~$2,499 MSRP
HelpingAI2.5 5B i1 needs ~6.9 GB VRAM. RTX 4090 24GB has 24.0 GB. With Q4_K_M quantization, expect ~80 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
80.0 tok/s
TTFT
2420 ms
Safe context
482K
Memory
6.9 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 | 80.0 tok/s | 1320 ms | 482K |
| Coding | C | Runs well | 80.0 tok/s | 2420 ms | 482K |
| Agentic Coding | C | Runs well | 80.0 tok/s | 3520 ms | 482K |
| Reasoning | C | Runs well | 80.0 tok/s | 2860 ms | 482K |
| RAG | C | Runs well | 80.0 tok/s | 4400 ms | 482K |
How HelpingAI2.5 5B i1 (5B params) fits at each quantization level on RTX 4090 24GB (24.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.0 GB | Low | C44 |
Q3_K_S | 3 | 2.5 GB | Low | C44 |
NVFP4 | 4 |
Copy-paste commands to run HelpingAI2.5 5B i1 on your machine.
Run
lms load hf-mradermacher--helpingai2-5-5b-i1-gguf && lms server startUpgrade options
Yes, RTX 4090 24GB can run HelpingAI2.5 5B i1 with a C grade (Runs well). Expected decode speed: 80.0 tok/s.
HelpingAI2.5 5B i1 (5B parameters) requires approximately 6.9 GB of memory with Q4_K_M quantization.
The recommended quantization for HelpingAI2.5 5B i1 is Q4_K_M, which balances quality and memory efficiency.
On RTX 4090 24GB, HelpingAI2.5 5B i1 achieves approximately 80.0 tokens per second decode speed with a time-to-first-token of 2420ms using Q4_K_M quantization.
For coding workloads, HelpingAI2.5 5B i1 on RTX 4090 24GB receives a C grade with 80.0 tok/s and 482K context.
On RTX 4090 24GB, HelpingAI2.5 5B i1 can safely use up to 482K 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--helpingai2-5-5b-i1-gguf-on-rtx-4090-24gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
2.8 GB |
| Medium |
| C44 |
Q4_K_M | 4 | 3.1 GB | Medium | C44 |
Q5_K_M | 5 | 3.6 GB | High | C44 |
Q6_K | 6 | 4.1 GB | High | C44 |
Q8_0 | 8 | 5.4 GB | Very High | C45 |
F16Best for your GPU | 16 | 10.3 GB | Maximum | C48 |