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UNIT · AMD · GPU
8 GB VRAMhigh·Reviewed May 2026

AMD Radeon RX 5700 XT

RDNA 1 flagship. ROCm support was always experimental and is effectively defunct in 2026. Vulkan via llama.cpp is the only operator-grade path; performance is bandwidth-OK but lacks the matrix cores newer cards have. ~25-40 tok/s on 7B Q4. The card the 'I bought AMD before AI mattered' audience owns.

Released 2019·~$200 street·448 GB/s memory bandwidth
RUNLOCALAI SCORE
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214/ 1000
DD-tier
Estimated
Throughput
130/ 500
VRAM-fit
80/ 200
Ecosystem
80/ 200
Efficiency
16/ 100

Extrapolated from 448 GB/s bandwidth — 44.8 tok/s estimated. No measured benchmarks yet.

WORKLOAD FIT
Try other hardware →

Plain-English: Comfortable for 7B chat.

7B chat✓
Comfortable
14B chat✗
Doesn't fit
32B chat✗
Doesn't fit
70B chat✗
Doesn't fit
Coding agent✗
Doesn't fit
Vision (≤8B VLM)△
Marginal
Long context (32K)✗
Doesn't fit
✓Comfortable — fits with headroom
~Tight — works, no slack
△Marginal — needs aggressive quant
✗Doesn't fit usefully

Verdicts extrapolated from catalog VRAM + bandwidth + ecosystem flags. Hover any chip for the rationale. Want measured numbers? Submit your own run with runlocalai-bench --submit.

BLK · VERDICT

Our verdict

OP · Fredoline Eruo|VERIFIED MAY 10, 2026
3.5/10

This card is for the operator who already owns it from a gaming build and wants to dip a toe into local inference without spending more money. It is not for anyone buying a GPU today for local AI. On 7B Q4 models via Vulkan in llama.cpp, expect 25-40 tok/s—usable for chat but not for real-time streaming. 13B Q4 models (8.5 GB weights) barely fit in 8 GB VRAM, yielding ~15-25 tok/s with heavy system RAM spillover. 30B models are out of reach entirely. The lack of ROCm and CUDA means no access to exllama, AutoGPTQ, or any optimized inference stack; Vulkan is the only path and lags in features and performance. Pass on this card if you are buying a GPU for local AI today—an RTX 3060 12 GB offers CUDA, more VRAM, and similar speed for ~$50 more used. At $200 used, it is a budget option only for the AMD-curious who already have the card; otherwise, skip it.

›Why this rating

The RX 5700 XT is usable for small models via Vulkan but lacks CUDA/ROCm, limiting software compatibility and future-proofing. Its 8 GB VRAM is tight for 13B models, and performance is mediocre. Only worth considering if acquired cheaply from an existing build.

BLK · OVERVIEW

Overview

RDNA 1 flagship. ROCm support was always experimental and is effectively defunct in 2026. Vulkan via llama.cpp is the only operator-grade path; performance is bandwidth-OK but lacks the matrix cores newer cards have. ~25-40 tok/s on 7B Q4. The card the 'I bought AMD before AI mattered' audience owns.

Retailers we'd check:Amazon

Search-fallback links. Editorial hasn't yet curated retailer URLs for this card. Approx. $200.

Some links above are affiliate links. We may earn a commission at no extra cost to you. How we make money.

BLK · SPECS

Specs

VRAM8 GB
Power draw225 W
Released2019
MSRP$399
Backends
Vulkan

Models that fit

Open-weight models small enough to run on AMD Radeon RX 5700 XT with usable context.

Llama 3.2 3B Instruct
3B · llama
Gemma 4 E4B (Effective 4B)
4B · gemma
Qwen 3 4B
4B · qwen
Phi-3.5 Mini Instruct
3.8B · phi
Llama 3.2 1B Instruct
1B · llama
Gemma 3 4B
4B · gemma
Gemma 4 E2B (Effective 2B)
2B · gemma
Phi-3.5 Vision
4.2B · phi

Frequently asked

What models can AMD Radeon RX 5700 XT run?

With 8GB VRAM, the AMD Radeon RX 5700 XT runs 7B models comfortably in Q4 quantization. See the model list below for tested combinations.

Does AMD Radeon RX 5700 XT support CUDA?

AMD Radeon RX 5700 XT does not support CUDA. Use Vulkan-compatible tools (llama.cpp Vulkan backend) or check vendor-specific runtimes.

How much does AMD Radeon RX 5700 XT cost?

Current street price for AMD Radeon RX 5700 XT is around $200 (MSRP $399). Prices vary by region and supply.

Where next?

Buyer guides
  • Best GPU for local AI →
  • Best laptop for local AI →
  • Best Mac for local AI →
  • Best used GPU for local AI →
Troubleshooting
  • CUDA out of memory →
  • Ollama running slowly →
  • ROCm not detected →
  • Model keeps crashing →

Reviewed by RunLocalAI Editorial. See our editorial policy for how we research and verify hardware specifications.

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DISCLOSURE

Some links on this site are affiliate links (Amazon Associates and other first-class retailers). When you buy through them, we earn a small commission at no extra cost to you. Affiliate links do not influence our verdicts — there are cards we rate highly that we don't have affiliate relationships with, and cards that sell well that we refuse to recommend. Read more →

SYS · ONLINEUPTIME · 100%2026 · operator-owned
RUNLOCALAI · v38
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