HelpingAI2 9B needs ~8.2 GB VRAM. Radeon Pro W7500 8GB has 8.0 GB. With Q4_K_M quantization, expect ~17 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
0.2 GB over capacity — needs offload or smaller quantization
Fit status
Runs with offload (needs ~0.2 GB host RAM)
Decode
16.9 tok/s
TTFT
11425 ms
Safe context
12K
Memory
8.2 GB / 8.0 GB
This setup is broadly balanced for this model.
Very little memory headroom
You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Runs with offload | 24.1 tok/s | 4387 ms | 12K |
| Coding | C | Runs with offload (needs ~0.2 GB host RAM) | 16.9 tok/s | 11425 ms | 12K |
| Agentic Coding | D | Very compromised (needs ~0.8 GB host RAM) | 13.2 tok/s | 21411 ms | 12K |
| Reasoning | C | Runs with offload (needs ~0.2 GB host RAM) | 16.9 tok/s | 13502 ms | 12K |
| RAG | D | Very compromised (needs ~0.8 GB host RAM) | 13.2 tok/s | 26764 ms | 12K |
How HelpingAI2 9B (9B params) fits at each quantization level on Radeon Pro W7500 8GB (8.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | C53 |
Q3_K_S | 3 | 4.4 GB | Low | C53 |
NVFP4Best for your GPU | 4 | 5.0 GB | Medium | C52 |
Q4_K_M | 4 | 5.5 GB | Medium | F0 |
Q5_K_M | 5 | 6.5 GB | High | F0 |
Q6_K | 6 | 7.4 GB | High | F0 |
Q8_0 | 8 | 9.6 GB | Very High | F0 |
F16 | 16 | 18.5 GB | Maximum | F0 |
Copy-paste commands to run HelpingAI2 9B on your machine.
Run
lms load hf-bartowski--helpingai2-9b-gguf && lms server startOpciones de mejora
Sube la velocidad estimada de decodificación alrededor de un 80%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$329 MSRP
Sube la velocidad estimada de decodificación alrededor de un 117%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$349 MSRP
Sube la velocidad estimada de decodificación alrededor de un 179%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$449 MSRP
Yes, Radeon Pro W7500 8GB can run HelpingAI2 9B with a C grade (Runs with offload (needs ~0.2 GB host RAM)). Expected decode speed: 16.9 tok/s.
HelpingAI2 9B (9B parameters) requires approximately 8.2 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 Radeon Pro W7500 8GB, HelpingAI2 9B achieves approximately 16.9 tokens per second decode speed with a time-to-first-token of 11425ms using Q4_K_M quantization.
For coding workloads, HelpingAI2 9B on Radeon Pro W7500 8GB receives a C grade with 16.9 tok/s and 12K context.
On Radeon Pro W7500 8GB, HelpingAI2 9B can safely use up to 12K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
Buy headroom, not only minimum fit. A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/hf-bartowski--helpingai2-9b-gguf-on-radeon-pro-w7500-8gb" 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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