HelpingAI 9B i1 needs ~9.0 GB VRAM. RX 6800 16GB has 16.0 GB. With Q4_K_M quantization, expect ~51 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
51.3 tok/s
TTFT
3774 ms
Safe context
122K
Memory
9.0 GB / 16.0 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 | 51.3 tok/s | 2059 ms | 122K |
| Coding | C | Runs well | 51.3 tok/s | 3774 ms | 122K |
| Agentic Coding | C | Runs well | 51.3 tok/s | 5490 ms | 122K |
| Reasoning | C | Runs well | 51.3 tok/s | 4461 ms | 122K |
| RAG | C | Runs well | 51.3 tok/s | 6863 ms | 122K |
How HelpingAI 9B i1 (9B params) fits at each quantization level on RX 6800 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | C47 |
Q3_K_S | 3 | 4.4 GB | Low | C48 |
NVFP4 | 4 |
Copy-paste commands to run HelpingAI 9B i1 on your machine.
Run
lms load hf-mradermacher--helpingai-9b-i1-gguf && lms server startYes, RX 6800 16GB can run HelpingAI 9B i1 with a C grade (Runs well). Expected decode speed: 51.3 tok/s.
HelpingAI 9B i1 (9B parameters) requires approximately 9.0 GB of memory with Q4_K_M quantization.
The recommended quantization for HelpingAI 9B i1 is Q4_K_M, which balances quality and memory efficiency.
On RX 6800 16GB, HelpingAI 9B i1 achieves approximately 51.3 tokens per second decode speed with a time-to-first-token of 3774ms using Q4_K_M quantization.
For coding workloads, HelpingAI 9B i1 on RX 6800 16GB receives a C grade with 51.3 tok/s and 122K context.
On RX 6800 16GB, HelpingAI 9B i1 can safely use up to 122K 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-9b-i1-gguf-on-rx-6800-16gb" 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 |
| C48 |
Q4_K_M | 4 | 5.5 GB | Medium | C49 |
Q5_K_M | 5 | 6.5 GB | High | C50 |
Q6_K | 6 | 7.4 GB | High | C51 |
Q8_0Best for your GPU | 8 | 9.6 GB | Very High | C51 |
F16 | 16 | 18.5 GB | Maximum | F0 |