llama3.3:70b-instruct-q4_K_M

llama · 70.6B · Q4_K_M

Dell Inc. Precision Tower 7910 (Intel Xeon® E5-2637 v3)

96 GB · Microsoft Windows 10 Pro 10.0.19045

Tested on August 20, 2026 · Submitted by Csaba

Top 88% Compare

Global Score

51 /100

Not Rec.

Hardware Fit

31/100

Quality

60/100

Get this model

🦙

Ollama

ollama pull llama3.3:70b-instruct-q4_K_M

View on Ollama Library

ollama.com/library/llama3.3

Get it in LM Studio

Search and download models directly from the app

🤗

Find on HuggingFace

GGUF versions & quantizations

Hardware

Machine: Dell Inc. Precision Tower 7910
CPU: Intel Xeon® E5-2637 v3
Cores: 16 total (16 perf)
Frequency: 3.5 GHz
RAM: 96 GB DDR4
GPU: NVIDIA GeForce RTX 3090, NVIDIA GeForce RTX 3060
OS: Microsoft Windows 10 Pro 10.0.19045
Arch: x64
Power Mode: balanced

Performance

Tokens/sec Tokens generated per second — higher is better: 1.7
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±0.0
First chunk latency Delay before the first streamed chunk arrives from runtime: 5.6 s
Time to first token How fast the model starts responding — lower is better: 5.6 s
Load time Time to load the model into memory before inference: 0.4 s
Memory usage RAM consumed during inference — percentage of total system memory: 50.3 GB (53%)
Total tokens Total number of tokens generated across all benchmark prompts: 389

Score breakdown

Speed

2/50

Time to first token

5/20

Memory

24/30

Quality

Reasoning

17/20

Coding

6/20

Instruction following

6/20

Structured output

11/15

Math

11/15

Multilingual

9/10

Category levels

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

Metadata

Spec version: 0.2.1
Runtime: Ollama 0.32.1
Model format: GGUF
Hardware profile: HIGH-END
Result hash: fc925a43e4145dde354f9f3f1df24a95d7cd86ab845df109221f8ad0d7353e10

Interpretation

Hardware fit: 31/100. Overall suitability: NOT RECOMMENDED (Global 51/100). Category profile: Reasoning: Strong, Coding: Weak, Instruction Following: Weak, Structured Output: Adequate, Math: Adequate, Multilingual: Strong.

Disqualifiers

Token speed too low: 1.7 tok/s (minimum: 7 tok/s for HIGH-END profile)

Bench Environment

CPU load: avg 35% (peak 42%)

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