Will It Run AI

Can DevStral 7B run on RTX 2080 Ti 11GB?

YES — Runs Great

A82Great
Estimated from fit model

DevStral 7B needs ~8.5 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
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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) 8.5 GB, 98.0 tok/s, Runs well
8.5 GB required11.0 GB available
77% VRAM used

Fit status

Runs well

Decode

98.0 tok/s

TTFT

1976 ms

Safe context

8K

Memory

8.5 GB / 11.0 GB

Memory breakdown

Weights4.3 GB
KV Cache2.0 GB
Runtime1.2 GB
Headroom1.1 GB

See how fast it feels

See how fast it feelsDevStral 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

WorkloadGradeFitDecodeTTFTContext
ChatARuns well98.0 tok/s1078 ms8K
CodingARuns well98.0 tok/s1976 ms8K
Agentic CodingARuns with offload98.0 tok/s2873 ms8K
ReasoningARuns well98.0 tok/s2335 ms8K
RAGARuns with offload98.0 tok/s3592 ms8K

Quantization options

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

QuantBitsVRAMQualityFit
Q2_K
2
2.7 GB
LowA75
Q3_K_S
3
3.4 GB
LowA76
NVFP4
4
3.9 GB
MediumA77
Q4_K_M
4
4.3 GB
MediumA77
Q5_K_M
5
5.0 GB
HighA78
Q6_K
6
5.7 GB
HighA78
Q8_0Best for your GPU
8
7.5 GB
Very HighA77
F16
16
14.3 GB
MaximumF0

Get started

Copy-paste commands to run DevStral 7B on your machine.

Run

ollama run devstral

Your hardware

More models your RTX 2080 Ti 11GB can run

ModelParamsGradeDecodeCapabilities
AlibabaQwen 3.5 9B9BS78.4 tok/s
AlibabaQwen 3 8B8BS88.2 tok/s
NVIDIANemotron Nano 8B8BS88.2 tok/s
InternLMInternVL2 8B8BS88.2 tok/s
MistralMinistral 3 8B8BA88.2 tok/s

Frequently asked questions

Can RTX 2080 Ti 11GB run DevStral 7B?

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

How much VRAM does DevStral 7B need?

DevStral 7B (7B parameters) requires approximately 8.5 GB of memory with Q4_K_M quantization.

What is the best quantization for DevStral 7B?

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

What speed will DevStral 7B run at on RTX 2080 Ti 11GB?

On RTX 2080 Ti 11GB, DevStral 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 DevStral 7B for coding?

For coding workloads, DevStral 7B on RTX 2080 Ti 11GB receives a A grade with 98.0 tok/s and 8K context.

What context window can DevStral 7B use on RTX 2080 Ti 11GB?

On RTX 2080 Ti 11GB, DevStral 7B can safely use up to 8K tokens of context. The model's official context limit is 8K, but available memory constrains the safe maximum.

See all results for RTX 2080 Ti 11GBSee all hardware for DevStral 7B
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