Hermes 2 Pro Llama 3 8B needs ~7.5 GB VRAM. RX 9060 8GB has 8.0 GB. With Q4_K_M quantization, expect ~37 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
37.2 tok/s
TTFT
5207 ms
Safe context
24K
Memory
7.5 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 | Tight fit | 37.2 tok/s | 2840 ms | 24K |
| Coding | C | Tight fit | 37.2 tok/s | 5207 ms | 24K |
| Agentic Coding | D | Runs with offload (needs ~0.3 GB host RAM) | 24.8 tok/s | 11346 ms | 24K |
| Reasoning | C | Tight fit | 37.2 tok/s | 6154 ms | 24K |
| RAG | D | Runs with offload (needs ~0.3 GB host RAM) | 24.8 tok/s | 14182 ms | 24K |
How Hermes 2 Pro Llama 3 8B (8B params) fits at each quantization level on RX 9060 8GB (8.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | C54 |
Q3_K_S | 3 | 3.9 GB | Low | C53 |
NVFP4 | 4 | 4.5 GB | Medium | C53 |
Q4_K_MBest for your GPU | 4 | 4.9 GB | Medium | C53 |
Q5_K_M | 5 | 5.8 GB | High | F0 |
Q6_K | 6 | 6.6 GB | High | F0 |
Q8_0 | 8 | 8.6 GB | Very High | F0 |
F16 | 16 | 16.4 GB | Maximum | F0 |
Copy-paste commands to run Hermes 2 Pro Llama 3 8B on your machine.
Run
lms load hf-nousresearch--hermes-2-pro-llama-3-8b-gguf && lms server startOpciones de mejora
Sube la velocidad estimada de decodificación alrededor de un 43%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$449 MSRP
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$479 MSRP
Sube la velocidad estimada de decodificación alrededor de un 119%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$479 MSRP
Yes, RX 9060 8GB can run Hermes 2 Pro Llama 3 8B with a C grade (Tight fit). Expected decode speed: 37.2 tok/s.
Hermes 2 Pro Llama 3 8B (8B parameters) requires approximately 7.5 GB of memory with Q4_K_M quantization.
The recommended quantization for Hermes 2 Pro Llama 3 8B is Q4_K_M, which balances quality and memory efficiency.
On RX 9060 8GB, Hermes 2 Pro Llama 3 8B achieves approximately 37.2 tokens per second decode speed with a time-to-first-token of 5207ms using Q4_K_M quantization.
For coding workloads, Hermes 2 Pro Llama 3 8B on RX 9060 8GB receives a C grade with 37.2 tok/s and 24K context.
On RX 9060 8GB, Hermes 2 Pro Llama 3 8B can safely use up to 24K 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-nousresearch--hermes-2-pro-llama-3-8b-gguf-on-rx-9060-8gb" 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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