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Model profile
Anthropic

Claude Opus 4.5 (Reasoning)

Claude Opus 4.5 (Reasoning) is a mid-range text-first model from Anthropic with a heavy runtime profile, unknown context posture, and the clearest fit around reasoning / coding.

Best for: Reasoning / CodingHeavy latencyUnknown contextMid-range pricing
Intelligence
49.7

Benchmark blend

Coding
0.871

Dev workflow signal

Context
N/A

Unknown

Input Price
$5.00

Mid-range tier

Decision snapshot
43

Claude Opus 4.5 (Reasoning) currently reads as a mid-range text-first option with unknown context and a heavy runtime profile.

Overall profile
Use-case specific
Best for
Reasoning / Coding
Latency tier
Heavy
Price tier
Mid-range
Source coverage
OpenRouter
Compare this modelSee leaderboard

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
49.7
50

General reasoning and benchmark headroom.

Situational
Speed
64 tok/s
23

TTFT 12.23s

Limited
Context
N/A
34

How much prompt and task state can stay in view.

Limited
Price
$5.00
62

$25.00 output / 1M

Competitive

Editorial Profile

Claude Opus 4.5 (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 40Math score 36

The Claude Opus 4.5 (Reasoning) AI model by Anthropic.

Identity

Anthropic text-first profile

Positioning

Reasoning / Coding with unknown context and heavy runtime.

Cost posture

Balanced spend profile. Easier to justify in mixed production and exploration workloads.

Strengths

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

Tradeoffs

  • Costs look manageable, but still deserve attention in always-on agents or batch jobs.

  • 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.

Best fit

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

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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
49.7
MMLU Pro
89.5%
GPQA
86.6%
Coding

Software implementation, debugging quality, and coding benchmark signal.

LiveCodeBench
0.871

Extra benchmark cuts are not available for this category yet.

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
$5.00
Output
per 1M output tokens
$25.00
Blended
AA 3:1 mix
N/A

This model sits in a balanced spend range. It is easier to justify across both production and exploratory workflows.