Can Antares 1B run on RTX 3050 Ti Laptop 4GB?

Q: What should I upgrade first if Antares 1B feels slow on RTX 3050 Ti Laptop 4GB?

Buy headroom, not only minimum fit. A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.

YES — With Offload

B67Good

Estimated from fit model

Antares 1B needs ~3.9 GB VRAM. RTX 3050 Ti Laptop 4GB has 4.0 GB. With Q4_K_M quantization, expect ~26 tok/s.

Runtime: OllamaCapacity: OffloadBandwidth: Very lowStack: BasicBottleneck: Memory bandwidth

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) — 3.9 GB, 25.8 tok/s, Runs with offload

3.9 GB required4.0 GB available

98% VRAM used

Fit status

Runs with offload

Decode

25.8 tok/s

TTFT

7516 ms

Safe context

17K

Memory

3.9 GB / 4.0 GB

Memory breakdown

Weights1.1 GB

KV Cache1.2 GB

Runtime1.2 GB

Headroom0.4 GB

See how fast it feels

See how fast it feelsAntares 1B on RTX 3050 Ti Laptop 4GB
1st promptCold start — includes initialization
>Write a Python function to sort a list
Here's a Python function that sorts a list using quicksort:

def quicksort(arr):
    if len(arr) <= 1:
        return arr
    pivot = arr[len(arr) // 2]
    left   = [x for x in arr if x < pivot]
    middle = [x for x in arr if x == pivot]
    right  = [x for x in arr if x > pivot]
    return quicksort(left) + middle + quicksort(right)

# Example usage
numbers = [3, 6, 8, 10, 1, 2, 1]
print(quicksort(numbers))  # [1, 1, 2, 3, 6, 8, 10]

The algorithm picks a pivot, partitions the list into smaller, equal, and larger elements, then recursively sorts each partition and concatenates the results.
2nd promptWarm — model ready, no init overhead
>Now add type hints and a docstring
def quicksort(arr: list[int]) -> list[int]:
    """Sort a list using the quicksort algorithm.

    Args:
        arr: List of integers to sort.

    Returns:
        A new sorted list.
    """
    if len(arr) <= 1:
        return arr
    pivot = arr[len(arr) // 2]
    left   = [x for x in arr if x < pivot]
    middle = [x for x in arr if x == pivot]
    right  = [x for x in arr if x > pivot]
    return quicksort(left) + middle + quicksort(right)

Added type hints for the input and return type, plus a Google-style docstring.
Estimated: 25.8 tok/s decode · 7.5s TTFT (warm) · 64 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

Very little memory headroom

You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.

Best improvement path

Buy headroom, not only minimum fit

A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.

Performance by workload

Workload	Grade	Fit	Decode	TTFT	Context
Chat	B	Tight fit	25.8 tok/s	4099 ms	17K
Coding	B	Runs with offload	25.8 tok/s	7516 ms	17K
Agentic Coding	F	Too heavy	25.8 tok/s	10932 ms	17K
Reasoning	B	Runs with offload	25.8 tok/s	8882 ms	17K
RAG	F	Too heavy	25.8 tok/s	13665 ms	17K

Inference speed

Antares 1B inference speed — tokens per second by GPU & Mac

Estimated decode speed (tokens/sec) for Antares 1B at Q4_K_M across popular GPUs and Apple Silicon, using the fastest local runtime per device. Fastest is RTX 5090 32GB at ~35 tok/s. Speed is memory-bandwidth bound, so cards that fit the whole model in VRAM run far faster than ones that offload to system RAM.

GPU / Mac	Memory	Quant	Speed (tok/s)	Fits?
RTX 5090 32GB	32 GB	Q4_K_M	35.0	Fits
RTX 4090 24GB	24 GB	Q4_K_M	29.4	Fits
RTX 4080 Super 16GB	16 GB	Q4_K_M	29.4

Quantization options

How Antares 1B (1.840000033378601B params) fits at each quantization level on RTX 3050 Ti Laptop 4GB (4.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q1_0_G128	1.125	0.3 GB	Very Low	A72
Q2_0_G128	1.71	0.5 GB	Low	A73
Q2_K	2

Get started

Copy-paste commands to run Antares 1B on your machine.

Run

docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
  --hf-repo "fdtn-ai/antares-1b" \
  --hf-file "antares-1b-Q4_K_M.gguf" \
  -c 4096 -ngl 99

Upgrade options

Hardware that runs Antares 1B well

GTX 1660 Super 6GBBudget pick

6 GB VRAM (+2)336 GB/s (+144)

Adds memory headroom for longer context windows and future model growth.25.8 tok/s decode

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

~$229 MSRP

GTX 1060 6GBBest value

6 GB VRAM (+2)

Adds memory headroom for longer context windows and future model growth.25.8 tok/s decode

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

~$249 MSRP

GTX 1660 Ti 6GBNVIDIA upgrade

6 GB VRAM (+2)288 GB/s (+96)

Adds memory headroom for longer context windows and future model growth.25.8 tok/s decode

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

~$279 MSRP

Frequently asked questions

Can RTX 3050 Ti Laptop 4GB run Antares 1B?

Yes, RTX 3050 Ti Laptop 4GB can run Antares 1B with a B grade (Runs with offload). Expected decode speed: 25.8 tok/s.

How much VRAM does Antares 1B need?

Antares 1B (1.840000033378601B parameters) requires approximately 3.9 GB of memory with Q4_K_M quantization.

What is the best quantization for Antares 1B?

The recommended quantization for Antares 1B is Q4_K_M, which balances quality and memory efficiency.

What speed will Antares 1B run at on RTX 3050 Ti Laptop 4GB?

On RTX 3050 Ti Laptop 4GB, Antares 1B achieves approximately 25.8 tokens per second decode speed with a time-to-first-token of 7516ms using Q4_K_M quantization.

Can RTX 3050 Ti Laptop 4GB run Antares 1B for coding?

For coding workloads, Antares 1B on RTX 3050 Ti Laptop 4GB receives a B grade with 25.8 tok/s and 17K context.

What context window can Antares 1B use on RTX 3050 Ti Laptop 4GB?

On RTX 3050 Ti Laptop 4GB, Antares 1B can safely use up to 17K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

What should I upgrade first if Antares 1B feels slow on RTX 3050 Ti Laptop 4GB?

See all results for RTX 3050 Ti Laptop 4GB See all hardware for Antares 1B

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