Raspberry Pi 5 16GB — Benchmarks & Specs
Bottom line: how fast is the Raspberry Pi 5 16GB?
SpecPicks median: 2.1 tokens/sec across 5 cited single-user runs of 7-9B dense models at 4-bit (Q4) under ollama (range 2.0–2.6 tok/s), from Local AI Master (2 runs), geerlingguy/ai-benchmarks (2 runs), It's FOSS. At 1080p Medium, the Raspberry Pi 5 16GB averages 61 fps in SuperTuxKart, per Raspberry Pi Forums. For local LLM inference it generates 1.4 tokens/sec running llama2:13b at q4_0 under ollama, per geerlingguy/ai-benchmarks. In 7-Zip Multi-Thread it scores 10,944 MIPS, per Electronics For You. It has 16 GB of memory shared by the CPU and GPU, and the largest model on file at 4-bit quantization on it is llama2:13b (13B parameters, Q4_0), generating 1.5 tokens/sec under ollama, per Jeff Geerling. Larger models have no sourced run on file.
Every figure above is a row in the tables below, and each row links out to the review or public benchmark database the number was taken from; the memory size is the on-paper spec; the SpecPicks median is computed here from the runs it names, each a row in the AI table. SpecPicks aggregates published measurements; it does not report first-party benchmark runs.
Read the full comparison → Best AI HATs for Raspberry Pi 5 in 2026
The Raspberry Pi 5 16GB is an APU from the Pi 5 family released in 2024 from Raspberry Pi. Key on-paper specs include 4 CPU cores, 16 GB of memory shared by the CPU and GPU, 17.1 GB/s of memory bandwidth. It launched with a $120 MSRP, though street prices typically diverge meaningfully from launch pricing. Data on this page draws on 17 synthetic benchmark results (top 10 shown), 36 community AI inference reports (top 18 shown), 3 measured game frame-rate results, compiled from Local AI Master, geerlingguy/ai-benchmarks, kunalganglani.com, Raspberry Pi Forums, Electronics For You, It's FOSS, Jeff Geerling, pi5-llm-arena, Raspberry Pi Foundation, WhyPi.org, CNX Software, dev.to, ohyaan.github.io, OpenClaw Pi OSS, PiMyLifeUp, Stratosphere Laboratory, Tom's Hardware; each table row links to its source. Read this page when shopping the Raspberry Pi 5 16GB, comparing it against other APUs in your build, or sizing it for a specific workload (gaming at 1080p/1440p/4K, synthetic benchmark scores, or local LLM inference).
Gaming Performance (measured FPS)
Average and 1% low frame rates by game, resolution, and quality preset. Bars are scaled against the fastest result on this page.
| Game | Resolution | Settings | Relative | Avg FPS | 1% low | Source |
|---|---|---|---|---|---|---|
| SuperTuxKart | 1080p | Medium | 61 fps | — | Raspberry Pi Forums 2023-11 | |
| Soulcalibur (Dreamcast via RetroArch lr-flycast) | 1080p | High | 60 fps | — | WhyPi.org 2023-11 | |
| OpenArena | 1080p | Medium | 27 fps | — | Raspberry Pi Foundation 2023-10-20 |
AI Inference Performance
Tokens per second under each model + quantization. Higher = faster generation. Bars compare runs across the same model.
| Model | Quantization | Relative | Tokens/sec | VRAM used | Source |
|---|---|---|---|---|---|
| gemma3:1b | q4_K_M ollama | 20.0 tok/s | 1.0 GB | kunalganglani.com 2026-04-12 | |
| qwen3:0.6b | q5_K_M ollama | 18.0 tok/s | 1.3 GB | OpenClaw Pi OSS (GitHub) 2026-03 | |
| llama3.2:1b | q4_K_M ollama | 17.2 tok/s | — | Local AI Master 2026-06 | |
| deepseek-r1:1.5b | — llama.cpp | 12.0 tok/s | 1.0 GB | pi5-llm-arena (GitHub) 2026-09-21 | |
| TinyLlama-1.1B-Chat-v1.0 | q4_K_M llama.cpp | 11.8 tok/s | 1.8 GB | ohyaan.github.io 2024-06 | |
| deepseek-r1:1.5b | q4_K_M ollama | 11.5 tok/s | — | pi5-llm-arena (GitHub) 2026-09-21 | |
| gemma2:2b | q4_K_M ollama | 11.3 tok/s | — | Local AI Master 2026-06 | |
| gemma4:e2b | q4_K_M ollama | 10.0 tok/s | — | dev.to (Alan West) 2026-04-06 | |
| gemma3:1b | q4_K_M ollama | 10.0 tok/s | 1.1 GB | kunalganglani.com 2026-04 | |
| gemma3:4b | q4_K_M ollama | 9.5 tok/s | 3.0 GB | kunalganglani.com 2026-04-12 | |
| llama3.2:3b | q4_K_M ollama | 8.8 tok/s | — | Local AI Master 2026-06 | |
| bitnet-b1.58-2b-4t | 1.58-bit ollama | 8.0 tok/s | — | Stratosphere Laboratory 2025-05-27 | |
| mistral:7b | q4_K_M ollama | 2.6 tok/s | — | Local AI Master 2026-06 | |
| llama3.1:8b | q4_K_M ollama | 2.2 tok/s | — | Jeff Geerling / geerlingguy ai-benchmarks GitHub 2025-01 | |
| llama3.1:8b | q4_K_M ollama | 2.1 tok/s | — | Local AI Master 2026-06 | |
| Mistral 7B | Q4 ollama | 2.0 tok/s | 5.0 GB | It's FOSS 2024-10-18 | |
| llama2:13b | Q4_0 ollama | 1.5 tok/s | — | Jeff Geerling 2025-01-09 | |
| llama2:13b | q4_0 ollama | 1.4 tok/s | — | Jeff Geerling / geerlingguy ai-benchmarks GitHub 2025-01 |
Synthetic Benchmarks
Higher is better. Bars are scaled within each benchmark family (multi-thread, single-thread, etc.) so you can compare like-with-like at a glance.
| Benchmark | Relative | Score | Source |
|---|---|---|---|
| 7-Zip Multi-Thread | 10,944 MIPS | Electronics For You 2023-11 | |
| Sysbench CPU | 2,730 events/sec | Electronics For You 2023-11 | |
| PassMark CPU Mark (multi-thread, stock 2.4GHz) | 2,226 CPU Mark | Raspberry Pi Forums / PassMark 2023-11-29 | |
| Geekbench 6 Multi-Core (post Dec-2024 firmware SDRAM tuning) | 2,164 points | Jeff Geerling / SBC Reviews 2024-12 | |
| Geekbench 6 multi-core | 2,144 points | Raspberry Pi Forums 2025-01-13 | |
| glmark2-es2-wayland | 2,036 points | CNX Software 2023-11-04 | |
| GLMark2 (Wayland/DRM) | 2,017 points | PiMyLifeUp 2023-11 | |
| GLMark2 (OpenGL ES) | 1,850 points | WhyPi.org 2026-01-24 | |
| Geekbench 6 Multi-Core | 1,604 points | Raspberry Pi Foundation 2023-10-23 | |
| Geekbench 6 multi | 1,584 points | Tom's Hardware 2025-01 |
Full Specifications
| Memory | 16 GB |
|---|---|
| CPU cores | 4 |
| Memory bandwidth | 17.1 GB/s |
Raspberry Pi 5 16GB — Frequently Asked Questions
What is the Raspberry Pi 5 16GB best used for?
When was the Raspberry Pi 5 16GB released, and what was its launch MSRP?
Where do the Raspberry Pi 5 16GB benchmark numbers come from?
How many cores does the Raspberry Pi 5 16GB have, and how does it benchmark?
Where can I buy the Raspberry Pi 5 16GB?
Buying guides that rank the Raspberry Pi 5 16GB's class
This page is the raw performance data. The guides below turn it into a ranked pick for a specific build.
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