Will It Run AI

Can Helply 10.2b chat i1 run on RX 7700 XT 12GB?

YES — Runs Great

C54Usable
Estimated from fit model

Helply 10.2b chat i1 needs ~9.5 GB VRAM. RX 7700 XT 12GB has 12.0 GB. With Q4_K_M quantization, expect ~42 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) — 9.5 GB, 41.7 tok/s, Runs well
9.5 GB required12.0 GB available
79% VRAM used

Fit status

Runs well

Decode

41.7 tok/s

TTFT

4647 ms

Safe context

49K

Memory

9.5 GB / 12.0 GB

Memory breakdown

Weights6.2 GB
KV Cache1.2 GB
Runtime0.9 GB
Headroom1.2 GB

See how fast it feels

See how fast it feelsHelply 10.2b chat i1 on RX 7700 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: 41.7 tok/s decode · 4.6s TTFT (warm) · 104 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 well41.7 tok/s2535 ms49K
CodingCRuns well41.7 tok/s4647 ms49K
Agentic CodingCTight fit41.7 tok/s6760 ms49K
ReasoningCRuns well41.7 tok/s5492 ms49K
RAGCTight fit41.7 tok/s8450 ms49K

Quantization options

How Helply 10.2b chat i1 (10.199999809265137B params) fits at each quantization level on RX 7700 XT 12GB (12.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
4.0 GB
LowC50
Q3_K_S
3
5.0 GB
LowC51
NVFP4
4
5.7 GB
MediumC52
Q4_K_M
4
6.2 GB
MediumC52
Q5_K_M
5
7.3 GB
HighC51
Q6_KBest for your GPU
6
8.4 GB
HighC51
Q8_0
8
10.9 GB
Very HighF0
F16
16
20.9 GB
MaximumF0

Get started

Copy-paste commands to run Helply 10.2b chat i1 on your machine.

Run

lms load hf-mradermacher--helply-10-2b-chat-i1-gguf && lms server start

Opções de upgrade

Hardware que roda bem Helply 10.2b chat i1

NVIDIARTX 5070 Ti 16GBOpção econômica
16 GB VRAM (+4)896 GB/s (+464)
C
Raises estimated decode speed by about 114%.89.4 tok/s decodificação

Raises estimated decode speed by about 114%.

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

~$749 MSRP

NVIDIARTX 4070 Ti Super 16GBMelhor custo-benefício
16 GB VRAM (+4)672 GB/s (+240)
C
Raises estimated decode speed by about 118%.90.7 tok/s decodificação

Raises estimated decode speed by about 118%.

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

~$799 MSRP

Frequently asked questions

Can RX 7700 XT 12GB run Helply 10.2b chat i1?

Yes, RX 7700 XT 12GB can run Helply 10.2b chat i1 with a C grade (Runs well). Expected decode speed: 41.7 tok/s.

How much VRAM does Helply 10.2b chat i1 need?

Helply 10.2b chat i1 (10.199999809265137B parameters) requires approximately 9.5 GB of memory with Q4_K_M quantization.

What is the best quantization for Helply 10.2b chat i1?

The recommended quantization for Helply 10.2b chat i1 is Q4_K_M, which balances quality and memory efficiency.

What speed will Helply 10.2b chat i1 run at on RX 7700 XT 12GB?

On RX 7700 XT 12GB, Helply 10.2b chat i1 achieves approximately 41.7 tokens per second decode speed with a time-to-first-token of 4647ms using Q4_K_M quantization.

Can RX 7700 XT 12GB run Helply 10.2b chat i1 for coding?

For coding workloads, Helply 10.2b chat i1 on RX 7700 XT 12GB receives a C grade with 41.7 tok/s and 49K context.

What context window can Helply 10.2b chat i1 use on RX 7700 XT 12GB?

On RX 7700 XT 12GB, Helply 10.2b chat i1 can safely use up to 49K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.

See all results for RX 7700 XT 12GBSee all hardware for Helply 10.2b chat i1
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