| Signal | GPT-5.2 Pro | Delta | Llama 3.2 11B Vision Instruct |
|---|---|---|---|
Capabilities | 100 | +50 | |
Pricing | 100 | +100 | |
Context window size | 89 | +8 | |
Recency | 100 | +65 | |
Output Capacity | 85 | +15 | |
| Overall Result | 5 wins | of 5 | 0 wins |
30
days ranked higher
0
days
0
days ranked higher
OpenAI
Meta
Llama 3.2 11B Vision Instruct saves you $10492.65/month
That's $125911.80/year compared to GPT-5.2 Pro at your current usage level of 100K calls/month.
| Metric | GPT-5.2 Pro | Llama 3.2 11B Vision Instruct | Winner |
|---|---|---|---|
| Overall Score | 96 | 56 | GPT-5.2 Pro |
| Rank | #10 | #226 | GPT-5.2 Pro |
| Quality Rank | #10 | #226 | GPT-5.2 Pro |
| Adoption Rank | #10 | #226 | GPT-5.2 Pro |
| Parameters | -- | 11B | -- |
| Context Window | 400K | 131K | GPT-5.2 Pro |
| Pricing | $21.00/$168.00/M | $0.05/$0.05/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 50 | GPT-5.2 Pro |
| Pricing | 100 | 0 | GPT-5.2 Pro |
| Context window size | 89 | 81 | GPT-5.2 Pro |
| Recency | 100 | 35 | GPT-5.2 Pro |
| Output Capacity | 85 | 70 | GPT-5.2 Pro |
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 96/100 (rank #10), placing it in the top 97% of all 290 models tracked.
Scores 56/100 (rank #226), placing it in the top 22% of all 290 models tracked.
GPT-5.2 Pro has a 39-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Llama 3.2 11B Vision Instruct offers 100% better value per quality point. At 1M tokens/day, you'd spend $1.47/month with Llama 3.2 11B Vision Instruct vs $2835.00/month with GPT-5.2 Pro — a $2833.53 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 3.2 11B Vision Instruct also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (400K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.05/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (96/100) 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
GPT-5.2 Pro clearly outperforms Llama 3.2 11B Vision Instruct with a significant 39.2-point lead. For most general use cases, GPT-5.2 Pro is the stronger choice. However, Llama 3.2 11B Vision Instruct may still excel in niche scenarios.
Best for Quality
GPT-5.2 Pro
Marginally better benchmark scores; both are excellent
Best for Cost
Llama 3.2 11B Vision Instruct
100% lower pricing; better value at scale
Best for Reliability
GPT-5.2 Pro
Higher uptime and faster response speeds
Best for Prototyping
GPT-5.2 Pro
Stronger community support and better developer experience
Best for Production
GPT-5.2 Pro
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-5.2 Pro | Llama 3.2 11B Vision Instruct |
|---|---|---|
| Vision (Image Input) | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Searchdiffers | ||
| Image Output |
OpenAI
Meta
Llama 3.2 11B Vision Instruct saves you $239.25/month
That's 100% cheaper than GPT-5.2 Pro 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-5.2 Pro | Llama 3.2 11B Vision Instruct |
|---|---|---|
| Context Window | 400K | 131K |
| Max Output Tokens | 128,000 | 16,384 |
| Open Source | No | Yes |
| Created | Dec 10, 2025 | Sep 25, 2024 |
GPT-5.2 Pro scores 96/100 (rank #10) compared to Llama 3.2 11B Vision Instruct's 56/100 (rank #226), giving it a 39-point advantage. GPT-5.2 Pro is the stronger overall choice, though Llama 3.2 11B Vision Instruct may excel in specific areas like cost efficiency.
GPT-5.2 Pro is ranked #10 and Llama 3.2 11B Vision Instruct is ranked #226 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 3.2 11B Vision Instruct is cheaper at $0.05/M output tokens vs GPT-5.2 Pro's $168.00/M output tokens — 3428.6x more expensive. Input token pricing: GPT-5.2 Pro at $21.00/M vs Llama 3.2 11B Vision Instruct at $0.05/M.
GPT-5.2 Pro has a larger context window of 400,000 tokens compared to Llama 3.2 11B Vision Instruct's 131,072 tokens. A larger context window means the model can process longer documents and conversations.