RX 7600 XT 16GBBudget pick
16 GB VRAM (+8)
C
Raises estimated decode speed by about 39%.30.4 tok/s decode
Raises estimated decode speed by about 39%.
Adds memory headroom for longer context windows and future model growth.
~$329 MSRP
HelpingAI 9B 200k i1 needs ~8.2 GB VRAM. Radeon RX 7700S 8GB has 8.0 GB. With Q4_K_M quantization, expect ~22 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
21.8 tok/s
TTFT
8886 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 | 31.0 tok/s | 3412 ms | 12K |
| Coding | C | Runs with offload (needs ~0.2 GB host RAM) | 21.8 tok/s | 8886 ms | 12K |
| Agentic Coding | D | Very compromised (needs ~0.8 GB host RAM) | 16.9 tok/s | 16653 ms | 12K |
| Reasoning | C | Runs with offload (needs ~0.2 GB host RAM) | 21.8 tok/s | 10502 ms | 12K |
| RAG | D | Very compromised (needs ~0.8 GB host RAM) | 16.9 tok/s |
How HelpingAI 9B 200k i1 (9B params) fits at each quantization level on Radeon RX 7700S 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 |
Copy-paste commands to run HelpingAI 9B 200k i1 on your machine.
Run
lms load hf-mradermacher--helpingai-9b-200k-i1-gguf && lms server startUpgrade options
Raises estimated decode speed by about 39%.
Adds memory headroom for longer context windows and future model growth.
~$329 MSRP
Raises estimated decode speed by about 68%.
Adds memory headroom for longer context windows and future model growth.
~$349 MSRP
Raises estimated decode speed by about 117%.
Adds memory headroom for longer context windows and future model growth.
~$449 MSRP
Yes, Radeon RX 7700S 8GB can run HelpingAI 9B 200k i1 with a C grade (Runs with offload (needs ~0.2 GB host RAM)). Expected decode speed: 21.8 tok/s.
HelpingAI 9B 200k i1 (9B parameters) requires approximately 8.2 GB of memory with Q4_K_M quantization.
The recommended quantization for HelpingAI 9B 200k i1 is Q4_K_M, which balances quality and memory efficiency.
On Radeon RX 7700S 8GB, HelpingAI 9B 200k i1 achieves approximately 21.8 tokens per second decode speed with a time-to-first-token of 8886ms using Q4_K_M quantization.
For coding workloads, HelpingAI 9B 200k i1 on Radeon RX 7700S 8GB receives a C grade with 21.8 tok/s and 12K context.
On Radeon RX 7700S 8GB, HelpingAI 9B 200k i1 can safely use up to 12K 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-200k-i1-gguf-on-rx-7700s-8gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
| 20816 ms |
| 12K |
| 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 |
Buy headroom, not only minimum fit. A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.