GLM-4.7 (Reasoning) vs GLM-4.7-Flash (Non-reasoning): The Ultimate Performance & Pricing Comparison

Deep dive into reasoning, benchmarks, and latency insights.

The Final Verdict in the GLM-4.7 (Reasoning) vs GLM-4.7-Flash (Non-reasoning) Showdown

After a comprehensive analysis, GLM-4.7 (Reasoning) emerges as the superior choice for users prioritizing raw intelligence and reasoning. However, GLM-4.7-Flash (Non-reasoning) remains a highly competitive option, especially for scenarios demanding faster response times and cost-efficiency. This detailed GLM-4.7 (Reasoning) vs GLM-4.7-Flash (Non-reasoning) comparison will break down every critical metric to help you make the best decision.

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Model Snapshot

Key decision metrics at a glance.

GLM-4.7 (Reasoning)

Other

Reasoning: 10
Coding: 4
Multimodal: 4
Long Context: 5
Blended Price / 1M tokens: $0.001
P95 Latency: 1000ms
Tokens per second: 116.946tokens/sec

GLM-4.7-Flash (Non-reasoning)

Other

Reasoning: 6
Coding: 1
Multimodal: 2
Long Context: 3
Blended Price / 1M tokens: $0.000
P95 Latency: 1000ms
Tokens per second: 108.952tokens/sec

Overall Capabilities

The capability radar provides a holistic view of the GLM-4.7 (Reasoning) vs GLM-4.7-Flash (Non-reasoning) matchup. This chart illustrates each model's strengths and weaknesses at a glance, forming a cornerstone of our GLM-4.7 (Reasoning) vs GLM-4.7-Flash (Non-reasoning) analysis.

This radar chart visually maps the core capabilities (reasoning, coding, math proxy, multimodal, long context) of `GLM-4.7 (Reasoning)` vs `GLM-4.7-Flash (Non-reasoning)`.

Benchmark Breakdown

For a granular look, this chart directly compares scores across standardized benchmarks. In the critical MMLU Pro test, a key part of the GLM-4.7 (Reasoning) vs GLM-4.7-Flash (Non-reasoning) debate, GLM-4.7 (Reasoning) scores 100 against GLM-4.7-Flash (Non-reasoning)'s 60. This data-driven approach is essential for any serious GLM-4.7 (Reasoning) vs GLM-4.7-Flash (Non-reasoning) comparison.

This grouped bar chart provides a side-by-side comparison for each benchmark metric.

Speed & Latency

Speed is a crucial factor in the GLM-4.7 (Reasoning) vs GLM-4.7-Flash (Non-reasoning) decision for interactive applications. The metrics below highlight the trade-offs you should weigh before shipping to production.

Time to First Token

GLM-4.7 (Reasoning)300ms

GLM-4.7-Flash (Non-reasoning)300ms

Tokens per Second

GLM-4.7 (Reasoning)116.946

GLM-4.7-Flash (Non-reasoning)108.952

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The Economics of GLM-4.7 (Reasoning) vs GLM-4.7-Flash (Non-reasoning)

Power is only one part of the equation. This GLM-4.7 (Reasoning) vs GLM-4.7-Flash (Non-reasoning) pricing analysis gives you a true sense of value.

Pricing Breakdown

Compare input and output pricing at a glance.

Real-World Cost Scenario

To process 1M input tokens and generate 250k output tokens, GLM-4.7 (Reasoning) would cost $0.001, whereas GLM-4.7-Flash (Non-reasoning) would cost $0.000. This practical calculation is vital for any developer considering the GLM-4.7 (Reasoning) vs GLM-4.7-Flash (Non-reasoning) choice.

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Which Model Wins the GLM-4.7 (Reasoning) vs GLM-4.7-Flash (Non-reasoning) Battle for You?

Choose GLM-4.7 (Reasoning) if...

Your top priority is raw performance and capability.

You are working in a technical or scientific field requiring the highest accuracy.

Cost is a secondary concern to power in your GLM-4.7 (Reasoning) vs GLM-4.7-Flash (Non-reasoning) decision.

Choose GLM-4.7-Flash (Non-reasoning) if...

You need a highly responsive model for user-facing applications.

Your budget is a primary consideration in the GLM-4.7 (Reasoning) vs GLM-4.7-Flash (Non-reasoning) choice.

You are developing at scale where operational costs are critical.

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Your Questions about the GLM-4.7 (Reasoning) vs GLM-4.7-Flash (Non-reasoning) Comparison

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Data source: https://artificialanalysis.ai/