Will It Run AI

Can DiscoPOP zephyr 7b gemma run on RX 9060 XT 16GB?

YES — Runs Great

C49Usable
Estimated from fit model

DiscoPOP zephyr 7b gemma needs ~7.6 GB VRAM. RX 9060 XT 16GB has 16.0 GB. With Q4_K_M quantization, expect ~47 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: LowStack: StandardBottleneck: 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) 7.6 GB, 47.2 tok/s, Runs well
7.6 GB required16.0 GB available
48% VRAM used

Fit status

Runs well

Decode

47.2 tok/s

TTFT

4101 ms

Safe context

180K

Memory

7.6 GB / 16.0 GB

Memory breakdown

Weights4.3 GB
KV Cache0.8 GB
Runtime0.9 GB
Headroom1.6 GB

See how fast it feels

See how fast it feelsDiscoPOP zephyr 7b gemma on RX 9060 XT 16GB
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: 47.2 tok/s decode · 4.1s TTFT (warm) · 118 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

WorkloadGradeFitDecodeTTFTContext
ChatCRuns well47.2 tok/s2237 ms180K
CodingCRuns well47.2 tok/s4101 ms180K
Agentic CodingCRuns well47.2 tok/s5964 ms180K
ReasoningCRuns well47.2 tok/s4846 ms180K
RAGCRuns well47.2 tok/s7456 ms180K

Quantization options

How DiscoPOP zephyr 7b gemma (7B params) fits at each quantization level on RX 9060 XT 16GB (16.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
2.7 GB
LowC46
Q3_K_S
3
3.4 GB
LowC47
NVFP4
4
3.9 GB
MediumC47
Q4_K_M
4
4.3 GB
MediumC48
Q5_K_M
5
5.0 GB
HighC48
Q6_K
6
5.7 GB
HighC49
Q8_0Best for your GPU
8
7.5 GB
Very HighC51
F16
16
14.3 GB
MaximumF0

Get started

Copy-paste commands to run DiscoPOP zephyr 7b gemma on your machine.

Run

lms load hf-bartowski--discopop-zephyr-7b-gemma-gguf && lms server start

Opções de upgrade

Hardware que roda bem DiscoPOP zephyr 7b gemma

Frequently asked questions

Can RX 9060 XT 16GB run DiscoPOP zephyr 7b gemma?

Yes, RX 9060 XT 16GB can run DiscoPOP zephyr 7b gemma with a C grade (Runs well). Expected decode speed: 47.2 tok/s.

How much VRAM does DiscoPOP zephyr 7b gemma need?

DiscoPOP zephyr 7b gemma (7B parameters) requires approximately 7.6 GB of memory with Q4_K_M quantization.

What is the best quantization for DiscoPOP zephyr 7b gemma?

The recommended quantization for DiscoPOP zephyr 7b gemma is Q4_K_M, which balances quality and memory efficiency.

What speed will DiscoPOP zephyr 7b gemma run at on RX 9060 XT 16GB?

On RX 9060 XT 16GB, DiscoPOP zephyr 7b gemma achieves approximately 47.2 tokens per second decode speed with a time-to-first-token of 4101ms using Q4_K_M quantization.

Can RX 9060 XT 16GB run DiscoPOP zephyr 7b gemma for coding?

For coding workloads, DiscoPOP zephyr 7b gemma on RX 9060 XT 16GB receives a C grade with 47.2 tok/s and 180K context.

What context window can DiscoPOP zephyr 7b gemma use on RX 9060 XT 16GB?

On RX 9060 XT 16GB, DiscoPOP zephyr 7b gemma can safely use up to 180K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.

See all results for RX 9060 XT 16GBSee all hardware for DiscoPOP zephyr 7b gemma
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