AesCode-32B on local hardware
Estimated comfort for repository coding with Aider on a MacBook Pro M4 Pro 48GB.
AesCode-32BOpen source
microsoft · apache-2.0 · 946 downloads
Vision
- Parameters
- 33B exact
- Context window
- 256K tokens
- Attention
- Standard (full attention)
- Layers · KV heads · head dim
- 64 · 8 · 128
- KV cache
- 256 KB/token · 8.0 GB at 32K
- Tool calling
- good (from chat template)
- Thinking
- basic (from chat template)
- Vision
- good (from config)
- Commercial use
- allowedRetain the required license and attribution notices
- Import confidence
- medium · capabilities estimated
Weights by quantization
Q3_K_M
15 GB
gguf file size
Q4_K_M
19 GB
gguf file size
Q5_K_M
22 GB
gguf file size
Q6_K
26 GB
gguf file size
Q8_0
32 GB
gguf file size
F16 / BF16
61 GB
gguf file size
- • vision: good, inferred from config (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.
AesCode-32B — 5-bit
Borderline for your workload
Speed
6–8 tok/s
Too slow
Memory left
5.5 GB
of 48 GB
First word in
≈3 min
Too slow
All the details
- Your setup
- MacBook Pro M4 Pro 48 GB
- Workload
- Repository coding with Aider
- Runtime → tool
- LM Studio → Aider
- Memory used
- 31 GB
- Context
- 32K · no size is practical here
- Tool support
- Official
- Use-case fit
- Well suited
Why?
- LM Studio supports hardware acceleration on this machine (Metal (Apple GPU)).
- Aider can connect to LM Studio (officially supported).
- Good coding capability for interactive coding.
- Only ≈5.5 GB of memory headroom remains for the OS, IDE, browser, terminal and agent.
- 32K window; generation drops to 5–7 tok/s when it is full.
- Generation (6–8 tok/s) is slow for interactive coding.
- Ingesting a prompt of 14K tokens takes ≈3 min and each step ≈2 min; across ~4 calls a task takes ≈13 min.
Why “Borderline” rather than “Acceptable”?
- Prompt processing: Ingesting the first prompt (14K tokens) takes ≈3 min; each of the ~4 follow-up turns takes ≈2 min (≈13 min per task).
- Generation: Expected 6–8 tok/s at ~16K tokens of context. Coding with repository context is comfortable from about 28 tok/s.
- Context: 32K window; generation drops to 5–7 tok/s when it is full.
- Memory: Estimated peak ≈42 GB of 48 GB; ≈5.5 GB remains for the OS, IDE, browser, terminal and your coding agent to grow into.
How sure are we?
Medium confidenceEstimated 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