Yi 9B Coder i1 needs ~8.6 GB VRAM. RX 7700 XT 12GB has 12.0 GB. With Q4_K_M quantization, expect ~47 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
47.2 tok/s
TTFT
4101 ms
Safe context
67K
Memory
8.6 GB / 12.0 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 | 47.2 tok/s | 2237 ms | 67K |
| Coding | C | Runs well | 47.2 tok/s | 4101 ms | 67K |
| Agentic Coding | C | Runs well | 47.2 tok/s | 5964 ms | 67K |
| Reasoning | C | Runs well | 47.2 tok/s | 4846 ms | 67K |
| RAG | C | Runs well | 47.2 tok/s | 7456 ms | 67K |
How Yi 9B Coder i1 (9B params) fits at each quantization level on RX 7700 XT 12GB (12.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | C50 |
Q3_K_S | 3 | 4.4 GB | Low | C51 |
NVFP4 | 4 |
Copy-paste commands to run Yi 9B Coder i1 on your machine.
Run
lms load hf-mradermacher--yi-9b-coder-i1-gguf && lms server startYes, RX 7700 XT 12GB can run Yi 9B Coder i1 with a C grade (Runs well). Expected decode speed: 47.2 tok/s.
Yi 9B Coder i1 (9B parameters) requires approximately 8.6 GB of memory with Q4_K_M quantization.
The recommended quantization for Yi 9B Coder i1 is Q4_K_M, which balances quality and memory efficiency.
On RX 7700 XT 12GB, Yi 9B Coder i1 achieves approximately 47.2 tokens per second decode speed with a time-to-first-token of 4101ms using Q4_K_M quantization.
For coding workloads, Yi 9B Coder i1 on RX 7700 XT 12GB receives a C grade with 47.2 tok/s and 67K context.
On RX 7700 XT 12GB, Yi 9B Coder i1 can safely use up to 67K 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--yi-9b-coder-i1-gguf-on-rx-7700-xt-12gb" 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 |
| C52 |
Q4_K_M | 4 | 5.5 GB | Medium | C52 |
Q5_K_M | 5 | 6.5 GB | High | C52 |
Q6_KBest for your GPU | 6 | 7.4 GB | High | C51 |
Q8_0 | 8 | 9.6 GB | Very High | F0 |
F16 | 16 | 18.5 GB | Maximum | F0 |