Model Comparison
Llama 3.2 Instruct 11B (Vision)
vs. GPT-5.5 (xhigh)
Comparing 2 AI models · 12 benchmarks · Meta, OpenAI
Recommended Pick
Op GPT-5.5 (xhigh) 10 metric wins Strongest on: Reasoning, Intelligence, Coding
Best Value
Llama 3.2 Instruct 11B (Vision)
100.0 value score
14.3 reasoning / $0.24/1M
Lowest Price
Llama 3.2 Instruct 11B (Vision)
$0.24/1M input price
Best Reasoning
GPT-5.5 (xhigh)
66.0 reasoning score
Blends available reasoning benchmarks
Best for Coding
GPT-5.5 (xhigh)
59.1 coding index
Composite Indices
Higher is better; speed and price are normalized
Standard Benchmarks
Only benchmarks with data are shown
Differences That Matter
Best value
Llama 3.2 Instruct 11B (Vision) has the strongest quality-to-price mix at 100.0 out of 100 value points.
Price gap
Llama 3.2 Instruct 11B (Vision) is 20.4x cheaper on input tokens than GPT-5.5 (xhigh).
Speed gap
Llama 3.2 Instruct 11B (Vision) generates about 1.4x as many tokens per second as GPT-5.5 (xhigh).
Reasoning gap
GPT-5.5 (xhigh) leads Llama 3.2 Instruct 11B (Vision) by 51.7 points on reasoning.
Coding gap
GPT-5.5 (xhigh) leads Llama 3.2 Instruct 11B (Vision) by 54.9 points on coding.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
Llama 3.2 Instruct 11B (Vision)
Meta
TTFT
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Time
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tok/s
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Tokens
—
Cost
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GPT-5.5 (xhigh)
OpenAI
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
Which answer was more useful?
Full Comparison
| Metric | Me Llama 3.2 Instruct 11B (Vision) | Top Pick Op GPT-5.5 (xhigh) |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.24/1M | $5.00/1M |
| Output Cost | $0.24/1M | $30.00/1M |
| Blended (3:1) | $0.24/1M | $11.25/1M |
| Specifications | ||
| Organization | Meta | OpenAI |
| Release Date | Sep 25, 2024 | Apr 23, 2026 |
| Performance & Speed | ||
| Throughput | 87.5 tok/s | 62.4 tok/s |
| TTFT | 491ms | 74068ms |
| Latency | 491ms | 74068ms |
| Composite Indices | ||
| Value Score | 100.0 | 10.0 |
| Reasoning Score | 14.3 | 66.0 |
| Intelligence | 8.7 | 60.2 |
| Coding | 4.2 | 59.1 |
| Math | 1.7 | — |
| Standard Benchmarks | ||
| GPQA | 22.1% | 93.5% |
| MMLU Pro | 46.4% | — |
| HLE | 5.2% | 44.3% |
| LiveCodeBench | 11.0% | — |
| MATH 500 | 51.6% | — |
| AIME 2025 | 1.7% | — |
| AIME (Original) | 9.3% | — |
| SciCode | 11.2% | 56.1% |
| LCR | 11.7% | 74.3% |
| IFBench | 30.4% | 75.9% |
| TAU-bench v2 | 14.6% | 93.9% |
| TerminalBench Hard | 0.8% | 60.6% |
Key Takeaways
Llama 3.2 Instruct 11B (Vision) offers the best value at $0.24/1M, making it ideal for high-volume applications and cost-conscious projects.
GPT-5.5 (xhigh) has the strongest reasoning profile with a 66.0 reasoning score, combining the available reasoning-heavy benchmarks.
GPT-5.5 (xhigh) reaches a 59.1 coding index, making it the top choice for software development and code generation tasks.
All models support context windows of ∞+ tokens, suitable for processing lengthy documents and maintaining extended conversations.
When to Choose Each Model
Llama 3.2 Instruct 11B (Vision)
- Cost-sensitive applications
- High-volume processing
GPT-5.5 (xhigh)
- Complex reasoning tasks
- Research & analysis
- Code generation
- Software development
