| Signal | GPT-5 | Delta | Llama 3.2 11B Vision Instruct |
|---|---|---|---|
Capabilities | 83 | +33 | |
Benchmarks | 88 | +88 | |
Pricing | 90 | -10 | |
Context window size | 89 | +8 | |
Recency | 83 | +58 | |
Output Capacity | 85 | +15 | |
| Overall Result | 5 wins | of 6 | 1 wins |
Score History
87.8
current score
GPT-5
right now
40
current score
OpenAI
Meta
Llama 3.2 11B Vision Instruct saves you $588.25/month
That's $7059.00/year compared to GPT-5 at your current usage level of 100K calls/month.
| Metric | GPT-5 | Llama 3.2 11B Vision Instruct | Winner |
|---|---|---|---|
| Overall Score | 88 | 40 | GPT-5 |
| Rank | #16 | #304 | GPT-5 |
| Quality Rank | #16 | #304 | GPT-5 |
| Adoption Rank | #16 | #304 | GPT-5 |
| Parameters | -- | 11B | -- |
| Context Window | 400K | 131K | GPT-5 |
| Pricing | $1.25/$10.00/M | $0.24/$0.24/M | -- |
| Signal Scores | |||
| Capabilities | 83 | 50 | GPT-5 |
| Benchmarks | 88 | -- | GPT-5 |
| Pricing | 90 | 100 | Llama 3.2 11B Vision Instruct |
| Context window size | 89 | 81 | GPT-5 |
| Recency | 83 | 25 | GPT-5 |
| Output Capacity | 85 | 70 | GPT-5 |
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 88/100 (rank #16), placing it in the top 95% of all 290 models tracked.
Scores 40/100 (rank #304), placing it in the top -4% of all 290 models tracked.
GPT-5 has a 48-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 96% better value per quality point. At 1M tokens/day, you'd spend $7.35/month with Llama 3.2 11B Vision Instruct vs $168.75/month with GPT-5 - a $161.40 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 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 ($0.24/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (88/100) 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 clearly outperforms Llama 3.2 11B Vision Instruct with a significant 47.8-point lead. For most general use cases, GPT-5 is the stronger choice. However, Llama 3.2 11B Vision Instruct may still excel in niche scenarios.
Best for Quality
GPT-5
Marginally better benchmark scores; both are excellent
Best for Cost
Llama 3.2 11B Vision Instruct
96% lower pricing; better value at scale
Best for Reliability
GPT-5
Higher uptime and faster response speeds
Best for Prototyping
GPT-5
Stronger community support and better developer experience
Best for Production
GPT-5
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-5 | Llama 3.2 11B Vision Instruct |
|---|---|---|
| Vision (Image Input) | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
OpenAI
Meta
Llama 3.2 11B Vision Instruct saves you $13.52/month
That's 95% cheaper than GPT-5 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 | Llama 3.2 11B Vision Instruct |
|---|---|---|
| Context Window | 400K | 131K |
| Max Output Tokens | 128,000 | 16,384 |
| Open Source | No | Yes |
| Created | Aug 7, 2025 | Sep 25, 2024 |