Will It Run AI

Can Phi 4 reasoning vision 15B run on RX 6800 16GB?

YES — Tight Fit

C50Usable
Estimated from fit model

Phi 4 reasoning vision 15B needs ~13.4 GB VRAM. RX 6800 16GB has 16.0 GB. With Q4_K_M quantization, expect ~31 tok/s.

Runtime: llama.cppCapacity: TightBandwidth: MediumStack: StandardBottleneck: Balanced
Share:

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) — 13.4 GB, 30.8 tok/s, Tight fit
13.4 GB required16.0 GB available
84% VRAM used

Fit status

Tight fit

Decode

30.8 tok/s

TTFT

6291 ms

Safe context

40K

Memory

13.4 GB / 16.0 GB

Memory breakdown

Weights9.2 GB
KV Cache1.8 GB
Runtime0.9 GB
Headroom1.6 GB

See how fast it feels

See how fast it feelsPhi 4 reasoning vision 15B on RX 6800 16GB
1st promptCold start — includes initialization
>Solve: If a train travels at 60 mph for 2.5 hours, how far does it go?
Let me work through this step by step. Given information: - Speed = 60 mph (miles per hour) - Time = 2.5 hours Formula: Distance = Speed x Time Calculation: Distance = 60 mph x 2.5 h = 150 miles The train travels 150 miles. Double-check: at 60 mph the train covers 60 miles each hour. In half an hour it covers 30 miles. So in 2.5 hours: 60 + 60 + 30 = 150 miles. Confirmed.
2nd promptWarm — model ready, no init overhead
>What if the train stops for 20 minutes halfway?
The stop doesn't change the total distance covered while moving, but it affects total trip time. Breakdown: - First half: 1.25 hours at 60 mph = 75 miles - Stop: 20 minutes (no distance) - Second half: 1.25 hours at 60 mph = 75 miles Total distance: 150 miles (same) Total time: 2.5 h + 0.33 h = 2.83 hours Average speed: 150 / 2.83 = 53 mph The distance stays the same but average speed drops to 53 mph because of the stop.
Estimated: 30.8 tok/s decode · 6.3s TTFT (warm) · 77 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 well30.8 tok/s3431 ms40K
CodingCTight fit30.8 tok/s6291 ms40K
Agentic CodingCTight fit30.8 tok/s9150 ms40K
ReasoningCTight fit30.8 tok/s7434 ms40K
RAGCTight fit30.8 tok/s11438 ms40K

Quantization options

How Phi 4 reasoning vision 15B (15B params) fits at each quantization level on RX 6800 16GB (16.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
5.9 GB
LowC50
Q3_K_S
3
7.4 GB
LowC51
NVFP4
4
8.4 GB
MediumC51
Q4_K_M
4
9.2 GB
MediumC51
Q5_K_M
5
10.8 GB
HighC51
Q6_KBest for your GPU
6
12.3 GB
HighC50
Q8_0
8
16.1 GB
Very HighF0
F16
16
30.7 GB
MaximumF0

Get started

Copy-paste commands to run Phi 4 reasoning vision 15B on your machine.

Run

lms load hf-jamesburton--phi-4-reasoning-vision-15b-gguf && lms server start

Opções de upgrade

Hardware que roda bem Phi 4 reasoning vision 15B

RX 7900 XT 20GBOpção econômica
20 GB VRAM (+4)800 GB/s (+288)
C
Raises estimated decode speed by about 70%.52.5 tok/s decodificação

Raises estimated decode speed by about 70%.

Adds memory headroom for longer context windows and future model growth.

~$899 MSRP

RX 7900 XTX 24GBMelhor custo-benefício
24 GB VRAM (+8)960 GB/s (+448)
C
Raises estimated decode speed by about 145%.75.5 tok/s decodificação

Raises estimated decode speed by about 145%.

Adds memory headroom for longer context windows and future model growth.

~$999 MSRP

AMD Instinct MI100 32GBUpgrade AMD
32 GB VRAM (+16)1228 GB/s (+716)
C
Raises estimated decode speed by about 183%.87.2 tok/s decodificação

Raises estimated decode speed by about 183%.

Adds memory headroom for longer context windows and future model growth.

~$11,500 MSRP

Frequently asked questions

Can RX 6800 16GB run Phi 4 reasoning vision 15B?

Yes, RX 6800 16GB can run Phi 4 reasoning vision 15B with a C grade (Tight fit). Expected decode speed: 30.8 tok/s.

How much VRAM does Phi 4 reasoning vision 15B need?

Phi 4 reasoning vision 15B (15B parameters) requires approximately 13.4 GB of memory with Q4_K_M quantization.

What is the best quantization for Phi 4 reasoning vision 15B?

The recommended quantization for Phi 4 reasoning vision 15B is Q4_K_M, which balances quality and memory efficiency.

What speed will Phi 4 reasoning vision 15B run at on RX 6800 16GB?

On RX 6800 16GB, Phi 4 reasoning vision 15B achieves approximately 30.8 tokens per second decode speed with a time-to-first-token of 6291ms using Q4_K_M quantization.

Can RX 6800 16GB run Phi 4 reasoning vision 15B for coding?

For coding workloads, Phi 4 reasoning vision 15B on RX 6800 16GB receives a C grade with 30.8 tok/s and 40K context.

What context window can Phi 4 reasoning vision 15B use on RX 6800 16GB?

On RX 6800 16GB, Phi 4 reasoning vision 15B can safely use up to 40K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.

See all results for RX 6800 16GBSee all hardware for Phi 4 reasoning vision 15B
Embed this result▼

Paste this snippet into any page to show a live fit card.

<iframe src="https://willitrunai.com/embed/hf-jamesburton--phi-4-reasoning-vision-15b-gguf-on-rx-6800-16gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>

Preview: