Can I Run DeepSeek-R1-Distill-Llama-8B on Intel Arc B570?

Autor: Jakub Rusinowski · Ostatnia aktualizacja: 12 lipca 2026

Yes, comfortably — DeepSeek R1 Distill Llama 8B at Q4_K_M needs 6.7 GB at 8K context (4.8 GB weights + 1.9 GB KV cache/overhead), leaving ~3.3 GB of the Intel Arc B570's 10 GB, at ~36 tok/s (est.), with room for up to 32K context.

These figures are for DeepSeek-R1-Distill-Llama-8B, a distill of Llama-3.1-8B — not the full DeepSeek R1. The full DeepSeek R1 (671B) needs about 405 GB of weights at Q4_K_M and is a different model.

See what else this hardware can run →

Kup ten sprzęt Intel Arc B570 10GB — 10 GB VRAM · 150 W board powerUruchom w chmurze RTX 4090 w RunPod — od $0.34/godz. · stawka sprawdzona 2026-07

lub porównaj w Vast.ai od $0.35/godz. (typical low · varies)

Jako partner Amazon zarabiamy na kwalifikujących się zakupach. Linki do chmurowych GPU są linkami polecającymi — możemy otrzymać prowizję bez dodatkowych kosztów dla Ciebie.

Ujawnienie afiliacyjne: Niektóre odnośniki na tej stronie to linki afiliacyjne — jeśli dokonasz zakupu za ich pośrednictwem, LLM Configurator może otrzymać prowizję bez dodatkowych kosztów dla Ciebie. Jako uczestnik programu Amazon Associates, LLM Configurator zarabia na kwalifikujących się zakupach.

Intel Arc B570 10GB
10 GB VRAM · 150 W board power
Ceny w 2026 są niestabilne — sprawdź aktualną ofertę.
Sprawdź cenę na Amazon

Intel Arc B570 Specs

VRAM10 GB
Memory Bandwidth380 GB/s

DeepSeek R1 Distill Llama 8B on the Intel Arc B570: VRAM by quantization

QuantVRAM neededFits 10 GB?Max contextWhole PC
F1617.9 GB✗ No——
Q8_010.4 GB✗ No——
Q6_K8.4 GB✓ Yes16K—
Q5_K_M7.5 GB✓ Yes16K—
Q4_K_M6.7 GB✓ Yes32K—
Q3_K_M5.3 GB✓ Yes32K—
Q2_K4.5 GB✓ Yes32K—

Assumes an 8K-token context with an f16 KV cache. A longer window needs more; a quantized KV cache needs less. “Max context” is the largest window that still fits in 10 GB. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.

Superseded model. DeepSeek R1 has been superseded by DeepSeek V4. This page is kept for reference; the newer family is a better starting point. DeepSeek V4 needs at least 172.8 GB at Q4_K_M with an 8K context, so it does not fit the Intel Arc B570.

Context costs VRAM too. At Q4_K_M on the Intel Arc B570: 8K 6.7 GB · 32K 9.9 GB · 128K 22.8 GB ✗. Past 128K it no longer fits 10 GB — a q8_0 KV cache buys roughly half of that back, which the calculator will price for you.

No compatible GPU? DeepSeek R1 Distill Llama 8B on 8 GB of system RAM, CPU only: runs.

DeepSeek R1 Sizes That Fit the Intel Arc B570 (at 8K context)

DeepSeek R1 Distill Llama 8BQ4_K_M · 6.7 GB at 8K context · ~36 tok/s (est.)
Buy vs. rent DeepSeek-R1-Distill-Llama-8B
Buy the GPU
~$219
Intel Arc B570 · MSRP
Rent by the hour
from $0.34/hr
RTX 4090 (24 GB) class

At 2 hrs/day, buying (~$219) beats renting at $0.34/hr after about 11 months.

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RunPod $0.34/hr
Rent on RunPod →
Vast.ai $0.35/hr · typical low · varies
Rent on Vast.ai →

Cloud rates verified 2026-07 — estimates, and marketplace prices vary. Buying price is GPU MSRP only, not a full PC.

FAQ

Is the Intel Arc B570 enough to run DeepSeek R1 locally?

Yes, comfortably — DeepSeek R1 Distill Llama 8B at Q4_K_M needs 6.7 GB at 8K context (4.8 GB weights + 1.9 GB KV cache/overhead), leaving ~3.3 GB of the Intel Arc B570's 10 GB, at ~36 tok/s (est.), with room for up to 32K context.

What's the best DeepSeek R1 size for the Intel Arc B570?

DeepSeek R1 Distill Llama 8B at Q4_K_M quantization needs 6.7 GB at 8K context (4.8 GB weights + 1.9 GB KV cache/overhead), estimated ~36 tokens/sec, up to 32K context.

Every DeepSeek R1 size on the Intel Arc B570

SizeVRAM at 8KVerdictSpeed
DeepSeek R1 (671B)406.5 GBDoes not fit—
DeepSeek R1 Distill Qwen 32B22.3 GBDoes not fit—
DeepSeek R1 Distill Qwen 14B10.6 GBRuns at Q3_K_M—

DeepSeek R1 on Other GPUs

Popular Models on the Intel Arc B570

VRAM Tier

Troubleshooting

Buying Guide

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