GGUF SOLARized GraniStral 14B 1902 YeAM HCT needs ~13.0 GB VRAM. NVIDIA A2 16GB has 16.0 GB. With Q4_K_M quantization, expect ~18 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
18.3 tok/s
TTFT
10598 ms
Safe context
45K
Memory
13.0 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 | 18.3 tok/s | 5781 ms | 45K |
| Coding | C | Runs well | 18.3 tok/s | 10598 ms | 45K |
| Agentic Coding | C | Tight fit | 18.3 tok/s | 15416 ms | 45K |
| Reasoning | C | Runs well | 18.3 tok/s | 12525 ms | 45K |
| RAG | C | Tight fit | 18.3 tok/s | 19270 ms | 45K |
Inference speed
Estimated decode speed (tokens/sec) for GGUF SOLARized GraniStral 14B 1902 YeAM HCT at Q4_K_M across popular GPUs and Apple Silicon, using the fastest local runtime per device. Fastest is RTX 5090 32GB at ~141 tok/s. Speed is memory-bandwidth bound, so cards that fit the whole model in VRAM run far faster than ones that offload to system RAM.
| GPU / Mac | Memory | Quant | Speed (tok/s) | Fits? |
|---|---|---|---|---|
 RTX 5090 32GB | 32 GB | Q4_K_M | 140.6 | Fits |
| RTX 4090 24GB | 24 GB | Q4_K_M | 89.7 | Fits |
RX 7900 XTX 24GB | 24 GB | Q4_K_M | 80.9 | Fits |
| RTX 3090 24GB | 24 GB | Q4_K_M | 76.7 | Fits |
| RTX 4080 Super 16GB | 16 GB | Q4_K_M | 75.1 | Fits |
Mac Studio M3 Ultra 256GB | 256 GB | Q4_K_M | 65.2 | Fits |
Mac Studio M2 Ultra 128GB | 128 GB | Q4_K_M | 54.3 | Fits |
Mac Studio M1 Ultra 128GB | 128 GB | Q4_K_M | 51.5 | Fits |
MacBook Pro M4 Max 128GB | 128 GB | Q4_K_M | 35.4 | Fits |
MacBook Pro M4 Max 64GB | 64 GB | Q4_K_M | 35.4 | Fits |
| RTX 4070 12GB | 12 GB | Q4_K_M | 33.2 | Offloads |
MacBook Pro M3 Max 64GB | 64 GB | Q4_K_M | 28.1 | Fits |
MacBook Pro M1 Max 64GB | 64 GB | Q4_K_M | 25.8 | Fits |
MacBook Pro M4 Pro 48GB | 48 GB | Q4_K_M | 21.7 | Fits |
| RTX 3060 12GB | 12 GB | Q4_K_M | 19.5 | Offloads |
| RTX 4060 8GB | 8 GB | Q4_K_M | 7.2 | Too big |
Estimates for single-stream decoding at Q4_K_M; real tokens/sec varies with prompt length, context, batch size, and runtime build. Prompt processing (prefill) is faster than the decode figures shown here.
How GGUF SOLARized GraniStral 14B 1902 YeAM HCT (14B params) fits at each quantization level on NVIDIA A2 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | C49 |
Q3_K_S | 3 | 6.9 GB | Low | C50 |
NVFP4 | 4 | 7.8 GB | Medium | C51 |
Q4_K_M | 4 | 8.5 GB | Medium | C51 |
Q5_K_M | 5 | 10.1 GB | High | C51 |
Q6_KBest for your GPU | 6 | 11.5 GB | High | C50 |
Q8_0 | 8 | 15.0 GB | Very High | F0 |
F16 | 16 | 28.7 GB | Maximum | F0 |
Copy-paste commands to run GGUF SOLARized GraniStral 14B 1902 YeAM HCT on your machine.
Run
lms load hf-srs6901--gguf-solarized-granistral-14b-1902-yeam-hct && lms server startUpgrade options
RTX 4000 Ada 20GBBudget pickRaises estimated decode speed by about 80%.
Adds memory headroom for longer context windows and future model growth.
~$1,250 MSRP
RTX 3090 24GBBest valueRaises estimated decode speed by about 319%.
Adds memory headroom for longer context windows and future model growth.
~$1,499 MSRP
RTX PRO 4000 Blackwell 24GBNVIDIA upgradeRaises estimated decode speed by about 261%.
Adds memory headroom for longer context windows and future model growth.
~$1,599 MSRP
Yes, NVIDIA A2 16GB can run GGUF SOLARized GraniStral 14B 1902 YeAM HCT with a C grade (Runs well). Expected decode speed: 18.3 tok/s.
GGUF SOLARized GraniStral 14B 1902 YeAM HCT (14B parameters) requires approximately 13.0 GB of memory with Q4_K_M quantization.
The recommended quantization for GGUF SOLARized GraniStral 14B 1902 YeAM HCT is Q4_K_M, which balances quality and memory efficiency.
On NVIDIA A2 16GB, GGUF SOLARized GraniStral 14B 1902 YeAM HCT achieves approximately 18.3 tokens per second decode speed with a time-to-first-token of 10598ms using Q4_K_M quantization.
For coding workloads, GGUF SOLARized GraniStral 14B 1902 YeAM HCT on NVIDIA A2 16GB receives a C grade with 18.3 tok/s and 45K context.
On NVIDIA A2 16GB, GGUF SOLARized GraniStral 14B 1902 YeAM HCT can safely use up to 45K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
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