Model profile
Anthropic

Claude 3.5 Sonnet (June '24)

Claude 3.5 Sonnet (June '24) is a mid-range-priced text-first model from Anthropic with partial runtime data, partial context coverage, and the clearest fit around coding / reasoning.

Best for: Coding / ReasoningN/A latencyN/A contextMid-range pricing
Intelligence
14.2

Benchmark blend

Coding
26.0

Dev workflow signal

Context
N/A

N/A

Input Price
$3.00

Mid-range tier

Decision snapshot
29

Claude 3.5 Sonnet (June '24) currently reads as a mid-range text-first option with partially published context and a partially published runtime profile.

Overall profile
Use-case specific
Best for
Coding / Reasoning
Latency tier
N/A
Price tier
Mid-range
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
14.2
14

General reasoning and benchmark headroom.

Limited
Speed
N/A
N/A

Latency data is partial.

Unavailable
Context
N/A
N/A

How much prompt and task state can stay in view.

Unavailable
Price
$3.00
62

$15.00 output / 1M

Competitive

Editorial Profile

Claude 3.5 Sonnet (June '24) 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 26Math score 70

The Claude 3.5 Sonnet (June '24) AI model by Anthropic.

Identity

Anthropic text-first profile

Positioning

Coding / Reasoning with partially published context and partially published 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 data is incomplete, so interactive responsiveness is harder to rank confidently.

  • 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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Intelligence
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Context
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Input Price
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Claude Sonnet 4.6 (Adaptive Reasoning, Max Effort)

Intelligence
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Context
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Input Price
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Anthropic

Anthropic: Claude Opus 4.5

Intelligence
49.7
Context
200K Tokens
Input Price
$5.00

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
14.2
MMLU Pro
75.1%
GPQA
56.0%
HLE
3.7%
Coding

Software implementation, debugging quality, and coding benchmark signal.

Coding Index
26.0
SciCode
31.6%
Math

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

AIME
9.7%
Math 500
69.5%

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
$3.00
Output
per 1M output tokens
$15.00
Blended
AA 3:1 mix
$6.00

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

Metadata

Raw source tables at the end

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