Claude Sonnet 4.6

v4.6

Anthropic

Modelcodingagenticproductionenterprise
91
Exceptional
About This Model

Anthropic's best speed/intelligence balance — the value workhorse for agentic and production workloads at $3/$15 per 1M tokens, with a 1M token context window, adaptive thinking, the effort parameter including 'max', and strong computer-use accuracy.

Last Evaluated: June 10, 2026
Official Website

Trust Vector Analysis

Dimension Breakdown

🚀Performance & Reliability
+

The value workhorse of the Claude lineup: near-Opus intelligence at Sonnet latency and price, with a 1M context window, adaptive thinking, and the full effort range including 'max'.

task accuracy code

Review of official model documentation and positioning for software engineering workloads

Evidence
Anthropic Models DocumentationRecommended model for agentic coding at the Sonnet tier; successor to Claude Sonnet 4.5
Anthropic Migration GuideDocumented as the drop-in upgrade target for Sonnet 4.5, 4.0, 3.7, and 3.5 coding workloads
highVerified: 2026-06-10
task accuracy reasoning

Review of documented thinking capabilities and reasoning benchmark positioning

Evidence
Anthropic Models DocumentationAdaptive thinking supported; effort defaults to high, scaling reasoning depth with task complexity
highVerified: 2026-06-10
task accuracy general

Comprehensive knowledge and multimodal capability review against official documentation

Evidence
Anthropic Models DocumentationPositioned as Anthropic's best combination of speed and intelligence
highVerified: 2026-06-10
output consistency

Internal testing of output stability across effort levels and adaptive thinking

Evidence
Anthropic Models DocumentationEffort parameter (low/medium/high/max) gives explicit, repeatable quality/cost control; strong computer-use accuracy with adaptive thinking at high effort
highVerified: 2026-06-10
latency p50

Median latency for API requests with standard prompt sizes

Evidence
Community benchmarkingTypical response time ~1.5s for standard prompts at low/medium effort; faster than Opus tier
mediumVerified: 2026-06-10
latency p95

95th percentile response time across diverse workloads

Evidence
Community benchmarkingp95 latency ~3.5s; higher at high/max effort with adaptive thinking
mediumVerified: 2026-06-10
context window

Official specification from provider

Evidence
Anthropic Models Documentation1M token context window; 64K max output tokens
highVerified: 2026-06-10
uptime

Historical uptime data from official status page

Evidence
Anthropic Status Page99.9%+ uptime (last 90 days)
highVerified: 2026-06-10
🛡️Security
+

Strong safety posture. Like Opus 4.6, last-assistant-turn prefills return a 400 — structured outputs (output_config.format) are the supported replacement.

prompt injection resistance

Testing against OWASP LLM01 prompt injection attacks

Evidence
Anthropic Safety ResearchStrong resistance to prompt injection in agentic and computer-use settings
highVerified: 2026-06-10
jailbreak resistance

Testing against adversarial prompt datasets

Evidence
Anthropic Constitutional AIConstitutional AI alignment with well-calibrated refusals
highVerified: 2026-06-10
data leakage prevention

Analysis of privacy policies and data handling practices

Evidence
Anthropic Privacy StatementNo training on user data without explicit consent
mediumVerified: 2026-06-10
output safety

Comprehensive safety testing across harmful content categories

Evidence
Anthropic Trust CenterReleased with comprehensive safety evaluations under the Responsible Scaling Policy
highVerified: 2026-06-10
api security

Review of API security features and best practices

Evidence
Anthropic API DocumentationAPI key authentication, HTTPS only, rate limiting; assistant prefills removed (400), closing a response-steering vector
highVerified: 2026-06-10
🔒Privacy & Compliance
+

Same enterprise-grade privacy posture as the Opus tier: ephemeral data handling, strong certifications, HIPAA eligible.

data residency

Review of enterprise documentation and privacy policies

Evidence
Anthropic Enterprise DocumentationData residency options for US and EU customers
highVerified: 2026-06-10
training data optout

Analysis of privacy policy and data usage terms

Evidence
Anthropic Privacy PolicyOpt-out available, no training on API data by default
highVerified: 2026-06-10
data retention

Review of terms of service and data retention policies

Evidence
Anthropic Terms of ServiceAPI prompts and outputs not retained (except for trust & safety)
highVerified: 2026-06-10
pii handling

Review of data protection capabilities and customer responsibilities

Evidence
Anthropic Privacy DocumentationCustomer responsible for PII redaction
mediumVerified: 2026-06-10
compliance certifications

Verification of compliance certifications and audit reports

Evidence
Anthropic Trust CenterSOC 2 Type II, GDPR compliant, HIPAA eligible
highVerified: 2026-06-10
zero data retention

Review of data handling practices

Evidence
Anthropic API DocumentationEphemeral data processing, no storage of prompts/outputs
highVerified: 2026-06-10
👁️Trust & Transparency
+

Transparent compute controls (adaptive thinking + effort) and thorough migration documentation. Follows instructions closely, reducing prompt-engineering opacity.

explainability

Evaluation of reasoning transparency and explanation capabilities

Evidence
Anthropic Models DocumentationAdaptive thinking and the effort parameter make reasoning depth explicit and controllable
highVerified: 2026-06-10
hallucination rate

Testing on factual QA datasets and real-world usage

Evidence
Anthropic TestingImproved factual calibration over Sonnet 4.5, especially with adaptive thinking enabled
mediumVerified: 2026-06-10
bias fairness

Evaluation on bias benchmarks and diverse demographic testing

Evidence
Anthropic Responsible Scaling PolicyRegular bias testing and mitigation
mediumVerified: 2026-06-10
uncertainty quantification

Qualitative assessment of confidence expression in outputs

Evidence
Model BehaviorModel expresses uncertainty appropriately; adaptive thinking scales effort with problem difficulty
mediumVerified: 2026-06-10
model card quality

Review of documentation completeness and clarity

Evidence
Anthropic Model DocumentationComprehensive model documentation with capabilities, limitations, and migration guidance from Sonnet 4.5
highVerified: 2026-06-10
training data transparency

Review of public disclosures about training data

Evidence
Anthropic Public StatementsGeneral description provided, detailed sources not disclosed
mediumVerified: 2026-06-10
guardrails

Analysis of built-in safety mechanisms

Evidence
Constitutional AIConstitutional AI safety guardrails with well-calibrated refusals
highVerified: 2026-06-10
⚙️Operational Excellence
+

Production-ready with multi-cloud availability. Migration from Sonnet 4.5 requires setting effort explicitly (4.6 defaults to high) and removing assistant prefills.

api design quality

Review of API design, consistency, and feature completeness

Evidence
Anthropic API DocumentationAdaptive thinking, effort parameter incl. max, structured outputs, streaming, tool use; prefills removed in favor of output_config.format
highVerified: 2026-06-10
sdk quality

Review of SDK quality, documentation, and maintenance

Evidence
Anthropic SDKsOfficial SDKs for Python, TypeScript, Java, Go, Ruby, C#, PHP — actively maintained
highVerified: 2026-06-10
versioning policy

Review of versioning policy and historical practices

Evidence
Anthropic API VersioningClear versioning with advance deprecation notice; documented migration path from Sonnet 4.5 and retired 3.x Sonnets
highVerified: 2026-06-10
monitoring observability

Review of available monitoring tools and metrics

Evidence
Anthropic ConsoleUsage dashboard with metrics
mediumVerified: 2026-06-10
support quality

Assessment of documentation, community, and support responsiveness

Evidence
Anthropic SupportEmail support, Discord community, comprehensive docs and migration guides
highVerified: 2026-06-10
ecosystem maturity

Analysis of third-party integrations and tools

Evidence
Cloud ProvidersAvailable on AWS Bedrock, Google Vertex AI, Azure Foundry; default model in many agent frameworks
highVerified: 2026-06-10
license terms

Review of licensing terms and restrictions

Evidence
Anthropic Terms of ServiceStandard commercial terms, enterprise agreements available
highVerified: 2026-06-10
Strengths
  • +Best speed/intelligence balance in the Claude lineup at $3/$15 per 1M tokens
  • +1M token context window with 64K max output
  • +Adaptive thinking supported — no manual thinking budgets to tune
  • +Effort parameter including 'max' (not available on Sonnet 4.5 or Haiku)
  • +Strong computer-use accuracy for agentic automation
  • +HIPAA eligible with ephemeral data handling
  • +Multi-cloud availability (AWS, GCP, Azure)
Limitations
  • !Lower ceiling than Opus tier on the hardest reasoning and long-horizon agentic tasks
  • !Removed assistant prefills — code relying on prefills returns 400
  • !Effort defaults to high — Sonnet 4.5 migrations see higher latency/cost unless effort is set explicitly
  • !64K max output (vs 128K on Opus 4.6+)
  • !No native audio capabilities
Metadata
pricing
input: $3.00 per 1M tokens
output: $15.00 per 1M tokens
notes: Same pricing as Sonnet 4.5. Batch API 50% discount. Prompt caching up to 90% savings.
last verified: 2026-06-10
context window: 1000000
max output: 64000
languages
0: English
1: Spanish
2: French
3: German
4: Italian
5: Portuguese
6: Japanese
7: Korean
8: Chinese
9: Arabic
10: Hindi
modalities
0: text
1: image (input)
2: document
3: computer-use
api endpoint: https://api.anthropic.com/v1/messages
open source: false
architecture: Transformer-based with Constitutional AI alignment, adaptive thinking, and effort parameter
parameters: Not disclosed
knowledge cutoff: Not disclosed

Use Case Ratings

code generation

Excellent agentic coding at a fraction of Opus cost. Pair effort 'medium' with adaptive thinking for the best cost/quality balance.

customer support

The sweet spot for support: fast, empathetic, and cost-effective at scale. Use effort 'low' with thinking disabled for high-volume tiers.

content creation

Strong long-form and marketing content with fast turnaround. Opus tier still leads on the most nuanced pieces.

data analysis

Solid analytical capabilities with 1M context for large datasets at workhorse pricing.

research assistant

1M context handles large corpora; adaptive thinking deepens analysis when needed. Opus preferred for the hardest synthesis tasks.

legal compliance

Strong privacy posture, HIPAA eligible, 1M context for contract repositories. Escalate the highest-stakes reviews to Opus.

healthcare

HIPAA eligible with strong privacy controls. Well-suited to clinical documentation at production volume.

financial analysis

Good quantitative reasoning with predictable cost. Use effort 'high' for complex modeling; Opus for the hardest problems.

education

Fast, patient explanations at a price point that scales to large student populations.

creative writing

Capable creative writing with good narrative flow; Opus tier produces more distinctive prose.