Baichuan 7B needs ~14.6 GB VRAM. RX 6800 16GB has 16.0 GB. With Q4_K_M quantization, expect ~66 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
Tight fit
Decode
65.9 tok/s
TTFT
2936 ms
Safe context
8K
Memory
14.6 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 | A | Runs well | 65.9 tok/s | 1601 ms | 8K |
| Coding | B | Tight fit | 65.9 tok/s | 2936 ms | 8K |
| Agentic Coding | F | Too heavy | 24.4 tok/s | 11555 ms | 8K |
| Reasoning | B | Tight fit | 65.9 tok/s | 3469 ms | 8K |
| RAG | F | Too heavy | 24.4 tok/s | 14443 ms | 8K |
How Baichuan 7B (7B params) fits at each quantization level on RX 6800 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | B63 |
Q3_K_S | 3 | 3.4 GB | Low | B63 |
NVFP4 | 4 | 3.9 GB | Medium | B64 |
Q4_K_M | 4 | 4.3 GB | Medium | B64 |
Q5_K_M | 5 | 5.0 GB | High | B65 |
Q6_K | 6 | 5.7 GB | High | B66 |
Q8_0Best for your GPU | 8 | 7.5 GB | Very High | B67 |
F16 | 16 | 14.3 GB | Maximum | F0 |
Copy-paste commands to run Baichuan 7B on your machine.
Run
docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
--hf-repo "baichuan-inc/Baichuan-7B" \
--hf-file "Baichuan-7B-Q4_K_M.gguf" \
-c 4096 -ngl 99Opciones de mejora
Sube la velocidad estimada de decodificación alrededor de un 49%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$899 MSRP
Sube la velocidad estimada de decodificación alrededor de un 49%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$999 MSRP
Yes, RX 6800 16GB can run Baichuan 7B with a B grade (Tight fit). Expected decode speed: 65.9 tok/s.
Baichuan 7B (7B parameters) requires approximately 14.6 GB of memory with Q4_K_M quantization.
The recommended quantization for Baichuan 7B is Q4_K_M, which balances quality and memory efficiency.
On RX 6800 16GB, Baichuan 7B achieves approximately 65.9 tokens per second decode speed with a time-to-first-token of 2936ms using Q4_K_M quantization.
For coding workloads, Baichuan 7B on RX 6800 16GB receives a B grade with 65.9 tok/s and 8K context.
On RX 6800 16GB, Baichuan 7B can safely use up to 8K tokens of context. The model's official context limit is 8K, 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/baichuan-7b-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>
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