Model Comparison
Llama 3.1 Instruct 8B
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 3.1 Instruct 8B
100.0 value score
15.9 reasoning / $0.10/1M
Lowest Price
Llama 3.1 Instruct 8B
$0.10/1M 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 3.1 Instruct 8B has the strongest quality-to-price mix at 100.0 out of 100 value points.
Price gap
Llama 3.1 Instruct 8B is 50x cheaper on input tokens than GPT-5.5 (xhigh).
Speed gap
Llama 3.1 Instruct 8B generates about 3.5x as many tokens per second as GPT-5.5 (xhigh).
Reasoning gap
GPT-5.5 (xhigh) leads Llama 3.1 Instruct 8B by 50.1 points on reasoning.
Coding gap
GPT-5.5 (xhigh) leads Llama 3.1 Instruct 8B by 54.2 points on coding.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
Llama 3.1 Instruct 8B
Meta
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
GPT-5.5 (xhigh)
OpenAI
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
Which answer was more useful?
Full Comparison
| Metric | Me Llama 3.1 Instruct 8B | Top Pick Op GPT-5.5 (xhigh) |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.10/1M | $5.00/1M |
| Output Cost | $0.10/1M | $30.00/1M |
| Blended (3:1) | $0.10/1M | $11.25/1M |
| Specifications | ||
| Organization | Meta | OpenAI |
| Release Date | Jul 23, 2024 | Apr 23, 2026 |
| Performance & Speed | ||
| Throughput | 204.0 tok/s | 58.6 tok/s |
| TTFT | 563ms | 70541ms |
| Latency | 563ms | 70541ms |
| Composite Indices | ||
| Value Score | 100.0 | 3.7 |
| Reasoning Score | 15.9 | 66.0 |
| Intelligence | 11.8 | 60.2 |
| Coding | 4.9 | 59.1 |
| Math | 4.3 | — |
| Standard Benchmarks | ||
| GPQA | 25.9% | 93.5% |
| MMLU Pro | 47.6% | — |
| HLE | 5.1% | 44.3% |
| LiveCodeBench | 11.6% | — |
| MATH 500 | 51.9% | — |
| AIME 2025 | 4.3% | — |
| AIME (Original) | 7.7% | — |
| SciCode | 13.2% | 56.1% |
| LCR | 15.7% | 74.3% |
| IFBench | 28.6% | 75.9% |
| TAU-bench v2 | 16.4% | 93.9% |
| TerminalBench Hard | 0.8% | 60.6% |
Key Takeaways
Llama 3.1 Instruct 8B offers the best value at $0.10/1M, 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 3.1 Instruct 8B
- Cost-sensitive applications
- High-volume processing
GPT-5.5 (xhigh)
- Complex reasoning tasks
- Research & analysis
- Code generation
- Software development
Recommended Comparisons
Popular alternatives 
