Local AI Advisor

MiniCPM5-2B on local hardware

Estimated comfort for repository coding with Aider on a MacBook Pro M4 Pro 48GB.

MiniCPM5-2BOpen source

openbmb · apache-2.0 · 1,320,660 downloads

Hugging Face
Reasoning / thinking mode
Parameters
2.5B exact
Context window
128K tokens
Attention
Standard (full attention)
Layers · KV heads · head dim
42 · 2 · 128
KV cache
42 KB/token · 1.3 GB at 32K
Tool calling
good (from chat template)
Thinking
good (from chat template)
Vision
basic (inferred — no supporting signal)
Commercial use
allowedRetain the required license and attribution notices
Import confidence
medium · capabilities estimated

Weights by quantization

Q3_K_M

1.2 GB

gguf file size

Q4_K_M

1.5 GB

gguf file size

Q5_K_M

1.8 GB

gguf file size

Q6_K

2.0 GB

gguf file size

Q8_0

2.5 GB

gguf file size

F16 / BF16

4.7 GB

gguf file size

  • • vision: basic, inferred from missing signals (low confidence).
  • • Capability ratings are estimated from model size and name — this model hasn't been assessed by hand.
  • • GGUF sizes come from community conversions matched by model name; equivalence and runtime support are not verified. MLX conversion availability is unverified.

MiniCPM5-2B — 6-bit

Technically Runs for your workload

Technically Runs

Speed

60–80 tok/s

Excellent

Memory left

32 GB

of 48 GB

First word in

≈15 s

Excellent

All the details
Your setup
MacBook Pro M4 Pro 48 GB
Workload
Repository coding with Aider
Runtime → tool
LM Studio → Aider
Memory used
4.2 GB
Context
32K · up to 128K practical
Tool support
Official
Use-case fit
Poorly suited

Why?

  • Model fits with approximately 32 GB of memory headroom.
  • LM Studio supports hardware acceleration on this machine (Metal (Apple GPU)).
  • Aider can connect to LM Studio (officially supported).
  • Generation (60–80 tok/s) should be appropriate for interactive coding.
  • Ingesting a prompt of 14K tokens takes ≈15 s; prompt processing keeps up with interactive coding.
  • 32K working context is reasonable.
  • Weak coding capability for interactive coding.

Why “Technically Runs” rather than “Borderline”?

  • Workload suitability: Weak coding capability for interactive coding.

How sure are we?

Medium confidence

Estimated from bandwidth and compute, calibrated against 2 verified benchmarks of other models on this same chip (measured with a different engine, so calibration is partial).

  • Calibrated with verified benchmarks of other models on this chip.
Medium confidence
Check with your hardware and workload