mistral-small:24b

llama · 23.6B · Q4_K_M

NVIDIA NVIDIA_DGX_Spark (Cortex-X925)

122 GB · Ubuntu 24.04.4 LTS

Tested on June 26, 2026

Top 43% Compare

Global Score

75 /100

Good

Hardware Fit

64/100

Quality

80/100

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Ollama

ollama pull mistral-small:24b

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ollama.com/library/mistral-small

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GGUF versions & quantizations

Hardware

Machine: NVIDIA NVIDIA_DGX_Spark
CPU: Cortex-X925
Cores: 20 total (20 perf)
Frequency: 3.35 GHz
RAM: 122 GB
GPU: Device 2e12
OS: Ubuntu 24.04.4 LTS
Arch: arm64
Power Mode: performance

Performance

Tokens/sec Tokens generated per second — higher is better: 14.3
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±0.1
First chunk latency Delay before the first streamed chunk arrives from runtime: 327 ms
Time to first token How fast the model starts responding — lower is better: 327 ms
Load time Time to load the model into memory before inference: 12.0 s
Memory usage RAM consumed during inference — percentage of total system memory: 18.5 GB (15%)
Total tokens Total number of tokens generated across all benchmark prompts: 1874

Score breakdown

Speed

14/50

Time to first token

20/20

Memory

30/30

Quality

Reasoning

16/20

Coding

18/20

Instruction following

14/20

Structured output

13/15

Math

9/15

Multilingual

10/10

Category levels

Reasoning: Strong Coding: Strong Instruction Following: Adequate Structured Output: Strong Math: Adequate Multilingual: Strong

Metadata

Spec version: 0.2.1
Runtime: Ollama 0.30.10
Model format: GGUF
Hardware profile: HIGH-END
Result hash: 231c5d1c74f845600655ec43c17923f659db83470e8266069a4dc3808d64b7c7

Interpretation

Hardware fit: 64/100. Overall suitability: GOOD (Global 75/100). Category profile: Reasoning: Strong, Coding: Strong, Instruction Following: Adequate, Structured Output: Strong, Math: Adequate, Multilingual: Strong.

Bench Environment

Thermal: nominal CPU load: avg 15% (peak 33%)

Run yours now

$ npm install -g metrillm@latest

$ metrillm

Requires Node 20+ and Ollama or LM Studio running

Or run without installing: npx metrillm@latest