Can Antares 1B run on GTX 1660 Super 6GB?

YES — Runs Great

B69Good

Estimated from fit model

Antares 1B needs ~4.1 GB VRAM. GTX 1660 Super 6GB has 6.0 GB. With Q4_K_M quantization, expect ~26 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: LowStack: BasicBottleneck: 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) — 4.1 GB, 25.8 tok/s, Runs well

4.1 GB required6.0 GB available

68% VRAM used

Fit status

Runs well

Decode

25.8 tok/s

TTFT

7516 ms

Safe context

40K

Memory

4.1 GB / 6.0 GB

Memory breakdown

Weights1.1 GB

KV Cache1.2 GB

Runtime1.2 GB

Headroom0.6 GB

See how fast it feels

See how fast it feelsAntares 1B on GTX 1660 Super 6GB
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.

Older PCIe generation

PCIe 3.0 is workable, but it compounds the penalty when you offload heavily or try to scale across multiple cards.

Best improvement path

Performance by workload

Workload	Grade	Fit	Decode	TTFT	Context
Chat	B	Runs well	25.8 tok/s	4099 ms	40K
Coding	B	Runs well	25.8 tok/s	7516 ms	40K
Agentic Coding	B	Tight fit	25.8 tok/s	10932 ms	40K
Reasoning	B	Runs well	25.8 tok/s	8882 ms	40K
RAG	B	Tight fit	25.8 tok/s	13665 ms	40K

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 GTX 1660 Super 6GB (6.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q1_0_G128	1.125	0.3 GB	Very Low	B68
Q2_0_G128	1.71	0.5 GB	Low	B68
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

Frequently asked questions

Can GTX 1660 Super 6GB run Antares 1B?

Yes, GTX 1660 Super 6GB can run Antares 1B with a B grade (Runs well). Expected decode speed: 25.8 tok/s.

How much VRAM does Antares 1B need?

Antares 1B (1.840000033378601B parameters) requires approximately 4.1 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 GTX 1660 Super 6GB?

On GTX 1660 Super 6GB, 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 GTX 1660 Super 6GB run Antares 1B for coding?

For coding workloads, Antares 1B on GTX 1660 Super 6GB receives a B grade with 25.8 tok/s and 40K context.

What context window can Antares 1B use on GTX 1660 Super 6GB?

On GTX 1660 Super 6GB, Antares 1B can safely use up to 40K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

See all results for GTX 1660 Super 6GB See all hardware for Antares 1B

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