Model profile
Anthropic

Claude 4.1 Opus (Reasoning)

Claude 4.1 Opus (Reasoning) is a premium-priced text-first model from Anthropic with heavy runtime profile, partial context coverage, and the clearest fit around agent workflows / reasoning.

Best for: Agent workflows / ReasoningHeavy latencyN/A contextPremium pricing
Intelligence
42.0

Benchmark blend

Coding
36.5

Dev workflow signal

Context
N/A

N/A

Input Price
$15.00

Premium tier

Decision snapshot
34

Claude 4.1 Opus (Reasoning) currently reads as a premium text-first option with partially published context and a heavy runtime profile.

Overall profile
Use-case specific
Best for
Agent workflows / Reasoning
Latency tier
Heavy
Price tier
Premium
Source coverage
OpenRouterArtificial Analysis

Decision Strip

Decision rail before the raw tables

Core buy-side signals stay in one pass. The rest of the page expands only after intelligence, speed, context, and price are clear.

Intelligence
42.0
42

General reasoning and benchmark headroom.

Situational
Speed
39 tok/s
14

TTFT 8.19s

Limited
Context
N/A
N/A

How much prompt and task state can stay in view.

Unavailable
Price
$15.00
38

$75.00 output / 1M

Expensive

Editorial Profile

Claude 4.1 Opus (Reasoning) in one narrative

Positioning, tradeoffs, and fit are consolidated into one read instead of repeating the same story across separate cards.

Use-case specificCoding score 37Math score 80

The Claude 4.1 Opus (Reasoning) AI model by Anthropic.

Identity

Anthropic text-first profile

Positioning

Agent workflows / Reasoning with partially published context and heavy runtime.

Cost posture

Premium spend profile. Best when the upside justifies tighter budget control.

Strengths
  • The available source data suggests a balanced profile rather than one dominant edge.

Tradeoffs
  • Pricing sits in premium territory, so bulk usage needs tighter cost controls.

  • Latency profile is better for deliberate runs than rapid back-and-forth chat.

  • Current metadata points to a text-first profile rather than a broad multimodal one.

  • Context limits are only partially published, so long-session planning needs extra validation.

Best fit
  • Focused chat, retrieval-augmented flows, and narrower production tasks.

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Context
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Anthropic: Claude Opus 4.5

Intelligence
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Context
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Input Price
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Benchmarks

Grouped by job-to-be-done

Only benchmark categories with actual signal are shown. Secondary values stay as simple definitions instead of nested micro-cards.

General intelligence

Broad reasoning, knowledge depth, and flagship benchmark posture.

Intelligence Index
42.0
MMLU Pro
88.0%
GPQA
80.9%
HLE
11.9%
Coding

Software implementation, debugging quality, and coding benchmark signal.

Coding Index
36.5
LiveCodeBench
0.654
SciCode
40.9%
Math

Formal reasoning, structured problem solving, and competition-style math.

Math Index
80.3
AIME 2025
80.3%
Agent / tool use

Long-horizon execution quality and interactive benchmark evidence.

IFBench
55.4%
TAU2
71.4%
TerminalBench Hard
34.3%
LCR
66.3%

Specs & Pricing

Technical snapshot and cost posture

Specs stay neutral, pricing gets emphasis through values rather than extra containers. Raw provider internals remain in metadata at the end.

Technical snapshot
Context Window
N/A
Vision
Text-first
Price architecture
Input
per 1M input tokens
$15.00
Output
per 1M output tokens
$75.00
Blended
AA 3:1 mix
$30.00

This model trades into premium territory. It makes sense when capability upside matters more than raw volume efficiency.

Metadata

Raw source tables at the end

Verification details remain available, but the page no longer forces them ahead of the editorial read.