Can Pixtral 12B run on RTX A4500 20GB?

YES — Runs Great

A79Great
Estimated from fit model

Pixtral 12B needs ~13.0 GB VRAM. RTX A4500 20GB has 20.0 GB. With Q4_K_M quantization, expect ~73 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) 13.0 GB, 73.3 tok/s, Runs well
13.0 GB required20.0 GB available
65% VRAM used

Fit status

Runs well

Decode

73.3 tok/s

TTFT

2641 ms

Safe context

62K

Memory

13.0 GB / 20.0 GB

Memory breakdown

Weights7.3 GB
KV Cache2.4 GB
Runtime1.2 GB
Headroom2.0 GB

See how fast it feels

See how fast it feelsPixtral 12B on RTX A4500 20GB
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: 73.3 tok/s decode · 2.6s TTFT (warm) · 183 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
ChatARuns well73.3 tok/s1440 ms62K
CodingARuns well73.3 tok/s2641 ms62K
Agentic CodingARuns well73.3 tok/s3841 ms62K
ReasoningARuns well73.3 tok/s3121 ms62K
RAGARuns well73.3 tok/s4801 ms62K

Quantization options

How Pixtral 12B (12B params) fits at each quantization level on RTX A4500 20GB (20.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
4.7 GB
LowA70
Q3_K_S
3
5.9 GB
LowA71
NVFP4
4
6.7 GB
MediumA72
Q4_K_M
4
7.3 GB
MediumA72
Q5_K_M
5
8.6 GB
HighA73
Q6_K
6
9.8 GB
HighA74
Q8_0Best for your GPU
8
12.8 GB
Very HighA74
F16
16
24.6 GB
MaximumF0

Get started

Copy-paste commands to run Pixtral 12B on your machine.

Run

ollama run pixtral

Your hardware

More models your RTX A4500 20GB can run

ModelParamsGradeDecodeCapabilities
AlibabaQwen3-Coder 30B A3B Instruct30.5BA41.2 tok/s
AlibabaQwen 3.5 27B27BA18.6 tok/s
AlibabaQwen 3.6 27B27BS23 tok/s
AlibabaQwen3-VL 30B A3B Instruct30BA43.8 tok/s
MistralMagistral Small 250724BS26.7 tok/s

Frequently asked questions

Can RTX A4500 20GB run Pixtral 12B?

Yes, RTX A4500 20GB can run Pixtral 12B with a A grade (Runs well). Expected decode speed: 73.3 tok/s.

How much VRAM does Pixtral 12B need?

Pixtral 12B (12B parameters) requires approximately 13.0 GB of memory with Q4_K_M quantization.

What is the best quantization for Pixtral 12B?

The recommended quantization for Pixtral 12B is Q4_K_M, which balances quality and memory efficiency.

What speed will Pixtral 12B run at on RTX A4500 20GB?

On RTX A4500 20GB, Pixtral 12B achieves approximately 73.3 tokens per second decode speed with a time-to-first-token of 2641ms using Q4_K_M quantization.

Can RTX A4500 20GB run Pixtral 12B for coding?

For coding workloads, Pixtral 12B on RTX A4500 20GB receives a A grade with 73.3 tok/s and 62K context.

What context window can Pixtral 12B use on RTX A4500 20GB?

On RTX A4500 20GB, Pixtral 12B can safely use up to 62K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

See all results for RTX A4500 20GBSee all hardware for Pixtral 12B
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