Back to leaderboard

glm-4.7-flash:bf16

OLLAMA GGUF

deepseek2 · 29.9B · F16

Good

Jun 26, 2026 · Cortex-X925

qwen/qwen3.8-27b

LM-STUDIO MLX

qwen3_5 · 27B · 8bit

Excellent

Aug 18, 2026 · Apple M4 Max

Global Score
76 vs 81
Hardware Fit
73 vs 68
Quality Score
77 vs 87

Hardware

glm-4.7-flash:bf16 qwen/qwen3.8-27b
MachineNVIDIA NVIDIA_DGX_SparkMacBook Pro
CPUCortex-X925Apple M4 Max
Cores2016
RAM122 GB128 GB
GPUDevice 2e12Apple M4 Max
OSUbuntu 24.04.4 LTSmacOS 26.5.2
Archarm64arm64
Power Modeperformancebalanced

Performance

glm-4.7-flash:bf16 qwen/qwen3.8-27b
Tokens/sec25.816.4
First chunk605 ms5 ms
TTFT605 ms742 ms
Load time44.2 sN/A
Memory usage57.0 GB38.5 GB
Memory %47%30%

HW Fit Score Breakdown

glm-4.7-flash:bf16

Speed
27/50
TTFT
20/20
Memory
26/30

qwen/qwen3.8-27b

Speed
18/50
TTFT
20/20
Memory
30/30

Quality

glm-4.7-flash:bf16

Reasoning
13/20
Coding
17/20
Instruction
12/20
Structured
15/15
Math
10/15
Multilingual
10/10
Reasoning: Adequate Coding: Strong Instruction Following: Adequate Structured Output: Strong Math: Adequate Multilingual: Strong

qwen/qwen3.8-27b

Reasoning
17/20
Coding
18/20
Instruction
16/20
Structured
15/15
Math
11/15
Multilingual
10/10
Reasoning: Strong Coding: Strong Instruction Following: Strong Structured Output: Strong Math: Adequate Multilingual: Strong
View glm-4.7-flash:bf16 details | View qwen/qwen3.8-27b details

Run yours and compare

$ npm install -g metrillm@latest
$ metrillm

Requires Node 20+ and Ollama or LM Studio running

Or run without installing: npx metrillm@latest