RUNLOCALAIv38
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RUNLOCALAI · v38
Will it run? / AMD Radeon RX 7900 XTX

What can AMD Radeon RX 7900 XTX run?

Build: RX 7900 XTX + Ryzen 9 7950X + 64GB DDR5 (Linux/ROCm)

Memory: 24 GB VRAM + 64 GB system RAM
Runner: llama.cpp (ROCm)
AnyChatCodingAgentsReasoningVisionLong contextCreative

Runs comfortably
205 models

Full-VRAM resident, with room for context. No compromises.

#1all-MiniLM-L6-v2
0.022B
other
Commercial OK
Quant: Q4_K_MContext: 256VRAM: 2.0 GBHeadroom: 22.0 GBTTFT: instant
39752
tok/s
Estimated
Weights
0.01 GB
KV cache
0.00 GB
Activations
0.00 GB
Runtime
2.00 GB
Time to first token (prefill, 512-token prompt): ~0 ms (instant)
Model details →
#2Piper
0.025B
other
Commercial OK
Quant: Q4_K_MContext: 0VRAM: 2.0 GBHeadroom: 22.0 GBTTFT: instant
34981
tok/s
Estimated
Weights
0.02 GB
KV cache
0.00 GB
Activations
0.00 GB
Runtime
2.00 GB
Time to first token (prefill, 512-token prompt): ~1 ms (instant)
Model details →
#3Whisper Tiny
0.039B
other
Commercial OK
Quant: Q4_K_MContext: 30VRAM: 2.0 GBHeadroom: 22.0 GBTTFT: instant
22424
tok/s
Estimated
Weights
0.02 GB
KV cache
0.00 GB
Activations
0.00 GB
Runtime
2.00 GB
Time to first token (prefill, 512-token prompt): ~1 ms (instant)
Model details →
#4Whisper Base
0.074B
other
Commercial OK
Quant: Q4_K_MContext: 30VRAM: 2.0 GBHeadroom: 22.0 GBTTFT: instant
11818
tok/s
Estimated
Weights
0.04 GB
KV cache
0.00 GB
Activations
0.00 GB
Runtime
2.00 GB
Time to first token (prefill, 512-token prompt): ~2 ms (instant)
Model details →
#5Kokoro 82M
0.082B
other
Commercial OK
Quant: Q4_K_MContext: 0VRAM: 2.1 GBHeadroom: 21.9 GBTTFT: instant
10665
tok/s
Estimated
Weights
0.05 GB
KV cache
0.00 GB
Activations
0.00 GB
Runtime
2.00 GB
Time to first token (prefill, 512-token prompt): ~2 ms (instant)
Model details →
#6all-mpnet-base-v2
0.109B
other
Commercial OK
Quant: Q4_K_MContext: 384VRAM: 2.1 GBHeadroom: 21.9 GBTTFT: instant
8023
tok/s
Estimated
Weights
0.07 GB
KV cache
0.00 GB
Activations
0.00 GB
Runtime
2.00 GB
Time to first token (prefill, 512-token prompt): ~2 ms (instant)
Model details →
#7paraphrase-multilingual-MiniLM-L12-v2
0.118B
other
Commercial OK
Quant: Q4_K_MContext: 128VRAM: 2.1 GBHeadroom: 21.9 GBTTFT: instant
7411
tok/s
Estimated
Weights
0.07 GB
KV cache
0.00 GB
Activations
0.00 GB
Runtime
2.00 GB
Time to first token (prefill, 512-token prompt): ~2 ms (instant)
Model details →
#8Nomic Embed Text v1.5
0.137B
other
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 2.2 GBHeadroom: 21.8 GBTTFT: instant
6383
tok/s
Estimated
Weights
0.08 GB
KV cache
0.07 GB
Activations
0.01 GB
Runtime
2.00 GB
Time to first token (prefill, 512-token prompt): ~3 ms (instant)
Model details →
#9SmolLM2 135M Instruct
0.135B
other
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 2.2 GBHeadroom: 21.8 GBTTFT: instant
6478
tok/s
Estimated
Weights
0.08 GB
KV cache
0.07 GB
Activations
0.01 GB
Runtime
2.00 GB
Time to first token (prefill, 512-token prompt): ~3 ms (instant)
Model details →
#10GTE ModernBERT Base
0.149B
other
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 2.2 GBHeadroom: 21.8 GBTTFT: instant
5869
tok/s
Estimated
Weights
0.09 GB
KV cache
0.07 GB
Activations
0.01 GB
Runtime
2.00 GB
Time to first token (prefill, 512-token prompt): ~3 ms (instant)
Model details →
#11Whisper Small
0.244B
other
Commercial OK
Quant: Q4_K_MContext: 30VRAM: 2.2 GBHeadroom: 21.8 GBTTFT: instant
3584
tok/s
Estimated
Weights
0.15 GB
KV cache
0.00 GB
Activations
0.01 GB
Runtime
2.00 GB
Time to first token (prefill, 512-token prompt): ~5 ms (instant)
Model details →
#12Gemma 3 270M
0.27B
gemma
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 2.3 GBHeadroom: 21.7 GBTTFT: instant
3239
tok/s
Estimated
Weights
0.16 GB
KV cache
0.14 GB
Activations
0.02 GB
Runtime
2.00 GB
Time to first token (prefill, 512-token prompt): ~6 ms (instant)
Model details →

Runs with tradeoffs
68 models

Tight VRAM, partial CPU offload, or context-limited.

Qwen 3 30B-A3B
30B
qwen
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 50.5 GBHeadroom: 11.9 GBTTFT: noticeable
  • • Partial CPU offload: ~52% of layers run on CPU
  • • CPU is the bottleneck — upgrading RAM bandwidth helps more than VRAM here
ollama run qwen3:30b
2
tok/s
Estimated
Weights
31.88 GB
KV cache
15.00 GB
Activations
1.60 GB
Runtime
2.00 GB
Time to first token (prefill, 512-token prompt): ~625 ms (noticeable)
Model details →
Qwen 2.5 Coder 32B Instruct
32B
qwen
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 22.8 GBHeadroom: 1.2 GBTTFT: noticeable
  • • Tight VRAM fit — only 1.2 GB headroom left for context growth
ollama run qwen2.5-coder:32b
27
tok/s
Estimated
Weights
19.32 GB
KV cache
0.54 GB
Activations
0.97 GB
Runtime
2.00 GB
Time to first token (prefill, 512-token prompt): ~667 ms (noticeable)
Model details →
Llama 3.3 70B Instruct
70B
llama
Commercial OK
Quant: Q5_K_MContext: 8,192VRAM: 55.2 GBHeadroom: 7.2 GBTTFT: noticeable
  • • Partial CPU offload: ~57% of layers run on CPU
  • • CPU is the bottleneck — upgrading RAM bandwidth helps more than VRAM here
ollama run llama3.3:70b
1
tok/s
Estimated
Weights
48.13 GB
KV cache
2.68 GB
Activations
2.41 GB
Runtime
2.00 GB
Time to first token (prefill, 512-token prompt): ~1459 ms (noticeable)
Model details →
Qwen 3 32B
32B
qwen
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 53.7 GBHeadroom: 8.7 GBTTFT: noticeable
  • • Partial CPU offload: ~55% of layers run on CPU
  • • CPU is the bottleneck — upgrading RAM bandwidth helps more than VRAM here
ollama run qwen3:32b
2
tok/s
Estimated
Weights
34.00 GB
KV cache
16.00 GB
Activations
1.71 GB
Runtime
2.00 GB
Time to first token (prefill, 512-token prompt): ~667 ms (noticeable)
Model details →
Gemma 4 31B Dense
31B
gemma
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 52.1 GBHeadroom: 10.3 GBTTFT: noticeable
  • • Partial CPU offload: ~54% of layers run on CPU
  • • CPU is the bottleneck — upgrading RAM bandwidth helps more than VRAM here
ollama run gemma4:31b
2
tok/s
Estimated
Weights
32.94 GB
KV cache
15.50 GB
Activations
1.66 GB
Runtime
2.00 GB
Time to first token (prefill, 512-token prompt): ~646 ms (noticeable)
Model details →
DeepSeek R1 Distill Llama 70B
70B
deepseek
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 55.1 GBHeadroom: 7.3 GBTTFT: noticeable
  • • Partial CPU offload: ~56% of layers run on CPU
  • • CPU is the bottleneck — upgrading RAM bandwidth helps more than VRAM here
ollama run deepseek-r1:70b
1
tok/s
Estimated
Weights
42.26 GB
KV cache
8.75 GB
Activations
2.12 GB
Runtime
2.00 GB
Time to first token (prefill, 512-token prompt): ~1459 ms (noticeable)
Model details →
DeepSeek R1 Distill Qwen 32B
32B
deepseek
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 53.7 GBHeadroom: 8.7 GBTTFT: noticeable
  • • Partial CPU offload: ~55% of layers run on CPU
  • • CPU is the bottleneck — upgrading RAM bandwidth helps more than VRAM here
ollama run deepseek-r1:32b
2
tok/s
Estimated
Weights
34.00 GB
KV cache
16.00 GB
Activations
1.71 GB
Runtime
2.00 GB
Time to first token (prefill, 512-token prompt): ~667 ms (noticeable)
Model details →
Gemma 4 26B MoE
26B
gemma
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 21.7 GBHeadroom: 2.3 GBTTFT: noticeable
  • • Tight VRAM fit — only 2.3 GB headroom left for context growth
ollama run gemma4:26b-moe
34
tok/s
Estimated
Weights
15.70 GB
KV cache
3.25 GB
Activations
0.79 GB
Runtime
2.00 GB
Time to first token (prefill, 512-token prompt): ~542 ms (noticeable)
Model details →

What if you upgraded?

Hypothetical scenarios. We re-ran the compatibility engine for each.

+32 GB system RAM

~$80–150

Doubles your CPU-offload working set. Helps when models don't quite fit in VRAM.

Unlocks: 70 new tradeoff

  • • Qwen 3 30B-A3B
  • • Qwen 2.5 Coder 32B Instruct
  • • Llama 3.3 70B Instruct
  • • Qwen 3 32B
Shop this upgrade↗

Upgrade to AMD Instinct MI210

see current pricing

64 GB VRAM (vs your 24 GB) plus a bandwidth jump from ~960 GB/s to ~1638 GB/s.

Unlocks: 66 new comfortable

  • • DeepSeek Coder V2 Lite (16B)
  • • Mistral Nemo 12B Instruct
  • • Gemma 3 12B
  • • Pixtral 12B
Shop this upgrade↗

Add a second AMD Radeon RX 7900 XTX

~$899

Tensor parallelism splits the model across both cards, effectively doubling VRAM. Bandwidth doesn't double — runs ~1.5× the single-card speed in practice.

Unlocks: 53 new comfortable

  • • DeepSeek Coder V2 Lite (16B)
  • • Mistral Nemo 12B Instruct
  • • Gemma 3 12B
  • • Pixtral 12B
Shop this upgrade↗

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Won't run
top 5 popular models

Need more memory than you have. Shown for orientation.

DeepSeek V4 Pro (1.6T MoE)
1600B
deepseek
Commercial OK

Even with CPU offload, needs more memory than your VRAM (24 GB) + 60% of system RAM (38 GB) combined.

—
Qwen 3.5 235B-A17B (MoE)
397B
qwen
Commercial OK

Even with CPU offload, needs more memory than your VRAM (24 GB) + 60% of system RAM (38 GB) combined.

—
Qwen 3 235B-A22B
235B
qwen
Commercial OK

Even with CPU offload, needs more memory than your VRAM (24 GB) + 60% of system RAM (38 GB) combined.

—
DeepSeek R1 (671B reasoning)
671B
deepseek
Commercial OK

Even with CPU offload, needs more memory than your VRAM (24 GB) + 60% of system RAM (38 GB) combined.

—
DeepSeek V4 Flash (284B MoE)
284B
deepseek
Commercial OK

Even with CPU offload, needs more memory than your VRAM (24 GB) + 60% of system RAM (38 GB) combined.

—

How to read these numbers

Measured here
Measured here - RunLocalAI ran this exact combo on owner hardware with public evidence.

Source-backed
Source-backed / community - a reproduced public source supports the speed, but it is not labeled as owner-measured.

Extrapolated
Extrapolated - predicted from a measured benchmark on similar-bandwidth hardware.

Estimated
Estimated - formula based on VRAM bandwidth and model architecture; not a benchmark row.

RunLocalAI Will-It-Run Framework →

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