Will It Run AI

Can cognitivecomputations Dolphin3.0 R1 Mistral 24B run on RTX PRO 5000 Blackwell 48GB?

YES — Runs Great

C52Usable
Estimated from fit model

cognitivecomputations Dolphin3.0 R1 Mistral 24B needs ~23.5 GB VRAM. RTX PRO 5000 Blackwell 48GB has 48.0 GB. With Q4_K_M quantization, expect ~77 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: HighStack: 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) — 23.5 GB, 77.1 tok/s, Runs well
23.5 GB required48.0 GB available
49% VRAM used

Fit status

Runs well

Decode

77.1 tok/s

TTFT

2511 ms

Safe context

156K

Memory

23.5 GB / 48.0 GB

Memory breakdown

Weights14.6 GB
KV Cache2.8 GB
Runtime1.2 GB
Headroom4.8 GB

See how fast it feels

See how fast it feelscognitivecomputations Dolphin3.0 R1 Mistral 24B on RTX PRO 5000 Blackwell 48GB
1st promptCold start — includes initialization
>Solve: If a train travels at 60 mph for 2.5 hours, how far does it go?
Let me work through this step by step. Given information: - Speed = 60 mph (miles per hour) - Time = 2.5 hours Formula: Distance = Speed x Time Calculation: Distance = 60 mph x 2.5 h = 150 miles The train travels 150 miles. Double-check: at 60 mph the train covers 60 miles each hour. In half an hour it covers 30 miles. So in 2.5 hours: 60 + 60 + 30 = 150 miles. Confirmed.
2nd promptWarm — model ready, no init overhead
>What if the train stops for 20 minutes halfway?
The stop doesn't change the total distance covered while moving, but it affects total trip time. Breakdown: - First half: 1.25 hours at 60 mph = 75 miles - Stop: 20 minutes (no distance) - Second half: 1.25 hours at 60 mph = 75 miles Total distance: 150 miles (same) Total time: 2.5 h + 0.33 h = 2.83 hours Average speed: 150 / 2.83 = 53 mph The distance stays the same but average speed drops to 53 mph because of the stop.
Estimated: 77.1 tok/s decode · 2.5s TTFT (warm) · 193 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

No major red flags

This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.

Best improvement path

Performance by workload

WorkloadGradeFitDecodeTTFTContext
ChatCRuns well77.1 tok/s1369 ms156K
CodingCRuns well77.1 tok/s2511 ms156K
Agentic CodingCRuns well77.1 tok/s3652 ms156K
ReasoningCRuns well77.1 tok/s2967 ms156K
RAGCRuns well77.1 tok/s4565 ms156K

Quantization options

How cognitivecomputations Dolphin3.0 R1 Mistral 24B (24B params) fits at each quantization level on RTX PRO 5000 Blackwell 48GB (48.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
9.4 GB
LowC43
Q3_K_S
3
11.8 GB
LowC43
NVFP4
4
13.4 GB
MediumC44
Q4_K_M
4
14.6 GB
MediumC44
Q5_K_M
5
17.3 GB
HighC45
Q6_K
6
19.7 GB
HighC46
Q8_0Best for your GPU
8
25.7 GB
Very HighC48
F16
16
49.2 GB
MaximumF0

Get started

Copy-paste commands to run cognitivecomputations Dolphin3.0 R1 Mistral 24B on your machine.

Run

lms load hf-bartowski--cognitivecomputations-dolphin3-0-r1-mistral-24b-gguf && lms server start

Frequently asked questions

Can RTX PRO 5000 Blackwell 48GB run cognitivecomputations Dolphin3.0 R1 Mistral 24B?

Yes, RTX PRO 5000 Blackwell 48GB can run cognitivecomputations Dolphin3.0 R1 Mistral 24B with a C grade (Runs well). Expected decode speed: 77.1 tok/s.

How much VRAM does cognitivecomputations Dolphin3.0 R1 Mistral 24B need?

cognitivecomputations Dolphin3.0 R1 Mistral 24B (24B parameters) requires approximately 23.5 GB of memory with Q4_K_M quantization.

What is the best quantization for cognitivecomputations Dolphin3.0 R1 Mistral 24B?

The recommended quantization for cognitivecomputations Dolphin3.0 R1 Mistral 24B is Q4_K_M, which balances quality and memory efficiency.

What speed will cognitivecomputations Dolphin3.0 R1 Mistral 24B run at on RTX PRO 5000 Blackwell 48GB?

On RTX PRO 5000 Blackwell 48GB, cognitivecomputations Dolphin3.0 R1 Mistral 24B achieves approximately 77.1 tokens per second decode speed with a time-to-first-token of 2511ms using Q4_K_M quantization.

Can RTX PRO 5000 Blackwell 48GB run cognitivecomputations Dolphin3.0 R1 Mistral 24B for coding?

For coding workloads, cognitivecomputations Dolphin3.0 R1 Mistral 24B on RTX PRO 5000 Blackwell 48GB receives a C grade with 77.1 tok/s and 156K context.

What context window can cognitivecomputations Dolphin3.0 R1 Mistral 24B use on RTX PRO 5000 Blackwell 48GB?

On RTX PRO 5000 Blackwell 48GB, cognitivecomputations Dolphin3.0 R1 Mistral 24B can safely use up to 156K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.

See all results for RTX PRO 5000 Blackwell 48GBSee all hardware for cognitivecomputations Dolphin3.0 R1 Mistral 24B
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