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Claude Opus 4.7 vs Claude Opus 4.8

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Claude Opus 4.7 and Claude Opus 4.8.

Anthropic

Claude Opus 4.7

Opus 4.7 is the next generation of Anthropic's Opus family, built for long-running, asynchronous agents. Building on the coding and agentic strengths of Opus 4.6, it delivers stronger performance on...

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Anthropic

Claude Opus 4.8

Claude Opus 4.8 is Anthropic's most capable generally available model in the Opus family. It supports text, image, and file inputs with text output, with reasoning support and a 1M-token...

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Technical Specifications

SpecificationClaude Opus 4.7Claude Opus 4.8
ProviderAnthropicAnthropic
Context Window1,000,000 tokens1,000,000 tokens
Agent Suitability96/10097/100
Time to First Token (TTFT)480 ms520 ms
Deployment Modelmanaged apimanaged api
Production Stabilitystablebeta
API AvailableYesYes
Released Date2026-04-162026-05-27

API Pricing Comparison

Input Price per Million Tokens

Claude Opus 4.7

$5.00

Claude Opus 4.8

$5.00

Output Price per Million Tokens

Claude Opus 4.7

$25.00

Claude Opus 4.8

$25.00

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

MMLUGeneral knowledge & multi-task understanding
9410.0%vs9540.0%
Claude Opus 4.7
Claude Opus 4.8
HumanEvalPython coding & logic synthesis
9610.0%vs9720.0%
Claude Opus 4.7
Claude Opus 4.8
MATHComplex mathematical problem solving
9150.0%vs9410.0%
Claude Opus 4.7
Claude Opus 4.8
GPQAGraduate-level expert reasoning
8420.0%vs8650.0%
Claude Opus 4.7
Claude Opus 4.8
HellaSwagCommonsense reasoning and inference
9880.0%vs9920.0%
Claude Opus 4.7
Claude Opus 4.8
MT-BenchMulti-turn conversation flow quality
975.0%vs980.0%
Claude Opus 4.7
Claude Opus 4.8

Claude Opus 4.7 Quirks & Gotchas

  • โ–ธTop-tier agentic coding model โ€” excels at autonomous software engineering
  • โ–ธRequires explicit tool_choice parameter for parallel function calling to work reliably

Claude Opus 4.8 Quirks & Gotchas

  • โ–ธBest-in-class for autonomous code repair and multi-agent orchestration
  • โ–ธPreview model โ€” API may introduce breaking changes without notice