Mac Studio M3 Ultra 96GBBudget pick
96 GB Unified (+48)819 GB/s (+123)
C
Adds memory headroom for longer context windows and future model growth.109.2 tok/s decode
Adds memory headroom for longer context windows and future model growth.
~$3,999 MSRP
EXAONE 3.5 7.8B Instruct i1 needs ~11.7 GB VRAM. NVIDIA A40 48GB has 48.0 GB. With Q4_K_M quantization, expect ~109 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
109.2 tok/s
TTFT
1773 ms
Safe context
652K
Memory
11.7 GB / 48.0 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 | 109.2 tok/s | 967 ms | 652K |
| Coding | C | Runs well | 109.2 tok/s | 1773 ms | 652K |
| Agentic Coding | C | Runs well | 109.2 tok/s | 2579 ms | 652K |
| Reasoning | C | Runs well | 109.2 tok/s | 2095 ms | 652K |
| RAG | C | Runs well | 109.2 tok/s | 3223 ms | 652K |
How EXAONE 3.5 7.8B Instruct i1 (7.800000190734863B params) fits at each quantization level on NVIDIA A40 48GB (48.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.0 GB | Low | C41 |
Q3_K_S | 3 | 3.8 GB | Low | C41 |
NVFP4 | 4 | 4.4 GB | Medium | C41 |
Q4_K_M | 4 | 4.8 GB | Medium | C41 |
Q5_K_M | 5 | 5.6 GB | High | C42 |
Q6_K | 6 | 6.4 GB | High | C42 |
Q8_0 | 8 | 8.3 GB | Very High | C42 |
F16Best for your GPU | 16 | 16.0 GB | Maximum | C44 |
Copy-paste commands to run EXAONE 3.5 7.8B Instruct i1 on your machine.
Run
lms load hf-mradermacher--exaone-3-5-7-8b-instruct-i1-gguf && lms server startUpgrade options
Yes, NVIDIA A40 48GB can run EXAONE 3.5 7.8B Instruct i1 with a C grade (Runs well). Expected decode speed: 109.2 tok/s.
EXAONE 3.5 7.8B Instruct i1 (7.800000190734863B parameters) requires approximately 11.7 GB of memory with Q4_K_M quantization.
The recommended quantization for EXAONE 3.5 7.8B Instruct i1 is Q4_K_M, which balances quality and memory efficiency.
On NVIDIA A40 48GB, EXAONE 3.5 7.8B Instruct i1 achieves approximately 109.2 tokens per second decode speed with a time-to-first-token of 1773ms using Q4_K_M quantization.
For coding workloads, EXAONE 3.5 7.8B Instruct i1 on NVIDIA A40 48GB receives a C grade with 109.2 tok/s and 652K context.
On NVIDIA A40 48GB, EXAONE 3.5 7.8B Instruct i1 can safely use up to 652K 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-mradermacher--exaone-3-5-7-8b-instruct-i1-gguf-on-a40-48gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: