Can Qwen 2.5 7B run on RX 6700 XT 12GB?

YES — Runs Great

A79Great

Estimated from fit model

Qwen 2.5 7B needs ~7.2 GB VRAM. RX 6700 XT 12GB has 12.0 GB. With Q4_K_M quantization, expect ~51 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: 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) — 7.2 GB, 50.8 tok/s, Runs well

7.2 GB required12.0 GB available

60% VRAM used

Fit status

Runs well

Decode

50.8 tok/s

TTFT

3813 ms

Safe context

105K

Memory

7.2 GB / 12.0 GB

Memory breakdown

Weights4.3 GB

KV Cache0.9 GB

Runtime0.9 GB

Headroom1.2 GB

See how fast it feels

See how fast it feelsQwen 2.5 7B on RX 6700 XT 12GB
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: 50.8 tok/s decode · 3.8s TTFT (warm) · 127 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	A	Runs well	50.8 tok/s	2080 ms	105K
Coding	A	Runs well	50.8 tok/s	3813 ms	105K
Agentic Coding	A	Runs well	50.8 tok/s	5546 ms	105K
Reasoning	A	Runs well	50.8 tok/s	4506 ms	105K
RAG	A	Runs well	50.8 tok/s	6933 ms	105K

Quantization options

How Qwen 2.5 7B (7B params) fits at each quantization level on RX 6700 XT 12GB (12.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	2.7 GB	Low	A75
Q3_K_S	3	3.4 GB	Low	A76
NVFP4	4	3.9 GB	Medium	A76
Q4_K_M	4	4.3 GB	Medium	A77
Q5_K_M	5	5.0 GB	High	A78
Q6_K	6	5.7 GB	High	A78
Q8_0Best for your GPU	8	7.5 GB	Very High	A78
F16	16	14.3 GB	Maximum	F0

Get started

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

Run

ollama run qwen2.5

Your hardware

More models your RX 6700 XT 12GB can run

Model	Params	Grade	Decode
Qwen 3.5 9B	9B	S	39.1 tok/s
Qwen 3 14B	14B	A	15.8 tok/s
Qwen 3 8B	8B	S	44 tok/s
Phi-4-reasoning-plus 14B	14.7B	A	12.8 tok/s
Nemotron Nano 8B	8B	S	44 tok/s

Frequently asked questions

Can RX 6700 XT 12GB run Qwen 2.5 7B?

Yes, RX 6700 XT 12GB can run Qwen 2.5 7B with a A grade (Runs well). Expected decode speed: 50.8 tok/s.

How much VRAM does Qwen 2.5 7B need?

Qwen 2.5 7B (7B parameters) requires approximately 7.2 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen 2.5 7B?

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

What speed will Qwen 2.5 7B run at on RX 6700 XT 12GB?

On RX 6700 XT 12GB, Qwen 2.5 7B achieves approximately 50.8 tokens per second decode speed with a time-to-first-token of 3813ms using Q4_K_M quantization.

Can RX 6700 XT 12GB run Qwen 2.5 7B for coding?

For coding workloads, Qwen 2.5 7B on RX 6700 XT 12GB receives a A grade with 50.8 tok/s and 105K context.

What context window can Qwen 2.5 7B use on RX 6700 XT 12GB?

On RX 6700 XT 12GB, Qwen 2.5 7B can safely use up to 105K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

See all results for RX 6700 XT 12GB See all hardware for Qwen 2.5 7B

Embed this result▼

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<iframe src="https://willitrunai.com/embed/qwen-2.5-7b-on-rx-6700-xt-12gb" 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

50.8 tok/s

2080 ms

105K

Coding

Runs well

50.8 tok/s

3813 ms

105K

Agentic Coding

Runs well

50.8 tok/s

5546 ms

105K

Reasoning

Runs well

50.8 tok/s

4506 ms

105K

RAG

Runs well

50.8 tok/s

6933 ms

105K

Quant

Bits

VRAM

Quality

Fit

Q2_K

2.7 GB

Low

A75

Q3_K_S

3.4 GB

Low

A76

NVFP4

3.9 GB

Medium

A76

Q4_K_M

4.3 GB

Medium

A77

Q5_K_M

5.0 GB

High

A78

Q6_K

5.7 GB

High

A78

Q8_0Best for your GPU

7.5 GB

Very High

A78

F16

14.3 GB

Maximum

Model

Params

Grade

Decode

Capabilities

Qwen 3.5 9B

39.1 tok/s

Qwen 3 14B

14B

15.8 tok/s

Qwen 3 8B

44 tok/s

Phi-4-reasoning-plus 14B

14.7B

12.8 tok/s

Nemotron Nano 8B

44 tok/s

Frequently asked questions

Can RX 6700 XT 12GB run Qwen 2.5 7B?

Yes, RX 6700 XT 12GB can run Qwen 2.5 7B with a A grade (Runs well). Expected decode speed: 50.8 tok/s.

How much VRAM does Qwen 2.5 7B need?

Qwen 2.5 7B (7B parameters) requires approximately 7.2 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen 2.5 7B?

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

What speed will Qwen 2.5 7B run at on RX 6700 XT 12GB?

On RX 6700 XT 12GB, Qwen 2.5 7B achieves approximately 50.8 tokens per second decode speed with a time-to-first-token of 3813ms using Q4_K_M quantization.

Can RX 6700 XT 12GB run Qwen 2.5 7B for coding?

For coding workloads, Qwen 2.5 7B on RX 6700 XT 12GB receives a A grade with 50.8 tok/s and 105K context.

What context window can Qwen 2.5 7B use on RX 6700 XT 12GB?

On RX 6700 XT 12GB, Qwen 2.5 7B can safely use up to 105K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.