Nous Hermes 1.0 needs ~19.7 GB but RTX 4070 Laptop 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
11.7 GB over capacity — needs offload or smaller quantization
Fit status
Too heavy
Decode
5.3 tok/s
TTFT
36419 ms
Safe context
4K
Memory
19.7 GB / 8.0 GB
Offload
60%
Usable VRAM is the main blocker for this model.
Not enough usable memory
The model needs 19.7 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 | 8.7 tok/s | 12128 ms | 4K |
| Coding | F | Too heavy | 5.3 tok/s | 36419 ms | 4K |
| Agentic Coding | F | Too heavy | 5.3 tok/s | 52974 ms | 4K |
| Reasoning | F | Too heavy | 5.3 tok/s | 43041 ms | 4K |
| RAG | F | Too heavy | 5.3 tok/s | 66217 ms | 4K |
How Nous Hermes 1.0 (9B params) fits at each quantization level on RTX 4070 Laptop 8GB (8.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | A74 |
Q3_K_S | 3 | 4.4 GB | Low | A74 |
NVFP4Best for your GPU | 4 | 5.0 GB | Medium | A73 |
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 |
Opciones de mejora
RTX 4000 Ada 20GBOpción económicaHace 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.
~$1,250 MSRP
RTX 3090 24GBMejor relación calidad-precioHace 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.
~$1,499 MSRP
RTX 4090 24GBMejora NVIDIAHace 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.
~$1,599 MSRP
No, Nous Hermes 1.0 requires more memory than RTX 4070 Laptop 8GB provides.
Nous Hermes 1.0 (9B parameters) requires approximately 19.7 GB of memory with Q4_K_M quantization.
The recommended quantization for Nous Hermes 1.0 is Q4_K_M, which balances quality and memory efficiency.
On RTX 4070 Laptop 8GB, Nous Hermes 1.0 achieves approximately 5.3 tokens per second decode speed with a time-to-first-token of 36419ms using Q4_K_M quantization.
For coding workloads, Nous Hermes 1.0 on RTX 4070 Laptop 8GB receives a F grade with 5.3 tok/s and 4K context.
On RTX 4070 Laptop 8GB, Nous Hermes 1.0 can safely use up to 4K tokens of context. The model's official context limit is 16K, 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/nous-hermes-1.0-on-rtx-4070-laptop-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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