Can Qwen 2.5 VL 7B run on RX 5700 XT 8GB?

YES — Tight Fit

A82Great

Estimated from fit model

Qwen 2.5 VL 7B needs ~6.8 GB VRAM. RX 5700 XT 8GB has 8.0 GB. With Q4_K_M quantization, expect ~59 tok/s.

Runtime: llama.cppCapacity: TightBandwidth: LowStack: StandardBottleneck: Balanced

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) — 6.8 GB, 59.2 tok/s, Tight fit

6.8 GB required8.0 GB available

85% VRAM used

Fit status

Tight fit

Decode

59.2 tok/s

TTFT

3268 ms

Safe context

33K

Memory

6.8 GB / 8.0 GB

Memory breakdown

Weights4.3 GB

KV Cache0.9 GB

Runtime0.9 GB

Headroom0.8 GB

See how fast it feels

See how fast it feelsQwen 2.5 VL 7B on RX 5700 XT 8GB
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: 59.2 tok/s decode · 3.3s TTFT (warm) · 148 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	S	Runs well	59.2 tok/s	1783 ms	33K
Coding	A	Tight fit	59.2 tok/s	3268 ms	33K
Agentic Coding	A	Runs with offload	59.2 tok/s	4754 ms	33K
Reasoning	A	Tight fit	59.2 tok/s	3863 ms	33K
RAG	A	Runs with offload	59.2 tok/s	5943 ms	33K

Quantization options

How Qwen 2.5 VL 7B (7B params) fits at each quantization level on RX 5700 XT 8GB (8.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	2.7 GB	Low	A83
Q3_K_S	3	3.4 GB	Low	A83
NVFP4	4	3.9 GB	Medium	A83
Q4_K_M	4	4.3 GB	Medium	A83
Q5_K_MBest for your GPU	5	5.0 GB	High	A82
Q6_K	6	5.7 GB	High	F0
Q8_0	8	7.5 GB	Very High	F0
F16	16	14.3 GB	Maximum	F0

Get started

Copy-paste commands to run Qwen 2.5 VL 7B on your machine.

Run

lms load Qwen2.5-VL-7B-Instruct && lms server start

Your hardware

More models your RX 5700 XT 8GB can run

Model	Params	Grade	Decode
Qwen 3.5 9B	9B	A	24.4 tok/s
Qwen 3 8B	8B	A	31.7 tok/s
Nemotron Nano 8B	8B	A	33.6 tok/s
InternVL2 8B	8B	A	33.6 tok/s
Ministral 3 8B	8B	A	31.7 tok/s

Frequently asked questions

Can RX 5700 XT 8GB run Qwen 2.5 VL 7B?

Yes, RX 5700 XT 8GB can run Qwen 2.5 VL 7B with a A grade (Tight fit). Expected decode speed: 59.2 tok/s.

How much VRAM does Qwen 2.5 VL 7B need?

Qwen 2.5 VL 7B (7B parameters) requires approximately 6.8 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen 2.5 VL 7B?

The recommended quantization for Qwen 2.5 VL 7B is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen 2.5 VL 7B run at on RX 5700 XT 8GB?

On RX 5700 XT 8GB, Qwen 2.5 VL 7B achieves approximately 59.2 tokens per second decode speed with a time-to-first-token of 3268ms using Q4_K_M quantization.

Can RX 5700 XT 8GB run Qwen 2.5 VL 7B for coding?

For coding workloads, Qwen 2.5 VL 7B on RX 5700 XT 8GB receives a A grade with 59.2 tok/s and 33K context.

What context window can Qwen 2.5 VL 7B use on RX 5700 XT 8GB?

On RX 5700 XT 8GB, Qwen 2.5 VL 7B can safely use up to 33K tokens of context. The model's official context limit is 33K, but available memory constrains the safe maximum.

See all results for RX 5700 XT 8GB See all hardware for Qwen 2.5 VL 7B

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<iframe src="https://willitrunai.com/embed/qwen-2.5-vl-7b-on-rx-5700-xt-8gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>

Preview:

Workload

Grade

Fit

Decode

TTFT

Context

Chat

Runs well

59.2 tok/s

1783 ms

33K

Coding

Tight fit

59.2 tok/s

3268 ms

33K

Agentic Coding

Runs with offload

59.2 tok/s

4754 ms

33K

Reasoning

Tight fit

59.2 tok/s

3863 ms

33K

RAG

Runs with offload

59.2 tok/s

5943 ms

33K

Quant

Bits

VRAM

Quality

Fit

Q2_K

2.7 GB

Low

A83

Q3_K_S

3.4 GB

Low

A83

NVFP4

3.9 GB

Medium

A83

Q4_K_M

4.3 GB

Medium

A83

Q5_K_MBest for your GPU

5.0 GB

High

A82

Q6_K

5.7 GB

High

Q8_0

7.5 GB

Very High

F16

14.3 GB

Maximum

Model

Params

Grade

Decode

Capabilities

24.4 tok/s

31.7 tok/s

33.6 tok/s

33.6 tok/s

31.7 tok/s

Frequently asked questions

Can RX 5700 XT 8GB run Qwen 2.5 VL 7B?

Yes, RX 5700 XT 8GB can run Qwen 2.5 VL 7B with a A grade (Tight fit). Expected decode speed: 59.2 tok/s.

How much VRAM does Qwen 2.5 VL 7B need?

Qwen 2.5 VL 7B (7B parameters) requires approximately 6.8 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen 2.5 VL 7B?

The recommended quantization for Qwen 2.5 VL 7B is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen 2.5 VL 7B run at on RX 5700 XT 8GB?

On RX 5700 XT 8GB, Qwen 2.5 VL 7B achieves approximately 59.2 tokens per second decode speed with a time-to-first-token of 3268ms using Q4_K_M quantization.

Can RX 5700 XT 8GB run Qwen 2.5 VL 7B for coding?

For coding workloads, Qwen 2.5 VL 7B on RX 5700 XT 8GB receives a A grade with 59.2 tok/s and 33K context.

What context window can Qwen 2.5 VL 7B use on RX 5700 XT 8GB?

On RX 5700 XT 8GB, Qwen 2.5 VL 7B can safely use up to 33K tokens of context. The model's official context limit is 33K, but available memory constrains the safe maximum.