Can Qwen 2.5 Coder 3B run on GTX 1660 Ti 6GB?

YES — With Offload

A77Great

Estimated from fit model

Qwen 2.5 Coder 3B needs ~5.8 GB VRAM. GTX 1660 Ti 6GB has 6.0 GB. With Q4_K_M quantization, expect ~42 tok/s.

Runtime: OllamaCapacity: OffloadBandwidth: 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) — 5.8 GB, 42.0 tok/s, Runs with offload

5.8 GB required6.0 GB available

97% VRAM used

Fit status

Runs with offload

Decode

42.0 tok/s

TTFT

4610 ms

Safe context

17K

Memory

5.8 GB / 6.0 GB

Memory breakdown

Weights1.8 GB

KV Cache2.2 GB

Runtime1.2 GB

Headroom0.6 GB

See how fast it feels

See how fast it feelsQwen 2.5 Coder 3B on GTX 1660 Ti 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: 42.0 tok/s decode · 4.6s TTFT (warm) · 105 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.

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

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	A	Runs well	42.0 tok/s	2514 ms	17K
Coding	A	Runs with offload	42.0 tok/s	4610 ms	17K
Agentic Coding	F	Too heavy	35.0 tok/s	8044 ms	17K
Reasoning	A	Runs with offload	42.0 tok/s	5448 ms	17K
RAG	F	Too heavy	35.0 tok/s	10055 ms	17K

Inference speed

Qwen 2.5 Coder 3B inference speed — tokens per second by GPU & Mac

Estimated decode speed (tokens/sec) for Qwen 2.5 Coder 3B at Q4_K_M across popular GPUs and Apple Silicon, using the fastest local runtime per device. Fastest is RTX 5090 32GB at ~57 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	57.0	Fits
RTX 4090 24GB	24 GB	Q4_K_M	48.0	Fits
RTX 4080 Super 16GB	16 GB	Q4_K_M	48.0	Fits
RTX 4060 8GB	8 GB	Q4_K_M	48.0	Fits
RTX 3090 24GB	24 GB	Q4_K_M	42.0	Fits
RTX 4070 12GB	12 GB	Q4_K_M	42.0	Fits
RTX 3060 12GB	12 GB	Q4_K_M	42.0	Fits
RX 7900 XTX 24GB	24 GB	Q4_K_M	42.0	Fits
MacBook Pro M4 Max 128GB	128 GB	Q4_K_M	42.0	Fits
Mac Studio M3 Ultra 256GB	256 GB	Q4_K_M	42.0	Fits
Mac Studio M2 Ultra 128GB	128 GB	Q4_K_M	42.0	Fits
Mac Studio M1 Ultra 128GB	128 GB	Q4_K_M	42.0	Fits
MacBook Pro M4 Max 64GB	64 GB	Q4_K_M	42.0	Fits
MacBook Pro M3 Max 64GB	64 GB	Q4_K_M	42.0	Fits
MacBook Pro M1 Max 64GB	64 GB	Q4_K_M	42.0	Fits
MacBook Pro M4 Pro 48GB	48 GB	Q4_K_M	42.0	Fits

Estimates for single-stream decoding at Q4_K_M; real tokens/sec varies with prompt length, context, batch size, and runtime build. Prompt processing (prefill) is faster than the decode figures shown here.

Quantization options

How Qwen 2.5 Coder 3B (3B params) fits at each quantization level on GTX 1660 Ti 6GB (6.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	1.2 GB	Low	A79
Q3_K_S	3	1.5 GB	Low	A80
NVFP4	4	1.7 GB	Medium	A80
Q4_K_M	4	1.8 GB	Medium	A80
Q5_K_M	5	2.2 GB	High	A80
Q6_K	6	2.5 GB	High	A80
Q8_0Best for your GPU	8	3.2 GB	Very High	A79
F16	16	6.1 GB	Maximum	F0

Get started

Copy-paste commands to run Qwen 2.5 Coder 3B on your machine.

Run

ollama run qwen2.5-coder:3b

Your hardware

More models your GTX 1660 Ti 6GB can run

Model	Params	Grade	Decode
Qwen 3.5 4B	4B	A	43.6 tok/s
Phi-4 Mini Reasoning 4B	3.8B	S	53.2 tok/s
Qwen 3 4B	4B	A	43.6 tok/s
Qwen 2.5 VL 7B	7B	B	21.4 tok/s
Qwen 2.5 7B	7B	B	21.4 tok/s

Frequently asked questions

Can GTX 1660 Ti 6GB run Qwen 2.5 Coder 3B?

Yes, GTX 1660 Ti 6GB can run Qwen 2.5 Coder 3B with a A grade (Runs with offload). Expected decode speed: 42.0 tok/s.

How much VRAM does Qwen 2.5 Coder 3B need?

Qwen 2.5 Coder 3B (3B parameters) requires approximately 5.8 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen 2.5 Coder 3B?

The recommended quantization for Qwen 2.5 Coder 3B is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen 2.5 Coder 3B run at on GTX 1660 Ti 6GB?

On GTX 1660 Ti 6GB, Qwen 2.5 Coder 3B achieves approximately 42.0 tokens per second decode speed with a time-to-first-token of 4610ms using Q4_K_M quantization.

Can GTX 1660 Ti 6GB run Qwen 2.5 Coder 3B for coding?

For coding workloads, Qwen 2.5 Coder 3B on GTX 1660 Ti 6GB receives a A grade with 42.0 tok/s and 17K context.

What context window can Qwen 2.5 Coder 3B use on GTX 1660 Ti 6GB?

On GTX 1660 Ti 6GB, Qwen 2.5 Coder 3B 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 Qwen 2.5 Coder 3B feels slow on GTX 1660 Ti 6GB?

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

See all results for GTX 1660 Ti 6GB See all hardware for Qwen 2.5 Coder 3B

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Preview:

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.

Older PCIe generation

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

Workload

Grade

Fit

Decode

TTFT

Context

Chat

Runs well

42.0 tok/s

2514 ms

17K

Coding

Runs with offload

42.0 tok/s

4610 ms

17K

Agentic Coding

Too heavy

35.0 tok/s

8044 ms

17K

Reasoning

Runs with offload

42.0 tok/s

5448 ms

17K

RAG

Too heavy

35.0 tok/s

10055 ms

17K

Qwen 2.5 Coder 3B inference speed — tokens per second by GPU & Mac

GPU / Mac

Memory

Quant

Speed (tok/s)

Fits?

RTX 5090 32GB

32 GB

Q4_K_M

57.0

Fits

RTX 4090 24GB

24 GB

Q4_K_M

48.0

Fits

RTX 4080 Super 16GB

16 GB

Q4_K_M

48.0

Fits

RTX 4060 8GB

8 GB

Q4_K_M

48.0

Fits

RTX 3090 24GB

24 GB

Q4_K_M

42.0

Fits

RTX 4070 12GB

12 GB

Q4_K_M

42.0

Fits

RTX 3060 12GB

12 GB

Q4_K_M

42.0

Fits

RX 7900 XTX 24GB

24 GB

Q4_K_M

42.0

Fits

MacBook Pro M4 Max 128GB

128 GB

Q4_K_M

42.0

Fits

Mac Studio M3 Ultra 256GB

256 GB

Q4_K_M

42.0

Fits

Mac Studio M2 Ultra 128GB

128 GB

Q4_K_M

42.0

Fits

Mac Studio M1 Ultra 128GB

128 GB

Q4_K_M

42.0

Fits

MacBook Pro M4 Max 64GB

64 GB

Q4_K_M

42.0

Fits

MacBook Pro M3 Max 64GB

64 GB

Q4_K_M

42.0

Fits

MacBook Pro M1 Max 64GB

64 GB

Q4_K_M

42.0

Fits

MacBook Pro M4 Pro 48GB

48 GB

Q4_K_M

42.0

Fits

Quantization options

How Qwen 2.5 Coder 3B (3B params) fits at each quantization level on GTX 1660 Ti 6GB (6.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	1.2 GB	Low	A79
Q3_K_S	3	1.5 GB	Low	A80
NVFP4	4	1.7 GB	Medium	A80
Q4_K_M	4	1.8 GB	Medium	A80
Q5_K_M	5	2.2 GB	High	A80
Q6_K	6	2.5 GB	High	A80
Q8_0Best for your GPU	8	3.2 GB	Very High	A79
F16	16	6.1 GB	Maximum	F0

Model

Params

Grade

Decode

Capabilities

Qwen 3.5 4B

43.6 tok/s

Phi-4 Mini Reasoning 4B

3.8B

53.2 tok/s

Qwen 3 4B

43.6 tok/s

Qwen 2.5 VL 7B

21.4 tok/s

Qwen 2.5 7B

21.4 tok/s

Frequently asked questions

Can GTX 1660 Ti 6GB run Qwen 2.5 Coder 3B?

Yes, GTX 1660 Ti 6GB can run Qwen 2.5 Coder 3B with a A grade (Runs with offload). Expected decode speed: 42.0 tok/s.

How much VRAM does Qwen 2.5 Coder 3B need?

Qwen 2.5 Coder 3B (3B parameters) requires approximately 5.8 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen 2.5 Coder 3B?

The recommended quantization for Qwen 2.5 Coder 3B is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen 2.5 Coder 3B run at on GTX 1660 Ti 6GB?

On GTX 1660 Ti 6GB, Qwen 2.5 Coder 3B achieves approximately 42.0 tokens per second decode speed with a time-to-first-token of 4610ms using Q4_K_M quantization.

Can GTX 1660 Ti 6GB run Qwen 2.5 Coder 3B for coding?

For coding workloads, Qwen 2.5 Coder 3B on GTX 1660 Ti 6GB receives a A grade with 42.0 tok/s and 17K context.

What context window can Qwen 2.5 Coder 3B use on GTX 1660 Ti 6GB?

On GTX 1660 Ti 6GB, Qwen 2.5 Coder 3B 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 Qwen 2.5 Coder 3B feels slow on GTX 1660 Ti 6GB?

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