Compare/GLM-4.7 (Reasoning) vs Qwen3 14B (Reasoning)

GLM-4.7 (Reasoning)vsQwen3 14B (Reasoning)

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

Z AI

GLM-4.7 (Reasoning)

Input
$0.6/M
Output
$2.2/M
Speed
107 tok/s
TTFT
0.78s
Alibaba

Qwen3 14B (Reasoning)

Input
$0.235/M
Output
$2.22/M
Speed
64 tok/s
TTFT
1.19s

Winner by Category

Cheaper
Qwen3 14B (Reasoning)
Faster (tok/s)
GLM-4.7 (Reasoning)
Lower Latency
GLM-4.7 (Reasoning)
Benchmarks (11-1)
GLM-4.7 (Reasoning)

Pricing Comparison

MetricGLM-4.7 (Reasoning)Qwen3 14B (Reasoning)
Input ($/M tokens)$0.6$0.235
Output ($/M tokens)$2.2$2.22
Cost for 1M input + 100K output tokens:
GLM-4.7 (Reasoning)$0.82
Qwen3 14B (Reasoning)$0.46

Speed Comparison

Output Speed (tokens/s) — higher is better
GLM-4.7 (Reasoning)
107 tok/s
Qwen3 14B (Reasoning)
64 tok/s
Time to First Token (seconds) — lower is better
GLM-4.7 (Reasoning)
0.78s
Qwen3 14B (Reasoning)
1.19s

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
42.116.2
Coding Index
36.313.1
Math Index
95.055.7
GPQA Diamond
85.9%60.4%
MMLU-Pro
85.6%77.4%
LiveCodeBench
89.4%52.3%
AIME 2025
95.0%55.7%
MATH-500
96.1%
Humanity's Last Exam
25.1%4.3%
SciCode
45.1%31.6%
IFBench
67.9%40.5%
TerminalBench
31.8%3.8%
GLM-4.7 (Reasoning)11 wins
1 winsQwen3 14B (Reasoning)

Frequently Asked Questions

Which is cheaper, GLM-4.7 (Reasoning) or Qwen3 14B (Reasoning)?

Qwen3 14B (Reasoning) is cheaper overall. Its blended price (3:1 input/output ratio) is $0.73/M tokens vs $1.00/M for GLM-4.7 (Reasoning).

Which model performs better on benchmarks?

GLM-4.7 (Reasoning) wins 11 out of 12 benchmarks compared to 1 for Qwen3 14B (Reasoning). See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

GLM-4.7 (Reasoning) generates tokens faster at 107 tok/s vs 64 tok/s. GLM-4.7 (Reasoning) also has lower time-to-first-token (0.78s vs 1.19s).

When should I use GLM-4.7 (Reasoning) vs Qwen3 14B (Reasoning)?

Choose based on your priorities: Qwen3 14B (Reasoning) for lower cost, GLM-4.7 (Reasoning) for stronger benchmark performance, and GLM-4.7 (Reasoning) for faster generation. For latency-sensitive apps, check the TTFT comparison above.