Can Qwen 2.5 Coder 7B run on RTX 2080 Ti 11GB?

YES — Runs Great

A76Great

Estimated from fit model

Qwen 2.5 Coder 7B needs ~7.4 GB VRAM. RTX 2080 Ti 11GB has 11.0 GB. With Q4_K_M quantization, expect ~98 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: MediumStack: 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) — 7.4 GB, 98.0 tok/s, Runs well

7.4 GB required11.0 GB available

67% VRAM used

Fit status

Runs well

Decode

98.0 tok/s

TTFT

1976 ms

Safe context

83K

Memory

7.4 GB / 11.0 GB

Memory breakdown

Weights4.3 GB

KV Cache0.9 GB

Runtime1.2 GB

Headroom1.1 GB

See how fast it feels

See how fast it feelsQwen 2.5 Coder 7B on RTX 2080 Ti 11GB
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: 98.0 tok/s decode · 2.0s TTFT (warm) · 245 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	A	Runs well	98.0 tok/s	1078 ms	83K
Coding	A	Runs well	98.0 tok/s	1976 ms	83K
Agentic Coding	A	Runs well	98.0 tok/s	2873 ms	83K
Reasoning	A	Runs well	98.0 tok/s	2335 ms	83K
RAG	A	Runs well	98.0 tok/s	3592 ms	83K

Quantization options

How Qwen 2.5 Coder 7B (7B params) fits at each quantization level on RTX 2080 Ti 11GB (11.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	2.7 GB	Low	B70
Q3_K_S	3	3.4 GB	Low	A71
NVFP4	4

Get started

Copy-paste commands to run Qwen 2.5 Coder 7B on your machine.

Run

ollama run qwen2.5-coder:7b

Your hardware

More models your RTX 2080 Ti 11GB can run

Model	Params	Grade	Decode	Capabilities
Qwen 3.5 9B	9B	S	78.4 tok/s
Qwen 3 8B	8B	S	88.2 tok/s

Frequently asked questions

Can RTX 2080 Ti 11GB run Qwen 2.5 Coder 7B?

Yes, RTX 2080 Ti 11GB can run Qwen 2.5 Coder 7B with a A grade (Runs well). Expected decode speed: 98.0 tok/s.

How much VRAM does Qwen 2.5 Coder 7B need?

Qwen 2.5 Coder 7B (7B parameters) requires approximately 7.4 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen 2.5 Coder 7B?

The recommended quantization for Qwen 2.5 Coder 7B is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen 2.5 Coder 7B run at on RTX 2080 Ti 11GB?

On RTX 2080 Ti 11GB, Qwen 2.5 Coder 7B achieves approximately 98.0 tokens per second decode speed with a time-to-first-token of 1976ms using Q4_K_M quantization.

Can RTX 2080 Ti 11GB run Qwen 2.5 Coder 7B for coding?

For coding workloads, Qwen 2.5 Coder 7B on RTX 2080 Ti 11GB receives a A grade with 98.0 tok/s and 83K context.

What context window can Qwen 2.5 Coder 7B use on RTX 2080 Ti 11GB?

On RTX 2080 Ti 11GB, Qwen 2.5 Coder 7B can safely use up to 83K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

See all results for RTX 2080 Ti 11GB See all hardware for Qwen 2.5 Coder 7B

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