| Signal | Llama Guard 4 12B | Delta | R1 |
|---|---|---|---|
Capabilities | 50 | -17 | |
Pricing | 100 | +2 | |
Context window size | 75 | -- | |
Recency | 56 | +18 | |
Output Capacity | 70 | +0 | |
Benchmarks | 0 | -73 | |
| Overall Result | 3 wins | of 6 | 2 wins |
Score History
40
current score
R1
right now
73.7
current score
Meta
DeepSeek
Llama Guard 4 12B saves you $168.00/month
That's $2016.00/year compared to R1 at your current usage level of 100K calls/month.
| Metric | Llama Guard 4 12B | R1 | Winner |
|---|---|---|---|
| Overall Score | 40 | 74 | R1 |
| Rank | #260 | #76 | R1 |
| Quality Rank | #260 | #76 | R1 |
| Adoption Rank | #260 | #76 | R1 |
| Parameters | 12B | -- | -- |
| Context Window | 164K | 164K | -- |
| Pricing | $0.18/$0.18/M | $0.70/$2.50/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 67 | R1 |
| Pricing | 100 | 98 | Llama Guard 4 12B |
| Context window size | 75 | 75 | Llama Guard 4 12B |
| Recency | 56 | 38 | Llama Guard 4 12B |
| Output Capacity | 70 | 70 | Llama Guard 4 12B |
| Benchmarks | -- | 73 | R1 |
Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.
Scores 40/100 (rank #260), placing it in the top 11% of all 290 models tracked.
Scores 74/100 (rank #76), placing it in the top 74% of all 290 models tracked.
R1 has a 34-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Llama Guard 4 12B offers 89% better value per quality point. At 1M tokens/day, you'd spend $5.40/month with Llama Guard 4 12B vs $48.00/month with R1 - a $42.60 monthly difference.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Suitable for user-facing chat with competitive response times. Llama Guard 4 12B also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (164K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.18/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (74/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
R1 clearly outperforms Llama Guard 4 12B with a significant 33.7-point lead. For most general use cases, R1 is the stronger choice. However, Llama Guard 4 12B may still excel in niche scenarios.
Best for Quality
Llama Guard 4 12B
Marginally better benchmark scores; both are excellent
Best for Cost
Llama Guard 4 12B
89% lower pricing; better value at scale
Best for Reliability
Llama Guard 4 12B
Higher uptime and faster response speeds
Best for Prototyping
Llama Guard 4 12B
Stronger community support and better developer experience
Best for Production
Llama Guard 4 12B
Wider enterprise adoption and proven at scale
by Meta
| Capability | Llama Guard 4 12B | R1 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
Meta
DeepSeek
Llama Guard 4 12B saves you $3.72/month
That's 87% cheaper than R1 at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | Llama Guard 4 12B | R1 |
|---|---|---|
| Context Window | 164K | 164K |
| Max Output Tokens | 16,384 | 16,000 |
| Open Source | Yes | Yes |
| Created | Apr 30, 2025 | Jan 20, 2025 |