local intelligence

will it local

Best local LLMs for the AMD RX 6700 XT

12GB · RDNA2 gfx1031

Hardware value real, software tax heavy: unofficial ROCm, Linux >> Windows, Ollama-on-ROCm inconsistent vs llama.cpp HIP. Buy only at a deep discount, and only if terminal-comfortable.

explore the full catalogupgrade paths with live prices · what fits on each machine

Speed

computed band 15.0-37.0 tok/s for 8B Q4_K_M (roofline, 384 GB/s VRAM); community: 25-40 tok/s 7B Q4 (kb-audit-0903)

Effective decode window: 0.20–0.50 of 384 GB/s nominal → ~77–192 GB/s effective (llama.cpp decode, Q4_K_M basis; card-specific window from cited community benches)

Community check — localmaxxing.com medians (1 bucket): localmaxxing.com

→ ~38 tok/s · 12-15B Q4 · 4 runs · above our band — small sample; documented outlier, computed window stands

What fits (computed)

13b-q4 offload-partial 14.6 GB vs 12 GB usable — partial CPU offload, expect large speed loss

3b-q4 full 2.8 GB needed of 12 GB usable — headroom for context

4b-q4 full 3.7 GB needed of 12 GB usable — headroom for context

8b-q4 full 6.1 GB needed of 12 GB usable — headroom for context

Cited community benches (1 rows)

→ 25-40 tok/s · 7B Q4 ROCm guides · kb-audit-0903

Runs fully in memory (machine alternatives)

Nominal bandwidth: 384 GB/s — see the effective decode window above

qwen3:0.6b on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) 0.6B · 0.6GB · needs ~1GB (4k ctx)

qwen3:1.7b on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) 1.7B · 1.4GB · needs ~1.8GB (4k ctx)

qwen3:4b on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) 4B · 2.6GB · needs ~3.2GB (4k ctx)

llama3.2:1b on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) 1B · 1.3GB · needs ~1.4GB (4k ctx)

llama3.2:3b on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) 3B · 2.0GB · needs ~2.4GB (4k ctx)

gemma3:1b on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) 1B · 1.0GB · needs ~1.1GB (4k ctx)

phi4:mini on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) mini 3.8B · 2.5GB · needs ~3GB (4k ctx)

moondream:2b on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) 2B · 1.7GB · needs ~3.7GB (4k ctx)

whisper:tiny on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) tiny · 0.1GB · needs ~2.1GB (4k ctx)

whisper on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) base · 0.3GB · needs ~2.3GB (4k ctx)

whisper:small on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) small · 0.9GB · needs ~2.9GB (4k ctx)

whisper:medium on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) medium · 3.1GB · needs ~5.1GB (4k ctx)

kokoro:82m on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) 82M · 0.3GB · needs ~2.3GB (4k ctx)

gemma3:4b on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) 4B · 3.3GB · needs ~3.8GB (4k ctx)

deepseek-r1:7b on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) distill 7B · 4.7GB · needs ~4.9GB (4k ctx)

mistral:7b on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) 7B · 4.1GB · needs ~4.6GB (4k ctx)

llava:7b on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) 7B · 4.7GB · needs ~6.7GB (4k ctx)

qwen3:8b on Tesla P100 (16GB, used) ($135) 8B · 5.2GB · needs ~5.8GB (4k ctx)

qwen2.5vl:7b on Tesla P100 (16GB, used) ($135) 7B · 5.6GB · needs ~5.8GB (4k ctx)

llama3.1:8b on Tesla P100 (16GB, used) ($135) 8B · 4.9GB · needs ~5.4GB (4k ctx)

deepseek-r1:8b on Tesla P100 (16GB, used) ($135) distill 8B · 4.9GB · needs ~5.4GB (4k ctx)

whisper:large-v3 on Tesla P100 (16GB, used) ($135) large-v3 · 6.2GB · needs ~8.2GB (4k ctx)

mistral-nemo:12b on Tesla P100 (16GB, used) ($135) 12B · 7.1GB · needs ~7.7GB (4k ctx)

sdxl on Tesla P100 (16GB, used) ($135) SDXL base · 6.9GB · needs ~8.9GB (4k ctx)

llava:13b on Tesla P100 (16GB, used) ($135) 13B · 8.0GB · needs ~11.1GB (4k ctx)

gemma3:12b on Tesla P100 (16GB, used) ($135) 12B · 8.1GB · needs ~9.6GB (4k ctx)

qwen3:14b on Tesla P100 (16GB, used) ($135) 14B · 9.3GB · needs ~9.9GB (4k ctx)

deepseek-r1:14b on Tesla P100 (16GB, used) ($135) distill 14B · 9.0GB · needs ~9.8GB (4k ctx)

phi4:14b on Tesla P100 (16GB, used) ($135) 14B · 9.1GB · needs ~9.9GB (4k ctx)

Borderline — runs, but offloads

→ gpt-oss:20b 20B MoE — 14.2 GB vs 12 GB usable — partial CPU offload, expect large speed loss

Gotchas

⚠ Software tax is heavy: unofficial ROCm, Linux >> Windows

⚠ Ollama-on-ROCm inconsistent vs llama.cpp HIP

⚠ Buy only at a deep discount, and only if terminally patient with setup

⚠ Band basis: card-cited rows (LocalScore floor 16.4, guides 25-40) imply eff 0.22-0.47 of 384 GB/s — gfx1031 unofficial ROCm never reaches the 6800-class window; eff_override set 0905.

Where to go next

Radeon RX 9070 XT (16GB)

$749 — RDNA4 with real AI accelerators, official ROCm path - stay AMD without the tax

Newegg ↗ · Amazon ↗ (affiliate)

RTX 3090 (24GB, used)

$1100 — or jump the fence: 24GB CUDA maturity at used price

NVIDIA (used market) ↗ · Amazon ↗

2026-09-18 · ← full hardware catalog · fit = working set vs VRAM · speeds are community-reported, cited in our knowledge base