| Signal | GPT-4o (2024-08-06) | Delta | Llama Guard 4 12B |
|---|---|---|---|
Capabilities | 67 | +17 | |
Benchmarks | 58 | +58 | |
Pricing | 10 | +10 | |
Context window size | 81 | -2 | |
Recency | 25 | -48 | |
Output Capacity | 70 | +50 | |
| Overall Result | 4 wins | of 6 | 2 wins |
3
days ranked higher
2
days
25
days ranked higher
OpenAI
Meta
Llama Guard 4 12B saves you $723.00/month
That's $8676.00/year compared to GPT-4o (2024-08-06) at your current usage level of 100K calls/month.
| Metric | GPT-4o (2024-08-06) | Llama Guard 4 12B | Winner |
|---|---|---|---|
| Overall Score | 56 | 59 | Llama Guard 4 12B |
| Rank | #242 | #228 | Llama Guard 4 12B |
| Quality Rank | #242 | #228 | Llama Guard 4 12B |
| Adoption Rank | #242 | #228 | Llama Guard 4 12B |
| Parameters | -- | 12B | -- |
| Context Window | 128K | 164K | Llama Guard 4 12B |
| Pricing | $2.50/$10.00/M | $0.18/$0.18/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 50 | GPT-4o (2024-08-06) |
| Benchmarks | 58 | -- | GPT-4o (2024-08-06) |
| Pricing | 10 | 0 | GPT-4o (2024-08-06) |
| Context window size | 81 | 83 | Llama Guard 4 12B |
| Recency | 25 | 73 | Llama Guard 4 12B |
| Output Capacity | 70 | 20 | GPT-4o (2024-08-06) |
Our composite score (0–100) combines six weighted signals: benchmark performance (25%), pricing efficiency (25%), context window size (15%), model recency (15%), output capacity (10%), and capability versatility (10%). Here's what the scores mean for these two models:
Scores 56/100 (rank #242), placing it in the top 17% of all 290 models tracked.
Scores 59/100 (rank #228), placing it in the top 22% of all 290 models tracked.
With only a 3-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.
Llama Guard 4 12B offers 97% better value per quality point. At 1M tokens/day, you'd spend $5.40/month with Llama Guard 4 12B vs $187.50/month with GPT-4o (2024-08-06) - a $182.10 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
Higher benchmark score (0/100) indicates stronger performance on coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Faster response time (speed score 0/100) is critical for user-facing chat. 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 (59/100) 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
Llama Guard 4 12B has a moderate advantage with a 3.3999999999999986-point lead in composite score. It wins on more signal dimensions, but GPT-4o (2024-08-06) has specific strengths that could make it the better choice for certain workflows.
Best for Quality
GPT-4o (2024-08-06)
Marginally better benchmark scores; both are excellent
Best for Cost
Llama Guard 4 12B
97% lower pricing; better value at scale
Best for Reliability
GPT-4o (2024-08-06)
Higher uptime and faster response speeds
Best for Prototyping
GPT-4o (2024-08-06)
Stronger community support and better developer experience
Best for Production
GPT-4o (2024-08-06)
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-4o (2024-08-06) | Llama Guard 4 12B |
|---|---|---|
| Vision (Image Input) | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
OpenAI
Meta
Llama Guard 4 12B saves you $15.96/month
That's 97% cheaper than GPT-4o (2024-08-06) 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 | GPT-4o (2024-08-06) | Llama Guard 4 12B |
|---|---|---|
| Context Window | 128K | 164K |
| Max Output Tokens | 16,384 | -- |
| Open Source | No | Yes |
| Created | Aug 6, 2024 | Apr 30, 2025 |
Llama Guard 4 12B scores 59/100 (rank #228) compared to GPT-4o (2024-08-06)'s 56/100 (rank #242), giving it a 3-point advantage. Llama Guard 4 12B is the stronger overall choice, though GPT-4o (2024-08-06) may excel in specific areas like certain benchmarks.
GPT-4o (2024-08-06) is ranked #242 and Llama Guard 4 12B is ranked #228 out of 290+ AI models. Rankings use a composite score combining benchmark performance (25%), pricing (25%), context window (15%), recency (15%), output capacity (10%), and versatility (10%). Scores update hourly.
Llama Guard 4 12B is cheaper at $0.18/M output tokens vs GPT-4o (2024-08-06)'s $10.00/M output tokens - 55.6x more expensive. Input token pricing: GPT-4o (2024-08-06) at $2.50/M vs Llama Guard 4 12B at $0.18/M.
Llama Guard 4 12B has a larger context window of 163,840 tokens compared to GPT-4o (2024-08-06)'s 128,000 tokens. A larger context window means the model can process longer documents and conversations.