Falcon 400B vs LLaMA 4

Comprehensive side-by-side comparison of pricing, performance benchmarks, and capabilities

At a Glance

Best Overall Performance

Falcon 400B

Higher overall benchmarks

Best for Coding

Falcon 400B

89.5% coding score

Best for Reasoning

Falcon 400B

89.7% reasoning score

Best MMLU Score

Falcon 400B

90% general knowledge

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Detailed Comparison

Feature Falcon 400B LLaMA 4 Winner
Provider Technology Innovation Institute Meta
Context Window 128k 128k
MMLU Score

General knowledge & reasoning

90% 85% Falcon 400B
Coding Score

Code generation & debugging

89.5% 84% Falcon 400B
Reasoning Score

Logic & problem-solving

89.7% 85.5% Falcon 400B
Release Date 2026 2025
Vision Support ✓ Yes ✓ Yes
Function Calling ✓ Yes ✓ Yes

Performance Comparison

MMLU (General Knowledge)

Difference: 5.0%
Falcon 400B 90%
LLaMA 4 85%

Coding Performance

Difference: 5.5%
Falcon 400B 89.5%
LLaMA 4 84%

Reasoning & Logic

Difference: 4.2%
Falcon 400B 89.7%
LLaMA 4 85.5%

Expert Analysis

Performance Analysis

Falcon 400B achieves superior scores across 3 of 3 key benchmarks, including coding (89.5%), demonstrating stronger general capabilities.

Final Verdict

Our comprehensive recommendation based on all factors

Falcon 400B demonstrates superior coding capabilities with a 5.5-point advantage, making it the stronger choice for software development tasks. Enterprise teams requiring maximum accuracy should invest in Falcon 400B for demanding workloads and complex tasks.

Our Recommendation

Enterprise teams and applications requiring maximum accuracy should choose Falcon 400B for mission-critical deployments where performance is paramount.

Best For These Use Cases

Falcon 400B Excels At:

  • Large research assistants
  • Foundation for custom AI stacks
  • Instruction-tuned agents
  • Benchmark research
  • High-capacity RAG

LLaMA 4 Excels At:

  • Self-hosted agents
  • Research experiments
  • Custom AI assistants
  • Offline inference
  • Fine-tuning for niche tasks

Strengths & Weaknesses

Falcon 400B

Strengths

  • Huge model capacity
  • Strong open research benchmarks
  • Support for instruction variants
  • Large-scale agent foundation

Considerations

  • Extremely high infra costs
  • Complex self-hosting
  • Safety tools community-managed
  • Deployment custom tooling needed
Full Falcon 400B Review →

LLaMA 4

Strengths

  • Open weights
  • High reasoning for size
  • Multimodal support
  • Community-driven

Considerations

  • Shorter context vs GPT-5
  • Resource-intensive
  • Moderate hallucination rate
  • Limited enterprise support
Full LLaMA 4 Review →

Frequently Asked Questions

Which is better: Falcon 400B or LLaMA 4?

Falcon 400B offers superior overall performance with higher benchmark scores across MMLU, coding, and reasoning tests. The best choice depends on your specific use case requirements and performance priorities.

What are the key differences?

Falcon 400B leads in overall performance with higher benchmark scores, while LLaMA 4 may offer advantages in specific areas like context window size or specialized capabilities. Both models have their strengths depending on your particular needs.

Which is better for coding?

Falcon 400B leads in coding performance with a score of 89.5%, making it 5.5 percentage points ahead of LLaMA 4. This makes Falcon 400B the superior choice for software development, code generation, and debugging tasks.

Can I use both models together?

Yes! Many organizations use multiple models strategically: one model for routine tasks where efficiency matters, and another for complex, mission-critical applications requiring maximum accuracy. This hybrid approach optimizes both performance and resource utilization across different use cases.

How often are these benchmarks updated?

We update all benchmark scores and pricing data daily to reflect the latest model versions and API pricing changes. Benchmark scores are sourced from official documentation, independent testing platforms like Artificial Analysis, and peer-reviewed academic evaluations. Last updated: 2/2/2026.

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