96 GB VRAM (+32)1792 GB/s (+1192)
B
Raises estimated decode speed by about 222%.78.8 tok/s decode
Raises estimated decode speed by about 222%.
Adds memory headroom for longer context windows and future model growth.
~$9,999 MSRP
Can Yi 1.5 34B run on NVIDIA A16 64GB?
YES — Runs Great
B61Good
○Estimated from fit model
Yi 1.5 34B needs ~32.0 GB VRAM. NVIDIA A16 64GB has 64.0 GB. With Q4_K_M quantization, expect ~23 tok/s.
Runtime: OllamaCapacity: RoomyBandwidth: MediumStack: BasicBottleneck: Balanced
Share:
Operating mode
Choose the run profile you care about
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
Q4_K_M (Medium quality) — 32.0 GB, 24.5 tok/s, Runs well
32.0 GB required64.0 GB available
50% VRAM used
Fit status
Runs well
Decode
24.5 tok/s
TTFT
7902 ms
Safe context
4K
Memory
32.0 GB / 64.0 GB
Memory breakdown
Weights20.7 GB
KV Cache3.7 GB
Runtime1.2 GB
Headroom6.4 GB
See how fast it feels
See how fast it feelsYi 1.5 34B on NVIDIA A16 64GB
1st promptCold start — includes initialization
>Solve: If a train travels at 60 mph for 2.5 hours, how far does it go?
Let me work through this step by step.
Given information:
- Speed = 60 mph (miles per hour)
- Time = 2.5 hours
Formula: Distance = Speed x Time
Calculation:
Distance = 60 mph x 2.5 h
= 150 miles
The train travels 150 miles.
Double-check: at 60 mph the train covers 60 miles each hour. In half an hour it covers 30 miles. So in 2.5 hours: 60 + 60 + 30 = 150 miles. Confirmed.
2nd promptWarm — model ready, no init overhead
>What if the train stops for 20 minutes halfway?
The stop doesn't change the total distance covered while moving, but it affects total trip time.
Breakdown:
- First half: 1.25 hours at 60 mph = 75 miles
- Stop: 20 minutes (no distance)
- Second half: 1.25 hours at 60 mph = 75 miles
Total distance: 150 miles (same)
Total time: 2.5 h + 0.33 h = 2.83 hours
Average speed: 150 / 2.83 = 53 mph
The distance stays the same but average speed drops to 53 mph because of the stop.
Estimated: 24.5 tok/s decode · 7.9s TTFT (warm) · 61 tok/s prefill
What limits this setup
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.
Best improvement path
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | B | Runs well | 24.5 tok/s | 4310 ms | 4K |
| Coding | B | Runs well | 22.6 tok/s | 8580 ms | 4K |
| Agentic Coding | B | Runs well | 24.5 tok/s | 11494 ms | 4K |
| Reasoning | B | Runs well | 24.5 tok/s | 9339 ms | 4K |
| RAG | B | Runs well | 24.5 tok/s | 14368 ms | 4K |
Quantization options
How Yi 1.5 34B (34B params) fits at each quantization level on NVIDIA A16 64GB (64.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 13.3 GB | Low | C55 |
Q3_K_S | 3 | 16.7 GB | Low | B55 |
NVFP4 | 4 |
Get started
Copy-paste commands to run Yi 1.5 34B on your machine.
Run
lms load Yi-1.5-34B-Chat && lms server startUpgrade options
Hardware that runs Yi 1.5 34B well
96 GB VRAM (+32)1597 GB/s (+997)
B
Raises estimated decode speed by about 187%.70.2 tok/s decode
Raises estimated decode speed by about 187%.
Adds memory headroom for longer context windows and future model growth.
~$9,999 MSRP
96 GB VRAM (+32)4000 GB/s (+3400)
B
Raises estimated decode speed by about 592%.169.6 tok/s decode
Raises estimated decode speed by about 592%.
Adds memory headroom for longer context windows and future model growth.
~$12,000 MSRP