Llama Nemotron Super 49B v1.5 (Reasoning) vs GLM-4.5-Air: The Ultimate Performance & Pricing Comparison

Deep dive into reasoning, benchmarks, and latency insights.

The Final Verdict in the Llama Nemotron Super 49B v1.5 (Reasoning) vs GLM-4.5-Air Showdown

After a comprehensive analysis, GLM-4.5-Air emerges as the superior choice for users prioritizing raw intelligence and reasoning. However, Llama Nemotron Super 49B v1.5 (Reasoning) remains a highly competitive option, especially for scenarios demanding faster response times and cost-efficiency. This detailed Llama Nemotron Super 49B v1.5 (Reasoning) vs GLM-4.5-Air comparison will break down every critical metric to help you make the best decision.

Explore best-for scenarios•Let the AI Selector recommend next steps

Model Snapshot

Key decision metrics at a glance.

Llama Nemotron Super 49B v1.5 (Reasoning)

Other

Reasoning: 8
Coding: 2
Multimodal: 2
Long Context: 2
Blended Price / 1M tokens: $0.000
P95 Latency: 1000ms
Tokens per second: 75.33tokens/sec

GLM-4.5-Air

Other

Reasoning: 8
Coding: 2
Multimodal: 2
Long Context: 3
Blended Price / 1M tokens: $0.000
P95 Latency: 1000ms
Tokens per second: 97.831tokens/sec

Overall Capabilities

The capability radar provides a holistic view of the Llama Nemotron Super 49B v1.5 (Reasoning) vs GLM-4.5-Air matchup. This chart illustrates each model's strengths and weaknesses at a glance, forming a cornerstone of our Llama Nemotron Super 49B v1.5 (Reasoning) vs GLM-4.5-Air analysis.

This radar chart visually maps the core capabilities (reasoning, coding, math proxy, multimodal, long context) of `Llama Nemotron Super 49B v1.5 (Reasoning)` vs `GLM-4.5-Air`.

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 Llama Nemotron Super 49B v1.5 (Reasoning) vs GLM-4.5-Air debate, Llama Nemotron Super 49B v1.5 (Reasoning) scores 80 against GLM-4.5-Air's 80. This data-driven approach is essential for any serious Llama Nemotron Super 49B v1.5 (Reasoning) vs GLM-4.5-Air comparison.

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

Speed & Latency

Speed is a crucial factor in the Llama Nemotron Super 49B v1.5 (Reasoning) vs GLM-4.5-Air decision for interactive applications. The metrics below highlight the trade-offs you should weigh before shipping to production.

Time to First Token

Llama Nemotron Super 49B v1.5 (Reasoning)300ms

GLM-4.5-Air300ms

Tokens per Second

Llama Nemotron Super 49B v1.5 (Reasoning)75.33

GLM-4.5-Air97.831

Head to the playground to validate these results yourself

The Economics of Llama Nemotron Super 49B v1.5 (Reasoning) vs GLM-4.5-Air

Power is only one part of the equation. This Llama Nemotron Super 49B v1.5 (Reasoning) vs GLM-4.5-Air 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, Llama Nemotron Super 49B v1.5 (Reasoning) would cost $0.000, whereas GLM-4.5-Air would cost $0.000. This practical calculation is vital for any developer considering the Llama Nemotron Super 49B v1.5 (Reasoning) vs GLM-4.5-Air choice.

Review the complete pricing and packaging strategy

Which Model Wins the Llama Nemotron Super 49B v1.5 (Reasoning) vs GLM-4.5-Air Battle for You?

Choose Llama Nemotron Super 49B v1.5 (Reasoning) if...

Your top priority is raw performance and capability.

You need the most advanced reasoning capabilities available.

Your use case demands cutting-edge AI performance.

Choose GLM-4.5-Air if...

You are developing at scale where operational costs are critical.

You prioritize cost-effectiveness over maximum performance.

Your workload requires consistent, reliable performance.

Explore all Best picks Use the AI Selector for a tailored recommendation

Your Questions about the Llama Nemotron Super 49B v1.5 (Reasoning) vs GLM-4.5-Air Comparison

Review the full evaluation methodology · Read the latest analysis posts

Data source: https://artificialanalysis.ai/