Baichuan 7B needs ~13.8 GB but Radeon Pro W7500 8GB only has 8.0 GB. Try a smaller quantization or lighter model.
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
5.8 GB over capacity — needs offload or smaller quantization
Fit status
Too heavy
Decode
7.4 tok/s
TTFT
26209 ms
Safe context
4K
Memory
13.8 GB / 8.0 GB
Offload
40%
Usable VRAM is the main blocker for this model.
Not enough usable memory
The model needs 13.8 GB, but this setup only exposes 8.0 GB of usable VRAM.
Add more VRAM headroom
The first useful upgrade is more dedicated VRAM so you can fit the model without shrinking context or dropping to a much lower quant.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | F | Too heavy | 14.9 tok/s | 7088 ms | 4K |
| Coding | F | Too heavy | 7.4 tok/s | 26209 ms | 4K |
| Agentic Coding | F | Too heavy | 4.6 tok/s | 60655 ms | 4K |
| Reasoning | F | Too heavy | 7.4 tok/s | 30974 ms | 4K |
| RAG | F | Too heavy | 4.6 tok/s | 75819 ms | 4K |
How Baichuan 7B (7B params) fits at each quantization level on Radeon Pro W7500 8GB (8.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | B69 |
Q3_K_S | 3 | 3.4 GB | Low | B70 |
NVFP4 | 4 | 3.9 GB | Medium | B69 |
Q4_K_M | 4 | 4.3 GB | Medium | B69 |
Q5_K_MBest for your GPU | 5 | 5.0 GB | High | B69 |
Q6_K | 6 | 5.7 GB | High | F0 |
Q8_0 | 8 | 7.5 GB | Very High | F0 |
F16 | 16 | 14.3 GB | Maximum | F0 |
Opciones de mejora
Hace que el modelo quepa en el acelerador en lugar de seguir fuera de alcance.
Elimina el offload a memoria del sistema, que suele ser la mayor mejora individual en latencia y throughput.
~$329 MSRP
Hace que el modelo quepa en el acelerador en lugar de seguir fuera de alcance.
Elimina el offload a memoria del sistema, que suele ser la mayor mejora individual en latencia y throughput.
~$349 MSRP
Hace que el modelo quepa en el acelerador en lugar de seguir fuera de alcance.
Sube la velocidad estimada de decodificación alrededor de un 332%.
~$449 MSRP
Hace que el modelo quepa en el acelerador en lugar de seguir fuera de alcance.
Elimina el offload a memoria del sistema, que suele ser la mayor mejora individual en latencia y throughput.
~$899 MSRP
No, Baichuan 7B requires more memory than Radeon Pro W7500 8GB provides.
Baichuan 7B (7B parameters) requires approximately 13.8 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 Radeon Pro W7500 8GB, Baichuan 7B achieves approximately 7.4 tokens per second decode speed with a time-to-first-token of 26209ms using Q4_K_M quantization.
For coding workloads, Baichuan 7B on Radeon Pro W7500 8GB receives a F grade with 7.4 tok/s and 4K context.
On Radeon Pro W7500 8GB, Baichuan 7B can safely use up to 4K tokens of context. The model's official context limit is 8K, but available memory constrains the safe maximum.
Add more VRAM headroom. The first useful upgrade is more dedicated VRAM so you can fit the model without shrinking context or dropping to a much lower quant.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/baichuan-7b-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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