will it local
RDNA3 flagship workstation: 48GB GDDR6 at 864 GB/s, 295W. One of the few 48GB single cards before the Blackwell generation.
computed band 84.0-130.0 tok/s for 8B Q4_K_M
Effective decode window: 0.50–0.75 of 864 GB/s nominal → ~432–648 GB/s effective (llama.cpp decode, Q4_K_M basis; arch window, community-calibrated)
→ 13b-q4 full 14.6 GB needed of 48 GB usable — headroom for context
→ 3b-q4 full 2.8 GB needed of 48 GB usable — headroom for context
→ 4b-q4 full 3.7 GB needed of 48 GB usable — headroom for context
→ 8b-q4 full 6.1 GB needed of 48 GB usable — headroom for context
no single-card bench published — band is computed (see notes)
Nominal bandwidth: 864 GB/s — see the effective decode window above
→ qwen3:0.6b on Tesla M60 (16GB, used) ($35) 0.6B · 0.6GB · needs ~1GB (4k ctx)
→ qwen3:1.7b on Tesla M60 (16GB, used) ($35) 1.7B · 1.4GB · needs ~1.8GB (4k ctx)
→ qwen3:4b on Tesla M60 (16GB, used) ($35) 4B · 2.6GB · needs ~3.2GB (4k ctx)
→ llama3.2:1b on Tesla M60 (16GB, used) ($35) 1B · 1.3GB · needs ~1.4GB (4k ctx)
→ llama3.2:3b on Tesla M60 (16GB, used) ($35) 3B · 2.0GB · needs ~2.4GB (4k ctx)
→ gemma3:1b on Tesla M60 (16GB, used) ($35) 1B · 1.0GB · needs ~1.1GB (4k ctx)
→ phi4:mini on Tesla M60 (16GB, used) ($35) mini 3.8B · 2.5GB · needs ~3GB (4k ctx)
→ moondream:2b on Tesla M60 (16GB, used) ($35) 2B · 1.7GB · needs ~3.7GB (4k ctx)
→ whisper:tiny on Tesla M60 (16GB, used) ($35) tiny · 0.1GB · needs ~2.1GB (4k ctx)
→ whisper on Tesla M60 (16GB, used) ($35) base · 0.3GB · needs ~2.3GB (4k ctx)
→ whisper:small on Tesla M60 (16GB, used) ($35) small · 0.9GB · needs ~2.9GB (4k ctx)
→ whisper:medium on Tesla M60 (16GB, used) ($35) medium · 3.1GB · needs ~5.1GB (4k ctx)
→ kokoro:82m on Tesla M60 (16GB, used) ($35) 82M · 0.3GB · needs ~2.3GB (4k ctx)
→ gemma3:4b on Tesla M60 (16GB, used) ($35) 4B · 3.3GB · needs ~3.8GB (4k ctx)
→ deepseek-r1:7b on Tesla M60 (16GB, used) ($35) distill 7B · 4.7GB · needs ~4.9GB (4k ctx)
→ mistral:7b on Tesla M60 (16GB, used) ($35) 7B · 4.1GB · needs ~4.6GB (4k ctx)
→ llava:7b on Tesla M60 (16GB, used) ($35) 7B · 4.7GB · needs ~6.7GB (4k ctx)
→ qwen3:8b on Tesla M60 (16GB, used) ($35) 8B · 5.2GB · needs ~5.8GB (4k ctx)
→ qwen2.5vl:7b on Tesla M60 (16GB, used) ($35) 7B · 5.6GB · needs ~5.8GB (4k ctx)
→ llama3.1:8b on Tesla M60 (16GB, used) ($35) 8B · 4.9GB · needs ~5.4GB (4k ctx)
→ deepseek-r1:8b on Tesla M60 (16GB, used) ($35) distill 8B · 4.9GB · needs ~5.4GB (4k ctx)
→ whisper:large-v3 on Tesla M60 (16GB, used) ($35) large-v3 · 6.2GB · needs ~8.2GB (4k ctx)
→ mistral-nemo:12b on Tesla M60 (16GB, used) ($35) 12B · 7.1GB · needs ~7.7GB (4k ctx)
→ sdxl on Tesla M60 (16GB, used) ($35) SDXL base · 6.9GB · needs ~8.9GB (4k ctx)
→ llava:13b on Tesla M60 (16GB, used) ($35) 13B · 8.0GB · needs ~11.1GB (4k ctx)
→ gemma3:12b on Tesla M60 (16GB, used) ($35) 12B · 8.1GB · needs ~9.6GB (4k ctx)
→ qwen3:14b on Tesla M60 (16GB, used) ($35) 14B · 9.3GB · needs ~9.9GB (4k ctx)
→ deepseek-r1:14b on Tesla M60 (16GB, used) ($35) distill 14B · 9.0GB · needs ~9.8GB (4k ctx)
→ phi4:14b on Tesla M60 (16GB, used) ($35) 14B · 9.1GB · needs ~9.9GB (4k ctx)
→ gpt-oss:20b on Tesla M40 (24GB, used) ($50) 20B MoE · 14GB · needs ~14.2GB (4k ctx)
→ devstral:24b on Tesla M40 (24GB, used) ($50) 24B · 14.6GB · needs ~15.2GB (4k ctx)
→ qwen3.8:27b on Tesla V100 32GB (used) ($640) 27B · 16.5GB · needs ~18.5GB (4k ctx)
→ gemma3:27b on Tesla V100 32GB (used) ($640) 27B · 17GB · needs ~18.9GB (4k ctx)
→ flux:schnell on Tesla V100 32GB (used) ($640) schnell fp8 · 17GB · needs ~19GB (4k ctx)
→ qwen3:30b-a3b on Tesla V100 32GB (used) ($640) 30B-A3B MoE · 18.6GB · needs ~19GB (4k ctx)
→ qwen3-coder:30b-a3b on Tesla V100 32GB (used) ($640) 30B-A3B MoE · 18.6GB · needs ~19GB (4k ctx)
→ qwen3:32b on Tesla V100 32GB (used) ($640) 32B · 20GB · needs ~21GB (4k ctx)
→ deepseek-r1:32b on Tesla V100 32GB (used) ($640) distill 32B · 20GB · needs ~21GB (4k ctx)
→ qwen2.5vl:32b on Mac mini M5 Pro (64GB) ($1669) 32B · 22GB · needs ~23GB (4k ctx)
→ flux:dev on Mac mini M5 Pro (64GB) ($1669) dev fp8 · 23GB · needs ~25GB (4k ctx)
→ mixtral:8x7b on Mac mini M5 Pro (64GB) ($1669) 8x7B MoE · 26GB · needs ~26.5GB (4k ctx)
→ llama3.1:70b on NIMO AI Mini PC (128GB) ($1999) 70B · 43GB · needs ~44.2GB (4k ctx)
→ llama3.3:70b on NIMO AI Mini PC (128GB) ($1999) 70B · 43GB · needs ~44.2GB (4k ctx)
→ deepseek-r1:70b on NIMO AI Mini PC (128GB) ($1999) distill 70B · 43GB · needs ~44.2GB (4k ctx)
—
⚠ 48GB: 70B Q4 fits tightly with modest context — quantize carefully
⚠ ROCm: gfx1100 target; verify your runtime's support matrix first
⚠ Same RDNA3 caveats as the W7800 (thinner ecosystem than CUDA)
$16499 — 96GB Blackwell when 48GB stops being enough