LLaMA 4 vs BLOOMZ 7B
Comprehensive side-by-side comparison of pricing, performance benchmarks, and capabilities
At a Glance
Best Overall Performance
LLaMA 4
Higher overall benchmarks
Best for Coding
LLaMA 4
84% coding score
Best for Reasoning
LLaMA 4
85.5% reasoning score
Best MMLU Score
LLaMA 4
85% general knowledge
Compare Different Models
Detailed Comparison
| Feature | LLaMA 4 | BLOOMZ 7B | Winner |
|---|---|---|---|
| Provider | Meta | Hugging Face | — |
| Context Window | 128k | 32k | — |
|
MMLU Score
General knowledge & reasoning | 85% | 78% | LLaMA 4 |
|
Coding Score
Code generation & debugging | 84% | 75% | LLaMA 4 |
|
Reasoning Score
Logic & problem-solving | 85.5% | 77% | LLaMA 4 |
| Release Date | 2025 | 2025 | — |
| Vision Support | ✓ Yes | — | — |
| Function Calling | ✓ Yes | ✓ Yes | — |
Performance Comparison
MMLU (General Knowledge)
Difference: 7.0%Coding Performance
Difference: 9.0%Reasoning & Logic
Difference: 8.5%Expert Analysis
Performance Analysis
LLaMA 4 achieves superior scores across 3 of 3 key benchmarks, including coding (84%), demonstrating stronger general capabilities.
Final Verdict
Our comprehensive recommendation based on all factors
LLaMA 4 demonstrates superior coding capabilities with a 9.0-point advantage, making it the stronger choice for software development tasks. Enterprise teams requiring maximum accuracy should invest in LLaMA 4 for demanding workloads and complex tasks.
Our Recommendation
Enterprise teams and applications requiring maximum accuracy should choose LLaMA 4 for mission-critical deployments where performance is paramount.
Best For These Use Cases
LLaMA 4 Excels At:
- Self-hosted agents
- Research experiments
- Custom AI assistants
- Offline inference
- Fine-tuning for niche tasks
BLOOMZ 7B Excels At:
- Open research
- Multilingual chatbots
- Custom fine-tuning
- Educational AI
- Prototype AI assistants
Strengths & Weaknesses
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
BLOOMZ 7B
Strengths
- • Open weights
- • Good multilingual support
- • Community-friendly
- • Fine-tuning ready
Considerations
- • Smaller size
- • Moderate reasoning
- • Limited multimodal support
- • Shorter context
Frequently Asked Questions
Which is better: LLaMA 4 or BLOOMZ 7B?
LLaMA 4 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?
LLaMA 4 leads in overall performance with higher benchmark scores, while BLOOMZ 7B 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?
LLaMA 4 leads in coding performance with a score of 84%, making it 9.0 percentage points ahead of BLOOMZ 7B. This makes LLaMA 4 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.
Ready to Get Started?
Choose the AI model that best fits your needs and budget
Or compare other models to find your perfect match