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OP·Eruo Fredoline
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RUNLOCALAI · v38
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  4. /AMD Radeon 780M (Phoenix iGPU)
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
See full leaderboard →
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.

Compare alternatives

Hardware worth comparing

The closest alternatives by price, memory bandwidth, and form factor, plus a step up and down — so you can frame the buying decision against real options.

Closest matches
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Step up
More capable — more memory or a higher tier
  • Apple Mac Mini (M4)
    apple · 120 GB/s
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Step down
Lighter — cheaper or more constrained
No verdicted hardware in the next tier down yet.