OpenHermes 2.5 7B needs ~8.6 GB VRAM. RTX 4070 Super 12GB has 12.0 GB. With Q4_K_M quantization, expect ~98 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
97.7 tok/s
TTFT
1982 ms
Safe context
8K
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 | B | Runs well | 97.7 tok/s | 1081 ms | 8K |
| Coding | B | Runs well | 97.7 tok/s | 1982 ms | 8K |
| Agentic Coding | C | Tight fit | 97.7 tok/s | 2882 ms | 8K |
| Reasoning | B | Runs well | 97.7 tok/s | 2342 ms | 8K |
| RAG | C | Tight fit | 97.7 tok/s | 3603 ms | 8K |
How OpenHermes 2.5 7B (7B params) fits at each quantization level on RTX 4070 Super 12GB (12.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | C50 |
Q3_K_S | 3 | 3.4 GB | Low | C51 |
NVFP4 | 4 | 3.9 GB | Medium | C51 |
Q4_K_M | 4 | 4.3 GB | Medium | C52 |
Q5_K_M | 5 | 5.0 GB | High | C53 |
Q6_K | 6 | 5.7 GB | High | C53 |
Q8_0Best for your GPU | 8 | 7.5 GB | Very High | C53 |
F16 | 16 | 14.3 GB | Maximum | F0 |
Copy-paste commands to run OpenHermes 2.5 7B on your machine.
Run
ollama run openhermesYes, RTX 4070 Super 12GB can run OpenHermes 2.5 7B with a B grade (Runs well). Expected decode speed: 97.7 tok/s.
OpenHermes 2.5 7B (7B parameters) requires approximately 8.6 GB of memory with Q4_K_M quantization.
The recommended quantization for OpenHermes 2.5 7B is Q4_K_M, which balances quality and memory efficiency.
On RTX 4070 Super 12GB, OpenHermes 2.5 7B achieves approximately 97.7 tokens per second decode speed with a time-to-first-token of 1982ms using Q4_K_M quantization.
For coding workloads, OpenHermes 2.5 7B on RTX 4070 Super 12GB receives a B grade with 97.7 tok/s and 8K context.
On RTX 4070 Super 12GB, OpenHermes 2.5 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/openhermes-2.5-7b-on-rtx-4070-super-12gb" 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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