Compare the listed model data for Anthropic Claude Opus 4.8 by Anthropic and Anthropic Claude Opus 4.7 by Anthropic. Benchmark and pricing records are not a controlled test and may change.
Data last updated: 2026-10-16. Verify current model details with each provider.
Anthropic Claude Opus 4.8: 200K tokens; Anthropic Claude Opus 4.7: 200K tokens. The listed context-window values are equal. Anthropic Claude Opus 4.8 is listed for coding, reasoning, vision, multimodal input, agentic workflows, long-context tasks; Anthropic Claude Opus 4.7 is listed for coding, reasoning, vision, multimodal input, agentic workflows, long-context tasks. Shared catalog benchmark entries: MMLU: Anthropic Claude Opus 4.8 92.1%; Anthropic Claude Opus 4.7 91.6%; HumanEval: Anthropic Claude Opus 4.8 90.5%; Anthropic Claude Opus 4.7 89.2%; GPQA: Anthropic Claude Opus 4.8 74.3%; Anthropic Claude Opus 4.7 72.8%; SWE-bench Verified: Anthropic Claude Opus 4.8 62.3%; Anthropic Claude Opus 4.7 58.4%. These records are reference data, not a controlled head-to-head test; verify current pricing and specifications with each provider.
Use these model and provider links to verify current specifications, pricing, and availability.
Using only the catalog's listed per-million-token rates, 1M input plus 1M output tokens costs about $36 for Anthropic Claude Opus 4.8 and $30 for Anthropic Claude Opus 4.7. This excludes provider-specific discounts, caching, and other fees.
Choose Anthropic Claude Opus 4.8 when your task aligns with catalog-listed uses or strengths such as Complex enterprise analysis requiring maximum accuracy: financial modeling, legal review, scientific research, Long-document processing: contracts, research papers, technical specifications up to 200K tokens, Agentic software engineering: autonomous multi-file codebase changes and complex debugging, Graduate-level academic and scientific reasoning requiring deep domain knowledge.
Choose Anthropic Claude Opus 4.7 when your task aligns with catalog-listed uses or strengths such as Product design analysis, UI/UX critique, and aesthetic evaluation, Complex multi-step reasoning tasks in finance, law, and science, Agentic coding workflows requiring architectural decision-making, High-quality long-form writing combining technical accuracy with compelling narrative.
Anthropic's most powerful model ever. Deeper reasoning, stronger agentic coding, superior design sense, and sharper analytical precision than Opus 4.7.
Parameters: ~200B+ (frontier MoE, exact size proprietary)
Context: 200K tokens
Catalog pricing: Access via LITHOVEX AI free. Anthropic API: high-tier pricing.
Excels in design, aesthetic quality, and nuanced reasoning. Perfect for agentic coding and complex long-running tasks.
Parameters: ~200B+ (frontier class, exact size proprietary)
Context: 200K tokens
Catalog pricing: Via LITHOVEX AI free.
| Specification | Anthropic Claude Opus 4.8 | Anthropic Claude Opus 4.7 |
|---|---|---|
| Provider | Anthropic | Anthropic |
| Parameters | ~200B+ (frontier MoE, exact size proprietary) | ~200B+ (frontier class, exact size proprietary) |
| Context window | 200K tokens | 200K tokens |
| Maximum output | Not listed | Not listed |
| Catalog pricing | Access via LITHOVEX AI free. Anthropic API: high-tier pricing. | Via LITHOVEX AI free. |
| Listed input/output cost per 1M tokens | input $6, output $30 per 1M tokens | input $5, output $25 per 1M tokens |
| License | Proprietary | Proprietary |
| Coding support | Listed | Listed |
| Reasoning support | Listed | Listed |
| Vision input | Listed | Listed |
| Multimodal | Listed | Listed |
| Open weights | No | No |
| Benchmark: MMLU | 92.1% | 91.6% |
| Benchmark: HumanEval | 90.5% | 89.2% |
| Benchmark: GPQA | 74.3% | 72.8% |
| Benchmark: SWE-bench Verified | 62.3% | 58.4% |
Figures are transcribed from LITHOVEX model records. Benchmark versions and evaluation setups may differ; pricing and specifications can change. Check each provider's current documentation before making a decision.
Read the Anthropic Claude Opus 4.8 model profile and Anthropic Claude Opus 4.7 model profile, or browse the model directory.