| Signal | Llama Guard 4 12B | Delta | Qwen3 14B |
|---|---|---|---|
Capabilities | 50 | -17 | |
Pricing | 0 | -- | |
Context window size | 83 | +10 | |
Recency | 71 | +0 | |
Output Capacity | 20 | -57 | |
| Overall Result | 2 wins | of 5 | 2 wins |
9
days higher
3
days
18
days higher
Meta
Alibaba
Qwen3 14B saves you $9.00/month
That's $108.00/year compared to Llama Guard 4 12B at your current usage level of 100K calls/month.
| Metric | Llama Guard 4 12B | Qwen3 14B | Winner |
|---|---|---|---|
| Overall Score | 40 | 40 | -- |
| Rank | #240 | #242 | Llama Guard 4 12B |
| Quality Rank | #240 | #242 | Llama Guard 4 12B |
| Adoption Rank | #240 | #242 | Llama Guard 4 12B |
| Parameters | 12B | 14B | -- |
| Context Window | 164K | 41K | Llama Guard 4 12B |
| Pricing | $0.18/$0.18/M | $0.06/$0.24/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 67 | Qwen3 14B |
| Pricing | 0 | 0 | Llama Guard 4 12B |
| Context window size | 83 | 73 | Llama Guard 4 12B |
| Recency | 71 | 71 | Llama Guard 4 12B |
| Output Capacity | 20 | 77 | Qwen3 14B |
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 #240), placing it in the top 18% of all 290 models tracked.
Scores 40/100 (rank #242), placing it in the top 17% 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.
Qwen3 14B offers 17% better value per quality point. At 1M tokens/day, you'd spend $4.50/month with Qwen3 14B vs $5.40/month with Llama Guard 4 12B - a $0.90 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
Llama Guard 4 12B and Qwen3 14B 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
Llama Guard 4 12B
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen3 14B
17% 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 | Qwen3 14B |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
Meta
Alibaba
Qwen3 14B saves you $0.1440/month
That's 27% cheaper than Llama Guard 4 12B 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 | Qwen3 14B |
|---|---|---|
| Context Window | 164K | 41K |
| Max Output Tokens | -- | 40,960 |
| Open Source | Yes | Yes |
| Created | Apr 30, 2025 | Apr 28, 2025 |
Both Llama Guard 4 12B and Qwen3 14B score 40/100, making them extremely close competitors. Choose based on pricing, provider ecosystem, or specific capability requirements.
Llama Guard 4 12B is ranked #240 and Qwen3 14B is ranked #242 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 Qwen3 14B's $0.24/M output tokens - 1.3x more expensive. Input token pricing: Llama Guard 4 12B at $0.18/M vs Qwen3 14B at $0.06/M.
Llama Guard 4 12B has a larger context window of 163,840 tokens compared to Qwen3 14B's 40,960 tokens. A larger context window means the model can process longer documents and conversations.