Can cognitivecomputations Dolphin3.0 R1 Mistral 24B run on AMD Instinct MI100 32GB?

YES — Runs Great

C55Usable

Estimated from fit model

cognitivecomputations Dolphin3.0 R1 Mistral 24B needs ~21.6 GB VRAM. AMD Instinct MI100 32GB has 32.0 GB. With Q4_K_M quantization, expect ~55 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: HighStack: StandardBottleneck: 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) — 21.6 GB, 54.5 tok/s, Runs well

21.6 GB required32.0 GB available

68% VRAM used

Fit status

Runs well

Decode

54.5 tok/s

TTFT

3551 ms

Safe context

75K

Memory

21.6 GB / 32.0 GB

Memory breakdown

Weights14.6 GB

KV Cache2.8 GB

Runtime0.9 GB

Headroom3.2 GB

See how fast it feels

See how fast it feelscognitivecomputations Dolphin3.0 R1 Mistral 24B on AMD Instinct MI100 32GB
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: 54.5 tok/s decode · 3.6s TTFT (warm) · 136 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

Workload	Grade	Fit	Decode	TTFT	Context
Chat	C	Runs well	54.5 tok/s	1937 ms	75K
Coding	C	Runs well	54.5 tok/s	3551 ms	75K
Agentic Coding	B	Runs well	54.5 tok/s	5165 ms	75K
Reasoning	C	Runs well	54.5 tok/s	4196 ms	75K
RAG	B	Runs well	54.5 tok/s	6456 ms	75K

Quantization options

How cognitivecomputations Dolphin3.0 R1 Mistral 24B (24B params) fits at each quantization level on AMD Instinct MI100 32GB (32.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	9.4 GB	Low	C46
Q3_K_S	3	11.8 GB	Low	C47
NVFP4	4	13.4 GB	Medium	C48
Q4_K_M	4	14.6 GB	Medium	C48
Q5_K_M	5	17.3 GB	High	C49
Q6_K	6	19.7 GB	High	C49
Q8_0Best for your GPU	8	25.7 GB	Very High	C48
F16	16	49.2 GB	Maximum	F0

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 AMD Instinct MI100 32GB run cognitivecomputations Dolphin3.0 R1 Mistral 24B?

Yes, AMD Instinct MI100 32GB can run cognitivecomputations Dolphin3.0 R1 Mistral 24B with a C grade (Runs well). Expected decode speed: 54.5 tok/s.

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

cognitivecomputations Dolphin3.0 R1 Mistral 24B (24B parameters) requires approximately 21.6 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 AMD Instinct MI100 32GB?

On AMD Instinct MI100 32GB, cognitivecomputations Dolphin3.0 R1 Mistral 24B achieves approximately 54.5 tokens per second decode speed with a time-to-first-token of 3551ms using Q4_K_M quantization.

Can AMD Instinct MI100 32GB run cognitivecomputations Dolphin3.0 R1 Mistral 24B for coding?

For coding workloads, cognitivecomputations Dolphin3.0 R1 Mistral 24B on AMD Instinct MI100 32GB receives a C grade with 54.5 tok/s and 75K context.

What context window can cognitivecomputations Dolphin3.0 R1 Mistral 24B use on AMD Instinct MI100 32GB?

On AMD Instinct MI100 32GB, cognitivecomputations Dolphin3.0 R1 Mistral 24B can safely use up to 75K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.

See all results for AMD Instinct MI100 32GB See all hardware for cognitivecomputations Dolphin3.0 R1 Mistral 24B

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