exaone 3.0 7.8b it needs ~8.2 GB VRAM. RX 9070 16GB has 16.0 GB. With Q4_K_M quantization, expect ~83 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
83.4 tok/s
TTFT
2321 ms
Safe context
153K
Memory
8.2 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 | C | Runs well | 83.4 tok/s | 1266 ms | 153K |
| Coding | C | Runs well | 83.4 tok/s | 2321 ms | 153K |
| Agentic Coding | C | Runs well | 83.4 tok/s | 3377 ms | 153K |
| Reasoning | C | Runs well | 83.4 tok/s | 2744 ms | 153K |
| RAG | C | Runs well | 83.4 tok/s | 4221 ms | 153K |
How exaone 3.0 7.8b it (7.800000190734863B params) fits at each quantization level on RX 9070 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.0 GB | Low | C47 |
Q3_K_S | 3 | 3.8 GB | Low | C47 |
NVFP4 | 4 |
Copy-paste commands to run exaone 3.0 7.8b it on your machine.
Run
lms load hf-bingsu--exaone-3-0-7-8b-it && lms server startYes, RX 9070 16GB can run exaone 3.0 7.8b it with a C grade (Runs well). Expected decode speed: 83.4 tok/s.
exaone 3.0 7.8b it (7.800000190734863B parameters) requires approximately 8.2 GB of memory with Q4_K_M quantization.
The recommended quantization for exaone 3.0 7.8b it is Q4_K_M, which balances quality and memory efficiency.
On RX 9070 16GB, exaone 3.0 7.8b it achieves approximately 83.4 tokens per second decode speed with a time-to-first-token of 2321ms using Q4_K_M quantization.
For coding workloads, exaone 3.0 7.8b it on RX 9070 16GB receives a C grade with 83.4 tok/s and 153K context.
On RX 9070 16GB, exaone 3.0 7.8b it can safely use up to 153K tokens of context. The model's official context limit is —, 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/hf-bingsu--exaone-3-0-7-8b-it-on-rx-9070-16gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
4.4 GB |
| Medium |
| C48 |
Q4_K_M | 4 | 4.8 GB | Medium | C48 |
Q5_K_M | 5 | 5.6 GB | High | C49 |
Q6_K | 6 | 6.4 GB | High | C50 |
Q8_0Best for your GPU | 8 | 8.3 GB | Very High | C51 |
F16 | 16 | 16.0 GB | Maximum | F0 |