Model Comparison

Llama 3.3 Instruct 70B
vs. Claude Opus 5.5 (Max, Default Fallback)

Comparing 2 AI models · 0 benchmarks · Meta, Anthropic

Recommended Pick

Llama 3.3 Instruct 70B6 metric wins

Strongest on: Value, Input price, Output price

Best Value

Llama 3.3 Instruct 70B

100.0 value score

7.7 reasoning / $0.71/1M

Lowest Price

Llama 3.3 Instruct 70B

$0.71/1M input price

Best Reasoning

Claude Opus 5.5 (Max, Default Fallback)

57.6 reasoning score

Blends available reasoning benchmarks

Best for Coding

Llama 3.3 Instruct 70B

11.9 coding index

Differences That Matter

Best value

Llama 3.3 Instruct 70B has the strongest quality-to-price mix at 100.0 out of 100 value points.

Price gap

Llama 3.3 Instruct 70B is 5.6x cheaper on input tokens than Claude Opus 5.5 (Max, Default Fallback).

Reasoning gap

Claude Opus 5.5 (Max, Default Fallback) leads Llama 3.3 Instruct 70B by 49.9 points on reasoning.

Top-pick rationale

Llama 3.3 Instruct 70B wins 6 measurable categories, including Value, Input price, Output price, Blended price.

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Response Face-Off

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Llama 3.3 Instruct 70B

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Full Comparison

Metric	Top Pick Me Llama 3.3 Instruct 70B Meta	An Claude Opus 5.5 (Max, Default Fallback) Anthropic
Pricing per 1M tokens
Input Cost	$0.71/1M	$4.00/1M
Output Cost	$0.72/1M	$20.00/1M
Blended (3:1)	$0.71/1M	$8.00/1M
Specifications
Organization	Meta	Anthropic
Release Date	Dec 6, 2024	Sep 22, 2026
Performance & Speed
Throughput	92.9 tok/s	96.8 tok/s
TTFT	1720ms	666740ms
Latency	1720ms	666740ms
Composite Indices
Value Score	100.0	66.6
Reasoning Score	7.7	57.6
Intelligence	7.7	57.6
Coding	11.9	—

Key Takeaways

Llama 3.3 Instruct 70B offers the best value at $0.71/1M,making it ideal for high-volume applications and cost-conscious projects.

Claude Opus 5.5 (Max, Default Fallback) has the strongest reasoning profile with a 57.6 reasoning score,combining the available reasoning-heavy benchmarks.

Llama 3.3 Instruct 70B reaches a 11.9 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.