Baichuan M2 32B Q4 K M needs ~29.3 GB VRAM. NVIDIA L40 48GB has 48.0 GB. With Q4_K_M quantization, expect ~35 tok/s.
Operating mode
Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Select quantization to explore
Fit status
Runs well
Decode
34.5 tok/s
TTFT
5608 ms
Safe context
96K
Memory
29.3 GB / 48.0 GB
This setup is broadly balanced for this model.
No major red flags
This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Runs well | 34.5 tok/s | 3059 ms | 96K |
| Coding | C | Runs well | 34.5 tok/s | 5608 ms | 96K |
| Agentic Coding | C | Runs well | 34.5 tok/s | 8157 ms | 96K |
| Reasoning | C | Runs well | 34.5 tok/s | 6627 ms | 96K |
| RAG | C | Runs well | 34.5 tok/s | 10196 ms | 96K |
How Baichuan M2 32B Q4 K M (32B params) fits at each quantization level on NVIDIA L40 48GB (48.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 12.5 GB | Low | C43 |
Q3_K_S | 3 | 15.7 GB | Low | C44 |
NVFP4 | 4 |
Copy-paste commands to run Baichuan M2 32B Q4 K M on your machine.
Run
lms load hf-baichuan-inc--baichuan-m2-32b-q4-k-m-gguf && lms server startYes, NVIDIA L40 48GB can run Baichuan M2 32B Q4 K M with a C grade (Runs well). Expected decode speed: 34.5 tok/s.
Baichuan M2 32B Q4 K M (32B parameters) requires approximately 29.3 GB of memory with Q4_K_M quantization.
The recommended quantization for Baichuan M2 32B Q4 K M is Q4_K_M, which balances quality and memory efficiency.
On NVIDIA L40 48GB, Baichuan M2 32B Q4 K M achieves approximately 34.5 tokens per second decode speed with a time-to-first-token of 5608ms using Q4_K_M quantization.
For coding workloads, Baichuan M2 32B Q4 K M on NVIDIA L40 48GB receives a C grade with 34.5 tok/s and 96K context.
On NVIDIA L40 48GB, Baichuan M2 32B Q4 K M can safely use up to 96K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/hf-baichuan-inc--baichuan-m2-32b-q4-k-m-gguf-on-l40-48gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
17.9 GB |
| Medium |
| C45 |
Q4_K_M | 4 | 19.5 GB | Medium | C46 |
Q5_K_M | 5 | 23.0 GB | High | C47 |
Q6_K | 6 | 26.2 GB | High | C48 |
Q8_0Best for your GPU | 8 | 34.2 GB | Very High | C47 |
F16 | 16 | 65.6 GB | Maximum | F0 |