GLM-4.7 (Reasoning) vs Pixtral Large: The Ultimate Performance & Pricing Comparison

Deep dive into reasoning, benchmarks, and latency insights.

The Final Verdict in the GLM-4.7 (Reasoning) vs Pixtral Large Showdown

After a comprehensive analysis, GLM-4.7 (Reasoning) emerges as the superior choice for users prioritizing raw intelligence and reasoning. However, Pixtral Large remains a highly competitive option, especially for scenarios demanding faster response times and cost-efficiency. This detailed GLM-4.7 (Reasoning) vs Pixtral Large 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: 147.905tokens/sec

Pixtral Large

Mistral

Reasoning: 1
Coding: 6
Multimodal: 1
Long Context: 2
Blended Price / 1M tokens: $0.003
P95 Latency: 1000ms
Tokens per second: 50.892tokens/sec

Overall Capabilities

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

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

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 Pixtral Large debate, GLM-4.7 (Reasoning) scores 100 against Pixtral Large's 10. This data-driven approach is essential for any serious GLM-4.7 (Reasoning) vs Pixtral Large 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 Pixtral Large 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

Pixtral Large300ms

Tokens per Second

GLM-4.7 (Reasoning)147.905

Pixtral Large50.892

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The Economics of GLM-4.7 (Reasoning) vs Pixtral Large

Power is only one part of the equation. This GLM-4.7 (Reasoning) vs Pixtral Large 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 Pixtral Large would cost $0.004. This practical calculation is vital for any developer considering the GLM-4.7 (Reasoning) vs Pixtral Large choice.

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Which Model Wins the GLM-4.7 (Reasoning) vs Pixtral Large 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.

You need the most advanced reasoning capabilities available.

Choose Pixtral Large if...

You are developing at scale where operational costs are critical.

You prioritize cost-effectiveness over maximum performance.

Your workload requires consistent, reliable performance.

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Your Questions about the GLM-4.7 (Reasoning) vs Pixtral Large Comparison

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Data source: https://artificialanalysis.ai/