Mistral Medium 3.1 vs Llama Nemotron Super 49B v1.5 (Reasoning): The Ultimate Performance & Pricing Comparison

Deep dive into reasoning, benchmarks, and latency insights.

The Final Verdict in the Mistral Medium 3.1 vs Llama Nemotron Super 49B v1.5 (Reasoning) Showdown

After a comprehensive analysis, Llama Nemotron Super 49B v1.5 (Reasoning) emerges as the superior choice for users prioritizing raw intelligence and reasoning. However, Mistral Medium 3.1 remains a highly competitive option, especially for scenarios demanding faster response times and cost-efficiency. This detailed Mistral Medium 3.1 vs Llama Nemotron Super 49B v1.5 (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.

Mistral Medium 3.1

Mistral

Reasoning: 4
Coding: 2
Multimodal: 2
Long Context: 3
Blended Price / 1M tokens: $0.001
P95 Latency: 1000ms
Tokens per second: 92.492tokens/sec

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

Overall Capabilities

The capability radar provides a holistic view of the Mistral Medium 3.1 vs Llama Nemotron Super 49B v1.5 (Reasoning) matchup. This chart illustrates each model's strengths and weaknesses at a glance, forming a cornerstone of our Mistral Medium 3.1 vs Llama Nemotron Super 49B v1.5 (Reasoning) analysis.

This radar chart visually maps the core capabilities (reasoning, coding, math proxy, multimodal, long context) of `Mistral Medium 3.1` vs `Llama Nemotron Super 49B v1.5 (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 Mistral Medium 3.1 vs Llama Nemotron Super 49B v1.5 (Reasoning) debate, Mistral Medium 3.1 scores 40 against Llama Nemotron Super 49B v1.5 (Reasoning)'s 80. This data-driven approach is essential for any serious Mistral Medium 3.1 vs Llama Nemotron Super 49B v1.5 (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 Mistral Medium 3.1 vs Llama Nemotron Super 49B v1.5 (Reasoning) decision for interactive applications. The metrics below highlight the trade-offs you should weigh before shipping to production.

Time to First Token

Mistral Medium 3.1300ms

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

Tokens per Second

Mistral Medium 3.192.492

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

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The Economics of Mistral Medium 3.1 vs Llama Nemotron Super 49B v1.5 (Reasoning)

Power is only one part of the equation. This Mistral Medium 3.1 vs Llama Nemotron Super 49B v1.5 (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, Mistral Medium 3.1 would cost $0.001, whereas Llama Nemotron Super 49B v1.5 (Reasoning) would cost $0.000. This practical calculation is vital for any developer considering the Mistral Medium 3.1 vs Llama Nemotron Super 49B v1.5 (Reasoning) choice.

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Which Model Wins the Mistral Medium 3.1 vs Llama Nemotron Super 49B v1.5 (Reasoning) Battle for You?

Choose Mistral Medium 3.1 if...

Cost is a secondary concern to power in your Mistral Medium 3.1 vs Llama Nemotron Super 49B v1.5 (Reasoning) decision.

You need the most advanced reasoning capabilities available.

Your use case demands cutting-edge AI performance.

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

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

Your budget is a primary consideration in the Mistral Medium 3.1 vs Llama Nemotron Super 49B v1.5 (Reasoning) choice.

You are developing at scale where operational costs are critical.

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Your Questions about the Mistral Medium 3.1 vs Llama Nemotron Super 49B v1.5 (Reasoning) Comparison

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Data source: https://artificialanalysis.ai/