What hardware do you need to run MiniCPM5 2B?
MiniCPM5 2B at Q4_K_M is 1.6 GB of weights, with a context ceiling of 128k tokens. The best score per gigabyte on this list: 13 on the index at 1.6 GB. On the cheapest machine that runs it, a Mac mini M6, 16GB, it generates 39 tok/s at 32k of context, worked out from memory bandwidth.
How good is MiniCPM5 2B, really?
On the Artificial Analysis Intelligence Index v4.3 it scores 13, which puts it in the Below every hosted tier band. Fine for simple, well-specified tasks. Noticeably less capable than anything the big labs sell today. See the whole table.
Head to head with its neighbours on the leaderboard: vs Qwen3 235B-A22B Instruct 2507 above it, vs Qwen3.5 4B below.
What MiniCPM5 2B costs either way
Nobody rents MiniCPM5 2B by the token. The closest hosted match, Granite 4.2 8B, costs $0.06 per million input tokens and $0.15 per million output (OpenRouter, cheapest active endpoint, checked 2026-10-29). Buying a machine only beats that if you use it hard enough, for long enough, that the hardware price divides down below the rental bill. What a million tokens costs each way puts the two prices side by side.
Machines that run MiniCPM5 2B
Every machine here holds it to 128k, this model's own ceiling, so the choice between them is speed and price rather than how much you can keep in the window.
| Machine | Price | Speed at 32k | Longest context | Pay-back | |
|---|---|---|---|---|---|
| Mac mini M6, 16GB | $899 | 39 tok/s estimated | 128k | Pays back in 81 years | Run the numbers |
| Strix Halo Framework Desktop, 32GB | $1,269 | 65 tok/s estimated | 128k | Pays back in 117 years | Run the numbers |
| MacBook Air M5 (13-inch), 16GB | $1,299 | 39 tok/s estimated | 128k | Pays back in 117 years | Run the numbers |
| AMD Radeon AI PRO R9700, 32GB | $1,299card only | 188 tok/s estimated | 128k | Pays back in 117 years | Run the numbers |
| MacBook Pro M5 (14-inch), 16GB | $1,999 | 39 tok/s estimated | 128k | Pays back in 180 years | Run the numbers |
| NVIDIA GeForce RTX 5090, 32GB | $1,999card only | 416 tok/s estimated | 128k | Pays back in 178 years | Run the numbers |
| Mac Studio M5 Max, 36GB | $2,499 | 116 tok/s estimated | 128k | Pays back in 221 years | Run the numbers |
| DGX Spark GB10 Grace Blackwell, 128GB | $4,699 | 69 tok/s estimated | 128k | Pays back in 435 years | Run the numbers |
All 56 machines on this site run it at 32k, not just the eight in the table. One table sets every machine against the others: price, the memory its GPU can use, what it holds and how long it takes to pay for itself.
One machine per family, cheapest first. Speeds are measured where a public benchmark exists and estimated from memory bandwidth otherwise; the calculator says which for any configuration. The longest context is the longest setting the calculator offers that the machine still holds this model at, cache included, and no machine is shown taking it past its own 128k limit. Each one opens the calculator on that machine at that length.
For scale, the calculator starts from 80 tok/s for a hosted API and times a local machine against it. 3 of the 8 above reach it, and the slowest is 39 tok/s.
The cheapest machine that runs it is sold with 16 GB. There is a page on what 16 GB runs, machine by machine: it names the 6 machines here sold at that size, and the 15 current models the roomiest of them holds at 32k, this one among them.
It fits in less memory than that: the smallest size here that runs it at 32k is 12 GB, on the GeForce RTX 3060, 12GB at $329, card only, which hands a model 11 GB and is no longer sold.
Run MiniCPM5 2B at 128k on the Mac mini M6, 16GB
How much memory does MiniCPM5 2B need at 128k?
Every figure above is priced at 32k of context. At 128k, this model's own ceiling, MiniCPM5 2B needs 7.2 GB rather than 3 GB. The weights are the same either way; the key-value cache goes from 1.4 GB to 5.6 GB.
The window costs nothing in hardware: all 37 machines here still sold at a published price hold MiniCPM5 2B at both lengths, and the cheapest of them is the Mac mini M6, 16GB at $899.
On the Mac mini M6, 16GB it runs 39 tok/s estimated at 32k and 16 tok/s estimated at 128k. Every token generated reads the whole cache back, so a longer window is slower as well as bigger.
The specifics
- Parameters
- 2.5B
- Quantisation
- Q4_K_M
- Weights on disk
- 1.6 GB
- KV cache
- 1.4 GB at 32k context — Standard grouped-query attention, 16 query heads to 2 KV heads. How weights and cache add up.
- Maximum context
- 128k tokens
- Licence
- Apache 2.0
- Sources
- openbmb/MiniCPM5-2B, openbmb/MiniCPM5-2B-GGUF