Kimi Linear 48B A3B needs ~35.0 GB but NVIDIA A10 24GB only has 24.0 GB. Try a smaller quantization or lighter model.
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
11.0 GB over capacity — needs offload or smaller quantization
Fit status
Too heavy
Decode
4.3 tok/s
TTFT
44687 ms
Safe context
4K
Memory
35.0 GB / 24.0 GB
Offload
30%
Usable VRAM is the main blocker for this model.
Not enough usable memory
The model needs 35.0 GB, but this setup only exposes 24.0 GB of usable VRAM.
Add more VRAM headroom
The first useful upgrade is more dedicated VRAM so you can fit the model without shrinking context or dropping to a much lower quant.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | F | Too heavy | 4.5 tok/s | 23700 ms | 4K |
| Coding | F | Too heavy | 4.3 tok/s | 44687 ms | 4K |
| Agentic Coding | F | Too heavy | 4.1 tok/s | 68675 ms | 4K |
| Reasoning | F | Too heavy | 4.3 tok/s | 52812 ms | 4K |
| RAG | F | Too heavy | 4.1 tok/s | 85844 ms | 4K |
How Kimi Linear 48B A3B (48B params) fits at each quantization level on NVIDIA A10 24GB (24.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 18.7 GB | Low | F0 |
Q3_K_S | 3 | 23.5 GB | Low | F0 |
NVFP4 | 4 | 26.9 GB | Medium | F0 |
Q4_K_M | 4 | 29.3 GB | Medium | F0 |
Q5_K_M | 5 | 34.6 GB | High | F0 |
Q6_K | 6 | 39.4 GB | High | F0 |
Q8_0 | 8 | 51.4 GB | Very High | F0 |
F16 | 16 | 98.4 GB | Maximum | F0 |
Upgrade options
RTX A6000 48GBBudget pickMakes the model fit on the accelerator instead of staying completely out of reach.
Removes host-memory offload, which is usually the single biggest latency and throughput win.
~$4,650 MSRP
RTX PRO 5000 Blackwell 48GBBest valueMakes the model fit on the accelerator instead of staying completely out of reach.
Removes host-memory offload, which is usually the single biggest latency and throughput win.
~$4,999 MSRP
NVIDIA L40 48GBNVIDIA upgradeMakes the model fit on the accelerator instead of staying completely out of reach.
Removes host-memory offload, which is usually the single biggest latency and throughput win.
~$5,500 MSRP
No, Kimi Linear 48B A3B requires more memory than NVIDIA A10 24GB provides.
Kimi Linear 48B A3B (48B parameters) requires approximately 35.0 GB of memory with Q4_K_M quantization.
The recommended quantization for Kimi Linear 48B A3B is Q4_K_M, which balances quality and memory efficiency.
On NVIDIA A10 24GB, Kimi Linear 48B A3B achieves approximately 4.3 tokens per second decode speed with a time-to-first-token of 44687ms using Q4_K_M quantization.
For coding workloads, Kimi Linear 48B A3B on NVIDIA A10 24GB receives a F grade with 4.3 tok/s and 4K context.
On NVIDIA A10 24GB, Kimi Linear 48B A3B can safely use up to 4K tokens of context. The model's official context limit is 1.0M, but available memory constrains the safe maximum.
Add more VRAM headroom. The first useful upgrade is more dedicated VRAM so you can fit the model without shrinking context or dropping to a much lower quant.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/kimi-linear-48b-a3b-on-a10-24gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
