 5 | 5.8 GB | High | B62 |
Q6_K | 6 | 6.6 GB | High | B63 |
Q8_0 | 8 | 8.6 GB | Very High | B64 |
F16Best for your GPU | 16 | 16.4 GB | Maximum | B66 |
Get started
Copy-paste commands to run DeepSeek R1 Distill 8B on your machine.
Run
ollama run deepseek-r1:8bOpciones de mejora
Hardware que ejecuta bien DeepSeek R1 Distill 8B
MacBook Pro M4 Max 48GBMejor relación calidad-precio
48 GB Unified (+24)546 GB/s (+90)
B
Sube la velocidad estimada de decodificación alrededor de un 52%.82.6 tok/s decodificación
Sube la velocidad estimada de decodificación alrededor de un 52%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$2,499 MSRP
Frequently asked questions
Can Intel Arc Pro B60 24GB run DeepSeek R1 Distill 8B?
Yes, Intel Arc Pro B60 24GB can run DeepSeek R1 Distill 8B with a B grade (Runs well). Expected decode speed: 54.2 tok/s.
How much VRAM does DeepSeek R1 Distill 8B need?
DeepSeek R1 Distill 8B (8B parameters) requires approximately 10.1 GB of memory with Q4_K_M quantization.
What is the best quantization for DeepSeek R1 Distill 8B?
The recommended quantization for DeepSeek R1 Distill 8B is Q4_K_M, which balances quality and memory efficiency.
What speed will DeepSeek R1 Distill 8B run at on Intel Arc Pro B60 24GB?
On Intel Arc Pro B60 24GB, DeepSeek R1 Distill 8B achieves approximately 54.2 tokens per second decode speed with a time-to-first-token of 3569ms using Q4_K_M quantization.
Can Intel Arc Pro B60 24GB run DeepSeek R1 Distill 8B for coding?
For coding workloads, DeepSeek R1 Distill 8B on Intel Arc Pro B60 24GB receives a B grade with 54.2 tok/s and 33K context.
What context window can DeepSeek R1 Distill 8B use on Intel Arc Pro B60 24GB?
On Intel Arc Pro B60 24GB, DeepSeek R1 Distill 8B can safely use up to 33K tokens of context. The model's official context limit is 33K, but available memory constrains the safe maximum.
What should I upgrade first if DeepSeek R1 Distill 8B feels slow on Intel Arc Pro B60 24GB?
Prefer CUDA if you want the path of least resistance. If your goal is maximum runtime coverage, easier troubleshooting, and better support for new local AI releases, CUDA is usually still the safer upgrade path.
Would CUDA be a better path than Intel Arc Pro B60 24GB for DeepSeek R1 Distill 8B?
Often yes, if your goal is the easiest setup and the widest runtime support. Intel can offer attractive memory capacity, but CUDA still tends to win on tooling maturity, guides, kernels, and model coverage for local AI.
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