Falcon 400B vs Jurassic 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
Compare Different Models
Detailed Comparison
| Feature | Falcon 400B | Jurassic 4 | Winner |
|---|---|---|---|
| Provider | Technology Innovation Institute | AI21 Labs | — |
| Context Window | 128k | 256k | — |
|
MMLU Score
General knowledge & reasoning | 90% | 87.5% | Falcon 400B |
|
Coding Score
Code generation & debugging | 89.5% | 86% | Falcon 400B |
|
Reasoning Score
Logic & problem-solving | 89.7% | 87% | Falcon 400B |
| Release Date | 2026 | 2026 | — |
| Vision Support | ✓ Yes | ✓ Yes | — |
| Function Calling | ✓ Yes | ✓ Yes | — |
Performance Comparison
MMLU (General Knowledge)
Difference: 2.5%Coding Performance
Difference: 3.5%Reasoning & Logic
Difference: 2.7%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
Both models show comparable coding performance, with less than 5 points separating them on benchmark tests. Enterprise teams requiring maximum accuracy should invest in Falcon 400B for demanding workloads and complex tasks.
Our Recommendation
Choose Falcon 400B for applications where response quality directly impacts business outcomes, or evaluate both models based on your specific use case requirements.
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
Jurassic 4 Excels At:
- Enterprise content generation
- Document understanding
- Chat assistants
- Developer APIs
- RAG workflows
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
Jurassic 4
Strengths
- • High-quality text generation
- • Support for larger context sizes
- • API-first enterprise tooling
- • Multimodal capabilities
Considerations
- • Closed-source
- • Benchmark transparency varies
- • Smaller ecosystem than hyperscalers
- • Premium pricing
Frequently Asked Questions
Which is better: Falcon 400B or Jurassic 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 Jurassic 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 3.5 percentage points ahead of Jurassic 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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