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Anthropic · Frontier

Claude 4.7 Opus Thinking

Added Apr 16, 2026

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Use in the app

Claude Opus 4.7 with thinking enabled (default budget: 16k tokens).

  • Reasoning
  • Tools
  • Vision
  • Structured output
  • PDF input
Input
Text, Images
Output
Text
Reasoning effort
low · medium · high · xhigh · max
Discovery tier
Frontier

Pricing

USD per 1M tokens
Input
$5.00
Output
$25.00
Cache read
$0.50

Reference prices as published by the model provider. API example

Specifications

Context window
1M
Max output
128K
Average output (7 days)
1.9K tokens
Longer than 90% of 473 models

Side by side

Claude 4.7 Opus Thinking compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

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Claude 4.7 Opus ThinkingAnthropicThis modelClaude Opus LatestAnthropicRemove
ProviderAnthropicAnthropic
Discovery tierFrontierFrontier
AddedApr 16, 2026Mar 29, 2026
Limits
Context window1M1M
Max output128K128K
Average output1.9K tokens—
Pricing, USD per 1M tokens
Input$5.00$4.00Best
Output$25.00$20.00Best
Cache read$0.50$0.20Best
Cache write—$5.00
Performance
Throughput98.9 tok/s133.5 tok/sBest
Time to first token3.0 sBest9.0 s
Request success (24h)99.1%99.8%Best
Benchmark indexes
Intelligence Index40.753.6Best
Coding Index73.6—
Capabilities
ReasoningYesYes
ToolsYesYes
VisionYesYes
Structured outputYesYes
PDF inputYesYes
Reasoning effortlow, medium, high, xhigh, maxlow, medium, high, xhigh, max

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

  • Claude 4.7 Opus Thinking
  • Claude Opus Latest

Intelligence Index

  • Claude 4.7 Opus Thinking40.7
  • Claude Opus Latest53.6

Claude 4.7 Opus Thinking tested at max reasoning effort

Claude 4.7 Opus Thinking: Better than 85% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • Claude 4.7 Opus Thinking: 73.6
    • Claude Opus Latest: —

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Claude 4.7 Opus Thinking: —
    • Claude Opus Latest: 63.2%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Claude 4.7 Opus Thinking: —
    • Claude Opus Latest: 33.8%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Claude 4.7 Opus Thinking: 1,252 Elo
    • Claude Opus Latest: 1,683 EloTop

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Claude 4.7 Opus Thinking: 1,353 Elo
    • Claude Opus Latest: 1,704 EloTop

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Claude 4.7 Opus Thinking: —
    • Claude Opus Latest: 28.8%

  • AA-LCRv1.1

    Reasoning across long documents

    • Claude 4.7 Opus Thinking: 78.7%
    • Claude Opus Latest: 82.7%Top

  • MLCR-AA

    Long-context reasoning over medical records

    • Claude 4.7 Opus Thinking: —
    • Claude Opus Latest: 15.0%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Claude 4.7 Opus Thinking: 42.3%
    • Claude Opus Latest: 55.6%Top

  • GPQA Diamond

    Graduate-level science questions

    • Claude 4.7 Opus Thinking: 91.4%
    • Claude Opus Latest: —

  • IFBench

    Following precise output instructions

    • Claude 4.7 Opus Thinking: 58.6%
    • Claude Opus Latest: —

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Claude 4.7 Opus Thinking: —
    • Claude Opus Latest: 56.6%

  • SciCode

    Scientific computing in Python

    • Claude 4.7 Opus Thinking: —
    • Claude Opus Latest: 60.4%

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Claude 4.7 Opus Thinking: 51.5%
    • Claude Opus Latest: —

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • Claude 4.7 Opus Thinking: 88.6%
    • Claude Opus Latest: —

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Claude 4.7 Opus Thinking: 78.7%
    • Claude Opus Latest: 82.7%Top

Scores from Artificial Analysis, updated Oct 26, 2026. Claude 4.7 Opus Thinking was tested at max reasoning effort; compare scores measured at the same effort.Artificial Analysis

Live routing data

Performance and reliability

Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.

Throughput
98.9 tok/s
Faster than 62% of 256 models
Time to first token
3.0 s
Quicker than 51% of 256 models
Prompt cache hits
55.9%
About $2.48 per 1M input tokens with caching
Request success (24h)
99.1%
Reliable

Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.

Hourly request success · last 72 hoursLowest hour 85.7%
  • Healthy (98% or more)
  • Degraded (90–98%)
  • Down (under 90%)
  • No requests

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart
curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "anthropic/claude-opus-4.7:thinking",
    "reasoning_effort": "medium",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'
import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="anthropic/claude-opus-4.7:thinking",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Anthropic

Other Anthropic models, starting with the same family.