Will It Run AI

Can Yi 1.5 6B Chat run on Quadro RTX 8000 48GB?

YES — Runs Great

C46Usable
Estimated from fit model

Yi 1.5 6B Chat needs ~10.4 GB VRAM. Quadro RTX 8000 48GB has 48.0 GB. With Q4_K_M quantization, expect ~84 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: MediumStack: BasicBottleneck: Balanced
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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.

Capabilities:

Select quantization to explore

Q4_K_M (Medium quality) — 10.4 GB, 84.0 tok/s, Runs well
10.4 GB required48.0 GB available
22% VRAM used

Fit status

Runs well

Decode

84.0 tok/s

TTFT

2305 ms

Safe context

872K

Memory

10.4 GB / 48.0 GB

Memory breakdown

Weights3.7 GB
KV Cache0.7 GB
Runtime1.2 GB
Headroom4.8 GB

See how fast it feels

See how fast it feelsYi 1.5 6B Chat on Quadro RTX 8000 48GB
1st promptCold start — includes initialization
>What is local AI inference?
Local AI inference means running an AI language model directly on your own hardware — your laptop, desktop, or server — instead of sending requests to a remote cloud API. When you run inference locally the model weights are loaded into your GPU or unified memory. Each token you generate requires reading those weights from memory, so memory bandwidth is the main bottleneck for decode speed. Key benefits of running locally: - Full privacy: your prompts never leave your machine - No per-token cost or rate limits - Works offline once the model is downloaded - Latency depends only on your hardware
2nd promptWarm — model ready, no init overhead
>How much VRAM do I need?
It depends on the model size and quantization level. A rough rule of thumb: Model size Q4 (4-bit) Q8 (8-bit) FP16 7B params ~4.3 GB ~7.5 GB ~14 GB 13B params ~7.9 GB ~13.9 GB ~26 GB 70B params ~42.7 GB ~74.9 GB ~140 GB Most people use 4-bit quantization (Q4_K_M) which gives 90-95% of full quality at a fraction of the memory. A 24 GB GPU can comfortably run most 7B-13B models.
Estimated: 84.0 tok/s decode · 2.3s TTFT (warm) · 210 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

Older PCIe generation

PCIe 3.0 is workable, but it compounds the penalty when you offload heavily or try to scale across multiple cards.

Best improvement path

Performance by workload

WorkloadGradeFitDecodeTTFTContext
ChatCRuns well84.0 tok/s1257 ms872K
CodingCRuns well84.0 tok/s2305 ms872K
Agentic CodingCRuns well84.0 tok/s3352 ms872K
ReasoningCRuns well84.0 tok/s2724 ms872K
RAGCRuns well84.0 tok/s4190 ms872K

Quantization options

How Yi 1.5 6B Chat (6B params) fits at each quantization level on Quadro RTX 8000 48GB (48.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
2.3 GB
LowC41
Q3_K_S
3
2.9 GB
LowC41
NVFP4
4
3.4 GB
MediumC41
Q4_K_M
4
3.7 GB
MediumC41
Q5_K_M
5
4.3 GB
HighC41
Q6_K
6
4.9 GB
HighC41
Q8_0
8
6.4 GB
Very HighC42
F16Best for your GPU
16
12.3 GB
MaximumC43

Get started

Copy-paste commands to run Yi 1.5 6B Chat on your machine.

Run

lms load hf-bartowski--yi-1-5-6b-chat-gguf && lms server start

Opciones de mejora

Hardware que ejecuta bien Yi 1.5 6B Chat

MacBook Pro M4 Max 96GBOpción económica
96 GB Unified (+48)
C
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.84 tok/s decodificación

Añade margen de memoria para más contexto y para que el modelo envejezca mejor.

~$2,499 MSRP

Mac Studio M3 Ultra 96GBMejor relación calidad-precio
96 GB Unified (+48)819 GB/s (+147)
C
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.84 tok/s decodificación

Añade margen de memoria para más contexto y para que el modelo envejezca mejor.

~$3,999 MSRP

Frequently asked questions

Can Quadro RTX 8000 48GB run Yi 1.5 6B Chat?

Yes, Quadro RTX 8000 48GB can run Yi 1.5 6B Chat with a C grade (Runs well). Expected decode speed: 84.0 tok/s.

How much VRAM does Yi 1.5 6B Chat need?

Yi 1.5 6B Chat (6B parameters) requires approximately 10.4 GB of memory with Q4_K_M quantization.

What is the best quantization for Yi 1.5 6B Chat?

The recommended quantization for Yi 1.5 6B Chat is Q4_K_M, which balances quality and memory efficiency.

What speed will Yi 1.5 6B Chat run at on Quadro RTX 8000 48GB?

On Quadro RTX 8000 48GB, Yi 1.5 6B Chat achieves approximately 84.0 tokens per second decode speed with a time-to-first-token of 2305ms using Q4_K_M quantization.

Can Quadro RTX 8000 48GB run Yi 1.5 6B Chat for coding?

For coding workloads, Yi 1.5 6B Chat on Quadro RTX 8000 48GB receives a C grade with 84.0 tok/s and 872K context.

What context window can Yi 1.5 6B Chat use on Quadro RTX 8000 48GB?

On Quadro RTX 8000 48GB, Yi 1.5 6B Chat can safely use up to 872K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.

See all results for Quadro RTX 8000 48GBSee all hardware for Yi 1.5 6B Chat
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