| Signal | DeepSeek V3.1 | Delta | Llama 3.2 11B Vision Instruct |
|---|---|---|---|
Capabilities | 67 | +17 | |
Benchmarks | 69 | +69 | |
Pricing | 1 | +1 | |
Context window size | 72 | -9 | |
Recency | 93 | +60 | |
Output Capacity | 64 | -6 | |
| Overall Result | 4 wins | of 6 | 2 wins |
30
days ranked higher
0
days
0
days ranked higher
DeepSeek
Meta
Llama 3.2 11B Vision Instruct saves you $45.15/month
That's $541.80/year compared to DeepSeek V3.1 at your current usage level of 100K calls/month.
| Metric | DeepSeek V3.1 | Llama 3.2 11B Vision Instruct | Winner |
|---|---|---|---|
| Overall Score | 74 | 54 | DeepSeek V3.1 |
| Rank | #118 | #246 | DeepSeek V3.1 |
| Quality Rank | #118 | #246 | DeepSeek V3.1 |
| Adoption Rank | #118 | #246 | DeepSeek V3.1 |
| Parameters | -- | 11B | -- |
| Context Window | 33K | 131K | Llama 3.2 11B Vision Instruct |
| Pricing | $0.15/$0.75/M | $0.05/$0.05/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 50 | DeepSeek V3.1 |
| Benchmarks | 69 | -- | DeepSeek V3.1 |
| Pricing | 1 | 0 | DeepSeek V3.1 |
| Context window size | 72 | 81 | Llama 3.2 11B Vision Instruct |
| Recency | 93 | 33 | DeepSeek V3.1 |
| Output Capacity | 64 | 70 | Llama 3.2 11B Vision Instruct |
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 74/100 (rank #118), placing it in the top 60% of all 290 models tracked.
Scores 54/100 (rank #246), placing it in the top 16% of all 290 models tracked.
DeepSeek V3.1 has a 19-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 89% better value per quality point. At 1M tokens/day, you'd spend $1.47/month with Llama 3.2 11B Vision Instruct vs $13.50/month with DeepSeek V3.1 - a $12.03 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 (131K 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 (74/100) 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
DeepSeek V3.1 clearly outperforms Llama 3.2 11B Vision Instruct with a significant 19.39999999999999-point lead. For most general use cases, DeepSeek V3.1 is the stronger choice. However, Llama 3.2 11B Vision Instruct may still excel in niche scenarios.
Best for Quality
DeepSeek V3.1
Marginally better benchmark scores; both are excellent
Best for Cost
Llama 3.2 11B Vision Instruct
89% lower pricing; better value at scale
Best for Reliability
DeepSeek V3.1
Higher uptime and faster response speeds
Best for Prototyping
DeepSeek V3.1
Stronger community support and better developer experience
Best for Production
DeepSeek V3.1
Wider enterprise adoption and proven at scale
by DeepSeek
| Capability | DeepSeek V3.1 | Llama 3.2 11B Vision Instruct |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
DeepSeek
Meta
Llama 3.2 11B Vision Instruct saves you $1.02/month
That's 87% cheaper than DeepSeek V3.1 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 | DeepSeek V3.1 | Llama 3.2 11B Vision Instruct |
|---|---|---|
| Context Window | 33K | 131K |
| Max Output Tokens | 7,168 | 16,384 |
| Open Source | Yes | Yes |
| Created | Aug 21, 2025 | Sep 25, 2024 |
DeepSeek V3.1 scores 74/100 (rank #118) compared to Llama 3.2 11B Vision Instruct's 54/100 (rank #246), giving it a 19-point advantage. DeepSeek V3.1 is the stronger overall choice, though Llama 3.2 11B Vision Instruct may excel in specific areas like cost efficiency.
DeepSeek V3.1 is ranked #118 and Llama 3.2 11B Vision Instruct is ranked #246 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 DeepSeek V3.1's $0.75/M output tokens - 15.3x more expensive. Input token pricing: DeepSeek V3.1 at $0.15/M vs Llama 3.2 11B Vision Instruct at $0.05/M.
Llama 3.2 11B Vision Instruct has a larger context window of 131,072 tokens compared to DeepSeek V3.1's 32,768 tokens. A larger context window means the model can process longer documents and conversations.