HelpingAI2 9B needs ~10.1 GB VRAM. RTX A5500 24GB has 24.0 GB. With Q4_K_M quantization, expect ~109 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
109.1 tok/s
TTFT
1774 ms
Safe context
226K
Memory
10.1 GB / 24.0 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 | 109.1 tok/s | 968 ms | 226K |
| Coding | C | Runs well | 109.1 tok/s | 1774 ms | 226K |
| Agentic Coding | C | Runs well | 109.1 tok/s | 2581 ms | 226K |
| Reasoning | C | Runs well | 109.1 tok/s | 2097 ms | 226K |
| RAG | C | Runs well | 109.1 tok/s | 3226 ms | 226K |
How HelpingAI2 9B (9B params) fits at each quantization level on RTX A5500 24GB (24.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | C44 |
Q3_K_S | 3 | 4.4 GB | Low | C45 |
NVFP4 | 4 |
Copy-paste commands to run HelpingAI2 9B on your machine.
Run
lms load hf-bartowski--helpingai2-9b-gguf && lms server startYes, RTX A5500 24GB can run HelpingAI2 9B with a C grade (Runs well). Expected decode speed: 109.1 tok/s.
HelpingAI2 9B (9B parameters) requires approximately 10.1 GB of memory with Q4_K_M quantization.
The recommended quantization for HelpingAI2 9B is Q4_K_M, which balances quality and memory efficiency.
On RTX A5500 24GB, HelpingAI2 9B achieves approximately 109.1 tokens per second decode speed with a time-to-first-token of 1774ms using Q4_K_M quantization.
For coding workloads, HelpingAI2 9B on RTX A5500 24GB receives a C grade with 109.1 tok/s and 226K context.
On RTX A5500 24GB, HelpingAI2 9B can safely use up to 226K 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-bartowski--helpingai2-9b-gguf-on-rtx-a5500-24gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
5.0 GB |
| Medium |
| C45 |
Q4_K_M | 4 | 5.5 GB | Medium | C45 |
Q5_K_M | 5 | 6.5 GB | High | C46 |
Q6_K | 6 | 7.4 GB | High | C46 |
Q8_0 | 8 | 9.6 GB | Very High | C48 |
F16Best for your GPU | 16 | 18.5 GB | Maximum | C49 |