| Signal | Coder Large | Delta | Llama Guard 4 12B |
|---|---|---|---|
Capabilities | 17 | -33 | |
Pricing | 1 | +1 | |
Context window size | 72 | -11 | |
Recency | 72 | +1 | |
Output Capacity | 20 | -- | |
| Overall Result | 2 wins | of 5 | 2 wins |
7
days higher
6
days
17
days higher
arcee-ai
Meta
Llama Guard 4 12B saves you $63.00/month
That's $756.00/year compared to Coder Large at your current usage level of 100K calls/month.
| Metric | Coder Large | Llama Guard 4 12B | Winner |
|---|---|---|---|
| Overall Score | 40 | 40 | -- |
| Rank | #238 | #240 | Coder Large |
| Quality Rank | #238 | #240 | Coder Large |
| Adoption Rank | #238 | #240 | Coder Large |
| Parameters | -- | 12B | -- |
| Context Window | 33K | 164K | Llama Guard 4 12B |
| Pricing | $0.50/$0.80/M | $0.18/$0.18/M | -- |
| Signal Scores | |||
| Capabilities | 17 | 50 | Llama Guard 4 12B |
| Pricing | 1 | 0 | Coder Large |
| Context window size | 72 | 83 | Llama Guard 4 12B |
| Recency | 72 | 71 | Coder Large |
| Output Capacity | 20 | 20 | Coder Large |
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%). Here's what the scores mean for these two models:
Scores 40/100 (rank #238), placing it in the top 18% of all 290 models tracked.
Scores 40/100 (rank #240), placing it in the top 18% of all 290 models tracked.
With only a 0-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 72% better value per quality point. At 1M tokens/day, you'd spend $5.40/month with Llama Guard 4 12B vs $19.50/month with Coder Large - a $14.10 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 (40/100) 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
Coder Large and Llama Guard 4 12B are extremely close in overall performance (only 0 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Coder Large
Marginally better benchmark scores; both are excellent
Best for Cost
Llama Guard 4 12B
72% lower pricing; better value at scale
Best for Reliability
Coder Large
Higher uptime and faster response speeds
Best for Prototyping
Coder Large
Stronger community support and better developer experience
Best for Production
Coder Large
Wider enterprise adoption and proven at scale
by arcee-ai
| Capability | Coder Large | Llama Guard 4 12B |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
arcee-ai
Meta
Llama Guard 4 12B saves you $1.32/month
That's 71% cheaper than Coder Large 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 | Coder Large | Llama Guard 4 12B |
|---|---|---|
| Context Window | 33K | 164K |
| Max Output Tokens | -- | -- |
| Open Source | No | Yes |
| Created | May 5, 2025 | Apr 30, 2025 |
Both Coder Large and Llama Guard 4 12B score 40/100, making them extremely close competitors. Choose based on pricing, provider ecosystem, or specific capability requirements.
Coder Large is ranked #238 and Llama Guard 4 12B is ranked #240 out of 290+ AI models. Rankings use a composite score combining benchmark performance (90%) from MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations, with capabilities and context window as tiebreakers (10%). Scores update hourly.
Llama Guard 4 12B is cheaper at $0.18/M output tokens vs Coder Large's $0.80/M output tokens - 4.4x more expensive. Input token pricing: Coder Large at $0.50/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 Coder Large's 32,768 tokens. A larger context window means the model can process longer documents and conversations.