NVIDIA H20 96GBBudget pick96 GB VRAM (+16)4000 GB/s (+1000)
C
Raises estimated decode speed by about 61%.53.1 tok/s decode
Raises estimated decode speed by about 61%.
~$12,000 MSRP
Solar Open 100B i1 needs ~81.6 GB VRAM. NVIDIA H800 80GB has 80.0 GB. With Q4_K_M quantization, expect ~33 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
1.6 GB over capacity — needs offload or smaller quantization
Fit status
Runs with offload (needs ~1.2 GB host RAM)
Decode
32.9 tok/s
TTFT
5889 ms
Safe context
14K
Memory
81.6 GB / 80.0 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 | 39.8 tok/s | 2651 ms | 14K |
| Coding | C | Runs with offload | 32.9 tok/s | 5889 ms | 14K |
| Agentic Coding | D | Very compromised | 26.3 tok/s | 10689 ms | 14K |
| Reasoning | C | Runs with offload | 32.9 tok/s | 6960 ms | 14K |
| RAG | D | Very compromised | 26.3 tok/s | 13361 ms | 14K |
How Solar Open 100B i1 (100B params) fits at each quantization level on NVIDIA H800 80GB (80.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 39.0 GB | Low | C47 |
Q3_K_S | 3 | 49.0 GB | Low | C48 |
NVFP4 | 4 |
Copy-paste commands to run Solar Open 100B i1 on your machine.
Run
lms load hf-mradermacher--solar-open-100b-i1-gguf && lms server startUpgrade options
NVIDIA H20 96GBBudget pickRaises estimated decode speed by about 61%.
~$12,000 MSRP
NVIDIA H200 141GBBest valueRaises estimated decode speed by about 101%.
Adds memory headroom for longer context windows and future model growth.
~$30,000 MSRP
NVIDIA H200 PCIe 141GBNVIDIA upgradeRaises estimated decode speed by about 101%.
Adds memory headroom for longer context windows and future model growth.
~$30,000 MSRP
Yes, NVIDIA H800 80GB can run Solar Open 100B i1 with a C grade (Runs with offload). Expected decode speed: 32.9 tok/s.
Solar Open 100B i1 (100B parameters) requires approximately 81.6 GB of memory with Q4_K_M quantization.
The recommended quantization for Solar Open 100B i1 is Q4_K_M, which balances quality and memory efficiency.
On NVIDIA H800 80GB, Solar Open 100B i1 achieves approximately 32.9 tokens per second decode speed with a time-to-first-token of 5889ms using Q4_K_M quantization.
For coding workloads, Solar Open 100B i1 on NVIDIA H800 80GB receives a C grade with 32.9 tok/s and 14K context.
On NVIDIA H800 80GB, Solar Open 100B i1 can safely use up to 14K 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--solar-open-100b-i1-gguf-on-h800-80gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
| Medium |
| C48 |
Q4_K_MBest for your GPU | 4 | 61.0 GB | Medium | C48 |
Q5_K_M | 5 | 72.0 GB | High | F0 |
Q6_K | 6 | 82.0 GB | High | F0 |
Q8_0 | 8 | 107.0 GB | Very High | F0 |
F16 | 16 | 205.0 GB | Maximum | F0 |
Buy headroom, not only minimum fit. A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.