Model Comparison
Llama 65B
vs. o3
Comparing 2 AI models · 12 benchmarks · Meta, OpenAI
Recommended Pick
Me Llama 65B 4 metric wins Strongest on: Input price, Output price, TTFT
Lowest Price
Llama 65B
$0.00/1M input price
Best Reasoning
o3
71.3 reasoning score
Blends available reasoning benchmarks
Composite Indices
Higher is better; speed and price are normalized
Standard Benchmarks
Only benchmarks with data are shown
Differences That Matter
Price gap
Llama 65B is ∞x cheaper on input tokens than o3.
Reasoning gap
o3 leads Llama 65B by 69.2 points on reasoning.
Top-pick rationale
Llama 65B wins 4 measurable categories, including Input price, Output price, TTFT, Latency.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
Llama 65B
Meta
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
o3
OpenAI
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
Which answer was more useful?
Full Comparison
| Metric | Top Pick Me Llama 65B | Op o3 |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.00/1M | $2.00/1M |
| Output Cost | $0.00/1M | $8.00/1M |
| Blended (3:1) | — | $3.50/1M |
| Specifications | ||
| Organization | Meta | OpenAI |
| Release Date | Feb 24, 2023 | Apr 16, 2025 |
| Performance & Speed | ||
| Throughput | — | 122.0 tok/s |
| TTFT | — | 7671ms |
| Latency | — | 7671ms |
| Composite Indices | ||
| Value Score | — | 100.0 |
| Reasoning Score | 2.1 | 71.3 |
| Intelligence | 2.1 | 30.4 |
| Math | — | 88.3 |
| Standard Benchmarks | ||
| GPQA | — | 82.7% |
| MMLU Pro | — | 85.3% |
| HLE | — | 20.0% |
| LiveCodeBench | — | 80.8% |
| MATH 500 | — | 99.2% |
| AIME 2025 | — | 88.3% |
| AIME (Original) | — | 90.3% |
| SciCode | — | 41.0% |
| LCR | — | 69.3% |
| IFBench | — | 71.4% |
| TAU-bench v2 | — | 80.7% |
| TerminalBench Hard | — | 37.1% |
Key Takeaways
Llama 65B offers the best value at $0.00/1M, making it ideal for high-volume applications and cost-conscious projects.
o3 has the strongest reasoning profile with a 71.3 reasoning score, combining the available reasoning-heavy benchmarks.
All models support context windows of ∞+ tokens, suitable for processing lengthy documents and maintaining extended conversations.
When to Choose Each Model
Llama 65B
- Cost-sensitive applications
- High-volume processing
o3
- Complex reasoning tasks
- Research & analysis
