Compare/GLM-4.7 (Reasoning) vs MiniMax M1 80k

GLM-4.7 (Reasoning)vsMiniMax M1 80k

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
80 tok/s
TTFT
0.72s
MiniMax

MiniMax M1 80k

Input
$0.55/M
Output
$2.2/M
Speed
TTFT

Winner by Category

Cheaper
MiniMax M1 80k
Faster (tok/s)
GLM-4.7 (Reasoning)
Lower Latency
MiniMax M1 80k
Benchmarks (11-1)
GLM-4.7 (Reasoning)

Pricing Comparison

MetricGLM-4.7 (Reasoning)MiniMax M1 80k
Input ($/M tokens)$0.6$0.55
Output ($/M tokens)$2.2$2.2
Cost for 1M input + 100K output tokens:
GLM-4.7 (Reasoning)$0.82
MiniMax M1 80k$0.77

Speed Comparison

Output Speed (tokens/s) — higher is better
GLM-4.7 (Reasoning)
80 tok/s
MiniMax M1 80k
Time to First Token (seconds) — lower is better
GLM-4.7 (Reasoning)
0.72s
MiniMax M1 80k

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
42.124.4
Coding Index
36.314.5
Math Index
95.061.0
GPQA Diamond
85.9%69.7%
MMLU-Pro
85.6%81.6%
LiveCodeBench
89.4%71.1%
AIME 2025
95.0%61.0%
MATH-500
98.0%
Humanity's Last Exam
25.1%8.2%
SciCode
45.1%37.4%
IFBench
67.9%41.8%
TerminalBench
31.8%3.0%
GLM-4.7 (Reasoning)11 wins
1 winsMiniMax M1 80k

Frequently Asked Questions

Which is cheaper, GLM-4.7 (Reasoning) or MiniMax M1 80k?

MiniMax M1 80k is cheaper overall. Its blended price (3:1 input/output ratio) is $0.96/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 MiniMax M1 80k. 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 80 tok/s vs 0 tok/s. However, MiniMax M1 80k has lower time-to-first-token (0.00s vs 0.72s).

When should I use GLM-4.7 (Reasoning) vs MiniMax M1 80k?

Choose based on your priorities: MiniMax M1 80k 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.