What can AMD Radeon RX 7900 XTX run for chat?

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
175 models

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

#1Qwen 3 0.6B
0.6B
qwen
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 1.6 GBHeadroom: 22.4 GBTTFT: instant
1193
tok/s
Estimated
Weights
0.30 GB
KV cache
0.30 GB
Activations
0.02 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~13 ms (instant)
Model details →
#2Llama 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 →
#3Qwen 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 →
#4TinyLlama 1.1B Chat v1.0
1.1B
llama
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 1.8 GBHeadroom: 22.2 GBTTFT: instant
650
tok/s
Estimated
Weights
0.60 GB
KV cache
0.14 GB
Activations
0.03 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~23 ms (instant)
Model details →
#5Gemma 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 →
#6DeepSeek V2 Lite Chat
15.7B
deepseek
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 17.9 GBHeadroom: 6.1 GBTTFT: instant
298
tok/s
Estimated
Weights
8.60 GB
KV cache
7.85 GB
Activations
0.44 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~50 ms (instant)
Model details →
#7Kumru 2B
2.4B
mistral
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 3.8 GBHeadroom: 20.2 GBTTFT: instant
ollama run alibayram/kumru:latest
298
tok/s
Estimated
Weights
1.50 GB
KV cache
1.20 GB
Activations
0.08 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~50 ms (instant)
Model details →
#8TinyLlama 1.1B Chat v0.3 AWQ
1.1B
other
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 1.8 GBHeadroom: 22.2 GBTTFT: instant
650
tok/s
Estimated
Weights
0.60 GB
KV cache
0.14 GB
Activations
0.03 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~23 ms (instant)
Model details →
#9TinyLlama 1.1B Chat v0.3 GPTQ
1.1B
other
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 1.8 GBHeadroom: 22.2 GBTTFT: instant
650
tok/s
Estimated
Weights
0.60 GB
KV cache
0.14 GB
Activations
0.03 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~23 ms (instant)
Model details →
#10EXAONE 3.5 2.4B Instruct
2.4B
exaone
Quant: Q4_K_MContext: 8,192VRAM: 3.6 GBHeadroom: 20.4 GBTTFT: instant
298
tok/s
Estimated
Weights
1.30 GB
KV cache
1.20 GB
Activations
0.07 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~50 ms (instant)
Model details →
#11Falcon 3 3B Instruct
3B
falcon
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 4.3 GBHeadroom: 19.7 GBTTFT: instant
239
tok/s
Estimated
Weights
1.70 GB
KV cache
1.50 GB
Activations
0.09 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~63 ms (instant)
Model details →
#12PhoGPT 4B Chat
3.7B
other
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 5.0 GBHeadroom: 19.0 GBTTFT: instant
193
tok/s
Estimated
Weights
2.00 GB
KV cache
1.85 GB
Activations
0.11 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~77 ms (instant)
Model details →

Runs with tradeoffs
56 models

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

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 →
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 →
Sarvam M
24B
mistral
Commercial OK
Quant: Q4_K_MContext: 4,096VRAM: 20.9 GBHeadroom: 3.1 GBTTFT: noticeable
  • • Tight VRAM fit — only 3.1 GB headroom left for context growth
30
tok/s
Estimated
Weights
13.20 GB
KV cache
6.00 GB
Activations
0.66 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~500 ms (noticeable)
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 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 →
Gemma 4 31B Dense
31B
gemma
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 23.8 GBHeadroom: 0.2 GBTTFT: noticeable
  • • Tight VRAM fit — only 0.2 GB headroom left for context growth
ollama run gemma4:31b
23
tok/s
Estimated
Weights
18.00 GB
KV cache
3.88 GB
Activations
0.90 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~646 ms (noticeable)
Model details →
OLMo 2 32B
32B
other
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 37.0 GBHeadroom: 6.2 GBTTFT: noticeable
  • • Partial CPU offload: ~35% of layers run on CPU
22
tok/s
Estimated
Weights
19.00 GB
KV cache
16.00 GB
Activations
0.96 GB
Runtime
1.00 GB
Time to first token (prefill, 512-token prompt): ~667 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: 9 new comfortable, 73 new tradeoff

  • • Gemma 3 270M
  • • SmolLM2 135M Instruct
  • • SmolLM2 360M Instruct
  • • VBART Large (Turkish Summarization)
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: 80 new comfortable

  • • Qwen 3 30B-A3B
  • • Qwen 2.5 Coder 32B Instruct
  • • Qwen3.6 27B
  • • Llama 3.3 70B Instruct
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: 62 new comfortable

  • • Qwen 3 30B-A3B
  • • Qwen 2.5 Coder 32B Instruct
  • • Qwen3.6 27B
  • • Qwen 3 32B
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.

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