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UNIT · AMD · GPU
entry·Reviewed May 2026

AMD Radeon 780M (Phoenix iGPU)

AMD · HARDWARE
AMD Radeon 780M (Phoenix iGPU)

No editorial image yet — generic vendor mark shown. Credentials in spec table below.

AMD's 780M iGPU (Ryzen 7040/8040 series Phoenix). Shares system RAM via unified memory architecture; 32 GB DDR5 system gives effective 16-20 GB usable for inference. Bandwidth (89 GB/s) is the bottleneck — ~6-12 tok/s on 7B Q4. The 'I have a thin laptop' audience can run AI but slowly.

Released 2023·89 GB/s memory bandwidth
RUNLOCALAI SCORE
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127/ 1000
DD-tier
Estimated
Throughput
26/ 500
VRAM-fit
0/ 200
Ecosystem
130/ 200
Efficiency
25/ 100

Sub-scores sum to 181 / 1000. Headline = 181 × 0.70 (Estimated-confidence discount) = 127. This is an algorithmic performance-tier score — distinct from, and often lower than, the editorial “Our verdict” below, which weighs value and real-world fit (especially for hardware we haven’t measured yet). How scoring works →

Extrapolated from 89 GB/s bandwidth — 8.9 tok/s estimated. No measured benchmarks yet.

WORKLOAD FIT
Try other hardware →

Plain-English: Doesn't fit modern chat models usefully — vision models won't fit.

7B chat✗
Doesn't fit
14B chat✗
Doesn't fit
32B chat✗
Doesn't fit
70B chat✗
Doesn't fit
Coding agent✗
Doesn't fit
Vision (≤8B VLM)✗
Doesn't fit
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 · Eruo Fredoline|VERIFIED MAY 10, 2026
2.1/10

This card is for the operator who already owns a Ryzen 7040/8040 laptop and wants to experiment with local AI without buying a discrete GPU. It runs 7B Q4 models at 6-12 tok/s — usable for chat but too slow for real-time interaction. 13B models dip to ~3-5 tok/s, and anything larger is impractical. The shared memory architecture means the system RAM (ideally 32 GB) is split between GPU and OS, leaving ~16-20 GB for models. What breaks: any model above 13B, any workload requiring sustained throughput, and ROCm support on iGPUs is still rough — expect manual setup and limited compatibility. Pass if you need interactive speeds or plan to run models larger than 7B; a used RTX 3060 12GB will cost ~$200 and deliver 5-10x the performance. Price/value note: the 780M is free with the CPU, so its value is purely incremental — if you already have the laptop, it's a bonus, not a reason to buy.

›Why this rating

The 780M is a capable iGPU for casual local AI experimentation, but its shared memory and low bandwidth severely limit model size and speed. It earns a 3.0 for being a free add-on that can run small models, but it's not a primary inference card.

BLK · OVERVIEW

Overview

AMD's 780M iGPU (Ryzen 7040/8040 series Phoenix). Shares system RAM via unified memory architecture; 32 GB DDR5 system gives effective 16-20 GB usable for inference. Bandwidth (89 GB/s) is the bottleneck — ~6-12 tok/s on 7B Q4. The 'I have a thin laptop' audience can run AI but slowly.

Retailers we'd check:Amazon

Search-fallback link — editorial hasn't yet curated a retailer URL for this card.

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

BLK · SPECS

Specs

VRAM0 GB
Power draw (peak)28 W
Released2023
Backends
ROCm
Vulkan

Frequently asked

Does AMD Radeon 780M (Phoenix iGPU) support CUDA?

No — AMD Radeon 780M (Phoenix iGPU) is an AMD card. Use ROCm (Linux) or the Vulkan backend in llama.cpp instead. CUDA-only tools won't work.

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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OP·Eruo Fredoline
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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 →

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RUNLOCALAI · v38
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