Model profile
anthropic

Anthropic: Claude 3.7 Sonnet

Anthropic: Claude 3.7 Sonnet is a mid-range multimodal generalist from anthropic with a heavy runtime profile, large context posture, and the clearest fit around long-context research / multimodal.

Best for: Long-context research / MultimodalHeavy latencyLarge contextMid-range pricing
Intelligence
34.7

Benchmark blend

Coding
26.7

Dev workflow signal

Context
200K Tokens

Large

Input Price
$3.00

Mid-range tier

Decision snapshot
48

Anthropic: Claude 3.7 Sonnet currently reads as a mid-range multimodal option with large context and a heavy runtime profile.

Overall profile
Use-case specific
Best for
Long-context research / Multimodal
Latency tier
Heavy
Price tier
Mid-range
Source coverage
OpenRouterArtificial AnalysisVision signal

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
34.7
35

General reasoning and benchmark headroom.

Limited
Speed
N/A
46

Latency data is partial.

Situational
Context
200K Tokens
88

How much prompt and task state can stay in view.

Above average
Price
$3.00
62

$15.00 output / 1M

Competitive

Editorial Profile

Anthropic: Claude 3.7 Sonnet 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 27Math score 21Vision enabled

Claude 3.7 Sonnet is an advanced large language model with improved reasoning, coding, and problem-solving capabilities. It introduces a hybrid reasoning approach, allowing users to choose between rapid responses and extended, step-by-step processing for complex tasks. The model demonstrates notable improvements in coding, particularly in front-end development and full-stack updates, and excels in agentic workflows, where it can autonomously navigate multi-step processes. Claude 3.7 Sonnet maintains performance parity with its predecessor in standard mode while offering an extended reasoning mode for enhanced accuracy in math, coding, and instruction-following tasks. Read more at the [blog post here](https://www.anthropic.com/news/claude-3-7-sonnet)

Identity

anthropic multimodal profile

Positioning

Long-context research / Multimodal with large context and heavy runtime.

Cost posture

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

Strengths
  • Large context headroom supports repo-wide prompts and long research sessions.

  • Vision-capable routing opens up multimodal review and extraction workflows.

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.

Best fit
  • Image-grounded review, multimodal extraction, and UI audit workflows.

  • Long-context summarization, repo analysis, and policy or document review.

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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
34.7
MMLU Pro
83.7%
GPQA
77.2%
HLE
4.8%
Coding

Software implementation, debugging quality, and coding benchmark signal.

Coding Index
26.7
LiveCodeBench
0.394
SciCode
37.6%
Math

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

Math Index
21.0
AIME
22.3%
AIME 2025
21.0%
Math 500
85.0%
Agent / tool use

Long-horizon execution quality and interactive benchmark evidence.

IFBench
44.0%
TAU2
50.0%
TerminalBench Hard
21.2%
LCR
48.3%

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
200K Tokens
Vision
Enabled
Modalities
text, image, file->text, file
Tokenizer
Claude
Max Completion
64000
Moderation
No
Supported Parameters
include_reasoningmax_tokensreasoningstoptemperaturetool_choicetoolstop_ktop_p
Input Modalities
textimagefile
Output Modalities
text
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.

OR Web Search Price
$0.0100
OR Cache Read
$0.00
OR Cache Write
$0.00

Metadata

Raw source tables at the end

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