Compare/Qwen3.6 27B (Reasoning) vs GLM-5 (Reasoning)

Qwen3.6 27B (Reasoning)vsGLM-5 (Reasoning)

Side-by-side comparison of pricing, 12 benchmarks, and generation speed.

Alibaba

Qwen3.6 27B (Reasoning)

Input
$0.6/M
Output
$3.6/M
Speed
68 tok/s
TTFT
1.77s
Z AI

GLM-5 (Reasoning)

Input
$1/M
Output
$3.2/M
Speed
66 tok/s
TTFT
0.85s

Winner by Category

Cheaper
Qwen3.6 27B (Reasoning)
Faster (tok/s)
Qwen3.6 27B (Reasoning)
Lower Latency
GLM-5 (Reasoning)
Benchmarks (1-6)
GLM-5 (Reasoning)

Pricing Comparison

MetricQwen3.6 27B (Reasoning)GLM-5 (Reasoning)
Input ($/M tokens)$0.6$1
Output ($/M tokens)$3.6$3.2
Cost for 1M input + 100K output tokens:
Qwen3.6 27B (Reasoning)$0.96
GLM-5 (Reasoning)$1.32

Speed Comparison

Output Speed (tokens/s) — higher is better
Qwen3.6 27B (Reasoning)
68 tok/s
GLM-5 (Reasoning)
66 tok/s
Time to First Token (seconds) — lower is better
Qwen3.6 27B (Reasoning)
1.77s
GLM-5 (Reasoning)
0.85s

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
45.849.8
Coding Index
36.544.2
Math Index
GPQA Diamond
84.2%82.0%
MMLU-Pro
LiveCodeBench
AIME 2025
MATH-500
Humanity's Last Exam
21.6%27.2%
SciCode
39.8%46.2%
IFBench
67.6%72.3%
TerminalBench
34.8%43.2%
Qwen3.6 27B (Reasoning)1 wins
6 winsGLM-5 (Reasoning)

Frequently Asked Questions

Which is cheaper, Qwen3.6 27B (Reasoning) or GLM-5 (Reasoning)?

Qwen3.6 27B (Reasoning) is cheaper overall. Its blended price (3:1 input/output ratio) is $1.35/M tokens vs $1.55/M for GLM-5 (Reasoning).

Which model performs better on benchmarks?

GLM-5 (Reasoning) wins 6 out of 12 benchmarks compared to 1 for Qwen3.6 27B (Reasoning). See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

Qwen3.6 27B (Reasoning) generates tokens faster at 68 tok/s vs 66 tok/s. However, GLM-5 (Reasoning) has lower time-to-first-token (0.85s vs 1.77s).

When should I use Qwen3.6 27B (Reasoning) vs GLM-5 (Reasoning)?

Choose based on your priorities: Qwen3.6 27B (Reasoning) for lower cost, GLM-5 (Reasoning) for stronger benchmark performance, and Qwen3.6 27B (Reasoning) for faster generation. For latency-sensitive apps, check the TTFT comparison above.