| Signal | Llama 3.2 11B Vision Instruct | Delta | Mistral Large 2411 |
|---|---|---|---|
Capabilities | 50 | -- | |
Pricing | 0 | -6 | |
Context window size | 81 | -- | |
Recency | 32 | -10 | |
Output Capacity | 70 | +50 | |
| Overall Result | 1 wins | of 5 | 2 wins |
9
days higher
3
days
18
days higher
Meta
Mistral AI
Llama 3.2 11B Vision Instruct saves you $492.65/month
That's $5911.80/year compared to Mistral Large 2411 at your current usage level of 100K calls/month.
| Metric | Llama 3.2 11B Vision Instruct | Mistral Large 2411 | Winner |
|---|---|---|---|
| Overall Score | 40 | 40 | -- |
| Rank | #286 | #284 | Mistral Large 2411 |
| Quality Rank | #286 | #284 | Mistral Large 2411 |
| Adoption Rank | #286 | #284 | Mistral Large 2411 |
| Parameters | 11B | -- | -- |
| Context Window | 131K | 131K | -- |
| Pricing | $0.05/$0.05/M | $2.00/$6.00/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 50 | Llama 3.2 11B Vision Instruct |
| Pricing | 0 | 6 | Mistral Large 2411 |
| Context window size | 81 | 81 | Llama 3.2 11B Vision Instruct |
| Recency | 32 | 42 | Mistral Large 2411 |
| Output Capacity | 70 | 20 | Llama 3.2 11B Vision Instruct |
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 #286), placing it in the top 2% of all 290 models tracked.
Scores 40/100 (rank #284), placing it in the top 2% 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 3.2 11B Vision Instruct offers 99% better value per quality point. At 1M tokens/day, you'd spend $1.47/month with Llama 3.2 11B Vision Instruct vs $120.00/month with Mistral Large 2411 - a $118.53 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 (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 (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 3.2 11B Vision Instruct and Mistral Large 2411 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 3.2 11B Vision Instruct
Marginally better benchmark scores; both are excellent
Best for Cost
Llama 3.2 11B Vision Instruct
99% lower pricing; better value at scale
Best for Reliability
Llama 3.2 11B Vision Instruct
Higher uptime and faster response speeds
Best for Prototyping
Llama 3.2 11B Vision Instruct
Stronger community support and better developer experience
Best for Production
Llama 3.2 11B Vision Instruct
Wider enterprise adoption and proven at scale
by Meta
| Capability | Llama 3.2 11B Vision Instruct | Mistral Large 2411 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Meta
Mistral AI
Llama 3.2 11B Vision Instruct saves you $10.65/month
That's 99% cheaper than Mistral Large 2411 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 3.2 11B Vision Instruct | Mistral Large 2411 |
|---|---|---|
| Context Window | 131K | 131K |
| Max Output Tokens | 16,384 | -- |
| Open Source | Yes | No |
| Created | Sep 25, 2024 | Nov 19, 2024 |
Both Llama 3.2 11B Vision Instruct and Mistral Large 2411 score 40/100, making them extremely close competitors. Choose based on pricing, provider ecosystem, or specific capability requirements.
Llama 3.2 11B Vision Instruct is ranked #286 and Mistral Large 2411 is ranked #284 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 3.2 11B Vision Instruct is cheaper at $0.05/M output tokens vs Mistral Large 2411's $6.00/M output tokens - 122.4x more expensive. Input token pricing: Llama 3.2 11B Vision Instruct at $0.05/M vs Mistral Large 2411 at $2.00/M.
Llama 3.2 11B Vision Instruct has a larger context window of 131,072 tokens compared to Mistral Large 2411's 131,072 tokens. A larger context window means the model can process longer documents and conversations.