HelpingAI 15B i1 needs ~14.5 GB VRAM. RTX A5500 24GB has 24.0 GB. With Q4_K_M quantization, expect ~66 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
65.5 tok/s
TTFT
2957 ms
Safe context
102K
Memory
14.5 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 | 65.5 tok/s | 1613 ms | 102K |
| Coding | C | Runs well | 65.5 tok/s | 2957 ms | 102K |
| Agentic Coding | C | Runs well | 65.5 tok/s | 4301 ms | 102K |
| Reasoning | C | Runs well | 65.5 tok/s | 3495 ms | 102K |
| RAG | C | Runs well | 65.5 tok/s | 5377 ms | 102K |
How HelpingAI 15B i1 (15B params) fits at each quantization level on RTX A5500 24GB (24.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.9 GB | Low | C46 |
Q3_K_S | 3 | 7.4 GB | Low | C46 |
NVFP4 | 4 | 8.4 GB | Medium | C47 |
Q4_K_M | 4 | 9.2 GB | Medium | C48 |
Q5_K_M | 5 | 10.8 GB | High | C49 |
Q6_K | 6 | 12.3 GB | High | C50 |
Q8_0Best for your GPU | 8 | 16.1 GB | Very High | C49 |
F16 | 16 | 30.7 GB | Maximum | F0 |
Copy-paste commands to run HelpingAI 15B i1 on your machine.
Run
lms load hf-mradermacher--helpingai-15b-i1-gguf && lms server startYes, RTX A5500 24GB can run HelpingAI 15B i1 with a C grade (Runs well). Expected decode speed: 65.5 tok/s.
HelpingAI 15B i1 (15B parameters) requires approximately 14.5 GB of memory with Q4_K_M quantization.
The recommended quantization for HelpingAI 15B i1 is Q4_K_M, which balances quality and memory efficiency.
On RTX A5500 24GB, HelpingAI 15B i1 achieves approximately 65.5 tokens per second decode speed with a time-to-first-token of 2957ms using Q4_K_M quantization.
For coding workloads, HelpingAI 15B i1 on RTX A5500 24GB receives a C grade with 65.5 tok/s and 102K context.
On RTX A5500 24GB, HelpingAI 15B i1 can safely use up to 102K 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-mradermacher--helpingai-15b-i1-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>
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