What can AMD Radeon RX 7900 XTX run for creative?

Build: AMD Radeon RX 7900 XTX + — + 32 GB RAM (windows)

Memory: 24 GB VRAM + 32 GB system RAM
Runner: llama.cpp (Vulkan)
AnyChatCodingAgentsReasoningVisionLong contextCreative

Runs comfortably
161 models

Ranked by fit for creative use case + predicted speed. Click a row for VRAM breakdown.

#1Hermes 3 Llama 3.1 8B
8B
hermes
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 13.9 GBHeadroom: 10.1 GBTTFT: fast
ollama run hermes3:8b
51
tok/s
Estimated
Weights
8.50 GB
KV cache
4.00 GB
Activations
0.43 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~167 ms (fast)
Model details →
#2Gemma 2 9B Instruct
9B
gemma
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 15.8 GBHeadroom: 8.2 GBTTFT: fast
ollama run gemma2:9b
45
tok/s
Estimated
Weights
9.80 GB
KV cache
4.50 GB
Activations
0.50 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~188 ms (fast)
Model details →
#3Hermes 3 Llama 3.2 3B
3B
hermes
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 4.4 GBHeadroom: 19.6 GBTTFT: instant
239
tok/s
Estimated
Weights
1.80 GB
KV cache
1.50 GB
Activations
0.10 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~63 ms (instant)
Model details →
#4Dolphin 3.0 Llama 3.2 3B
3B
dolphin
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 4.4 GBHeadroom: 19.6 GBTTFT: instant
239
tok/s
Estimated
Weights
1.80 GB
KV cache
1.50 GB
Activations
0.10 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~63 ms (instant)
Model details →
#5Dolphin 3.0 8B
8B
dolphin
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 10.3 GBHeadroom: 13.7 GBTTFT: fast
ollama run dolphin3:8b
89
tok/s
Estimated
Weights
5.00 GB
KV cache
4.00 GB
Activations
0.26 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~167 ms (fast)
Model details →
#6Gemma 2 2B Instruct
2B
gemma
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 3.2 GBHeadroom: 20.8 GBTTFT: instant
358
tok/s
Estimated
Weights
1.10 GB
KV cache
1.00 GB
Activations
0.06 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~42 ms (instant)
Model details →
#7Gemma 4 E2B (Effective 2B)
2B
gemma
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 4.3 GBHeadroom: 19.7 GBTTFT: instant
ollama run gemma4:e2b
203
tok/s
Estimated
Weights
2.20 GB
KV cache
1.00 GB
Activations
0.12 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~42 ms (instant)
Model details →
#8CodeGemma 7B
7B
gemma
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 8.9 GBHeadroom: 15.1 GBTTFT: fast
ollama run codegemma:7b
102
tok/s
Estimated
Weights
4.20 GB
KV cache
3.50 GB
Activations
0.22 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~146 ms (fast)
Model details →
#9Gemma 4 E4B (Effective 4B)
4B
gemma
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 7.6 GBHeadroom: 16.4 GBTTFT: instant
ollama run gemma4:e4b
102
tok/s
Estimated
Weights
4.40 GB
KV cache
2.00 GB
Activations
0.23 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~83 ms (instant)
Model details →
#10Gemma 3 4B
4B
gemma
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 7.6 GBHeadroom: 16.4 GBTTFT: instant
ollama run gemma3:4b
102
tok/s
Estimated
Weights
4.40 GB
KV cache
2.00 GB
Activations
0.23 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~83 ms (instant)
Model details →
#11Llama 3.2 3B Instruct
3B
llama
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 6.1 GBHeadroom: 17.9 GBTTFT: instant
ollama run llama3.2:3b
136
tok/s
Estimated
Weights
3.40 GB
KV cache
1.50 GB
Activations
0.18 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~63 ms (instant)
Model details →
#12Qwen 3 1.7B
1.7B
qwen
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 2.8 GBHeadroom: 21.2 GBTTFT: instant
421
tok/s
Estimated
Weights
0.90 GB
KV cache
0.85 GB
Activations
0.05 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~35 ms (instant)
Model details →

Runs with tradeoffs
56 models

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

Jamba 1.5 Mini
52B
other
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 39.0 GBHeadroom: 4.2 GBTTFT: fast
  • • Partial CPU offload: ~38% of layers run on CPU
60
tok/s
Estimated
Weights
30.00 GB
KV cache
6.50 GB
Activations
1.50 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~250 ms (fast)
Model details →
Gemma 3 12B
12B
gemma
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 20.7 GBHeadroom: 3.3 GBTTFT: fast
  • • Tight VRAM fit — only 3.3 GB headroom left for context growth
ollama run gemma3:12b
34
tok/s
Estimated
Weights
13.00 GB
KV cache
6.00 GB
Activations
0.66 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~250 ms (fast)
Model details →
Gemma 4 26B MoE
26B
gemma
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 21.1 GBHeadroom: 2.9 GBTTFT: noticeable
  • • Tight VRAM fit — only 2.9 GB headroom left for context growth
ollama run gemma4:26b-moe
28
tok/s
Estimated
Weights
16.00 GB
KV cache
3.25 GB
Activations
0.80 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~542 ms (noticeable)
Model details →
Gemma 4 26B-A4B
26B
gemma
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 21.1 GBHeadroom: 2.9 GBTTFT: noticeable
  • • Tight VRAM fit — only 2.9 GB headroom left for context growth
ollama run gemma4:26b-a4b-it-q4_K_M
28
tok/s
Estimated
Weights
16.00 GB
KV cache
3.25 GB
Activations
0.80 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~542 ms (noticeable)
Model details →
Gemma 3 27B
27B
gemma
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 21.2 GBHeadroom: 2.8 GBTTFT: noticeable
  • • Tight VRAM fit — only 2.8 GB headroom left for context growth
ollama run gemma3:27b
27
tok/s
Estimated
Weights
16.00 GB
KV cache
3.38 GB
Activations
0.80 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~563 ms (noticeable)
Model details →
MedGemma 27B
27B
gemma
Quant: Q4_K_MContext: 2,048VRAM: 21.2 GBHeadroom: 2.8 GBTTFT: noticeable
  • • Tight VRAM fit — only 2.8 GB headroom left for context growth
27
tok/s
Estimated
Weights
16.00 GB
KV cache
3.38 GB
Activations
0.80 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~563 ms (noticeable)
Model details →
GPT-OSS Swallow 20B RL v0.1
20B
other
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 22.6 GBHeadroom: 1.4 GBTTFT: fast
  • • Tight VRAM fit — only 1.4 GB headroom left for context growth
36
tok/s
Estimated
Weights
11.00 GB
KV cache
10.00 GB
Activations
0.56 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~417 ms (fast)
Model details →
Mistral Nemo 12B Instruct
12B
mistral
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 20.7 GBHeadroom: 3.3 GBTTFT: fast
  • • Tight VRAM fit — only 3.3 GB headroom left for context growth
ollama run mistral-nemo:12b
34
tok/s
Estimated
Weights
13.00 GB
KV cache
6.00 GB
Activations
0.66 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~250 ms (fast)
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: 23 new comfortable, 73 new tradeoff

  • • Qwen 3 0.6B
  • • Gemma 3 270M
  • • SmolLM2 135M Instruct
  • • TinyLlama 1.1B Chat v1.0
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: 94 new comfortable

  • • Qwen 3 0.6B
  • • Qwen 3 30B-A3B
  • • Qwen 2.5 Coder 32B Instruct
  • • Qwen3.6 27B
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: 76 new comfortable

  • • Qwen 3 0.6B
  • • Qwen 3 30B-A3B
  • • Qwen 2.5 Coder 32B Instruct
  • • Qwen3.6 27B
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 (19 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 (19 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 (19 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 (19 GB) combined.

—
Llama 4 Scout
109B
llama
Commercial OK

Even with CPU offload, needs more memory than your VRAM (24 GB) + 60% of system RAM (19 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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