Anthropic Claude Opus 5 (1M context) vs Meta Llama 5 Behemoth (2M)
Side-by-side comparison of pricing, context window, capabilities, and a real-cost sample workload.
Option A
Anthropic Claude Opus 5 (1M context)
by Anthropic
Context:1M
Input:$6.00 / 1M
Output:$30.00 / 1M
Released:2026-07
Option B
Meta Llama 5 Behemoth (2M)
by Meta
Context:2M
Input:$1.20 / 1M
Output:$4.00 / 1M
Released:2026-06
Detailed Comparison
| Dimension | Anthropic Claude Opus 5 (1M context) | Meta Llama 5 Behemoth (2M) |
|---|---|---|
| Provider | Anthropic | Meta |
| Context window Winner | 1M | 2M |
| Input price ($/1M) Winner | $6.00 | $1.20 |
| Output price ($/1M) Winner | $30.00 | $4.00 |
| Sample workload cost Winner 1M input + 500K output tokens | $21.00 | $3.20 |
| Released Winner | 2026-07 | 2026-06 |
| Tokenizer | claude-4 | llama |
The verdict
On the dimensions we measured, Meta Llama 5 Behemoth (2M) wins more often - particularly on cost-effectiveness for a typical 1M+0.5M workload.
Anthropic Claude Opus 5 (1M context) - Key features
The 1M-token context tier of Claude Opus 5. Same model, long-context premium pricing applied to requests above 200K input tokens. Built for whole-repository and whole-corpus work.
- 1M token context window
- Whole-repository reasoning
- Long-context premium tier
- Prompt caching support
- Adaptive effort control
Meta Llama 5 Behemoth (2M) - Key features
Meta's largest released model, positioned against closed frontier systems. Behemoth is served through partners rather than being practical to self-host, and it leads open-weight benchmarks on reasoning and math.
- Largest open-weight model to date
- 2M token context window
- Frontier-level reasoning and math
- Mixture-of-experts
- Partner-hosted inference
How to choose
- Pick the cheaper model if your workload is mostly straightforward classification, extraction, or summarization.
- Pick the bigger context if you process long documents, large codebases, or multi-document research.
- Pick the more recent release if you need state-of-the-art reasoning quality and don't mind paying a bit more.
- Use both via a routing layer - send simple tasks to the cheaper one and complex tasks to the smarter one. This is the highest-ROI optimization in production AI.
Estimate the real cost of either model for your prompts using our Token Calculator.