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Claude Sonnet 5 (Adaptive Reasoning, Low Effort)

★ featured
Anthropic · released 2026-06-30 · 14 recorded token offers

Top 5 cheapest providers (Adjusted $/task)

Within the active global provider, residency and confidentiality filters.

#ProviderPlatformRaw input $/1MRaw output $/1MAdjusted $/task
1Google Vertex AIGoogle Vertex AI$2.00$10.00
2AnthropicAnthropic$2.00$10.00
3Claude Platform on AWSOpenRouter$2.00$10.00
4AzureOpenRouter$2.00$10.00
5GoogleOpenRouter$2.00$10.00

Benchmarks

Composite80.2
Composite evidence1/5
AA Coding · unversioned snapshot 2026-09-10
AA Coding Agent · v1.4 · 2026-09-09
AA Intelligence · unversioned snapshot 2026-09-1024.7
DesignArena Frontend · unversioned snapshot 2026-09-10
DesignArena Full-Stack · unversioned snapshot 2026-09-10
Output speed (t/s)65

MODEL EVIDENCE

Benchmark sheet

10 / 73 registered benchmark versions covered · 11 observations including existing index snapshots.

Compare this model ↗
Composite retains Coding Agent v1.4 · source 2026-09-09

The five Composite inputs remain unchanged. Its Coding Agent input is the median across complete harness results in the retained v1.4 snapshot from 2026-09-09. Artificial Analysis now publishes v1.5, with different components. Explore current v1.5 separately. Dated snapshot labels on other indices identify unversioned source captures, not a verified semantic version.

Profile signals

No threshold-crossing signal · 11 eligible benchmark families

How flags are calculated

Heuristic screen, not statistical significance: benchmark families are correlated and source uncertainty is unknown. Peer evidence needs ≥ 20 independently measured matched configurations from ≥ 10 distinct model families. A flag needs a directed population z-score of magnitude ≥ 1.5 and a gap of ≥ 1.5 from the leave-one-benchmark-family-out mean z in the same direction, over ≥ 5 other benchmark families.

Protocol-compatible measured/vendor divergences

No verified protocol-compatible vendor/measured pair is available for this model; agreement cannot be assessed.

Agentic

Agentic: every observation for this exact model configuration
Benchmark / versionEvaluation groupScore / provenance
AA-Briefcase

Version snapshot-2026-09-10

Published board

Tests multi-week professional knowledge-work projects with linked tasks and large source collections.

927.41 Elomeasuredobserved 2026-09-10artificialanalysis.ai
Evidence
Axis: AA-Briefcase · snapshot-2026-09-10 · Published board
Exact value: 927.41 Elo
Observed: 2026-09-10T21:47:16.627Z · publication date: not recorded
Observation id: aa:142b93bf-09c4-42dc-9c3a-50b1a222cbd4:briefcaseBreakdown.overall.elo
GDPval-AA v2

Version 2

Published board

Tests professional knowledge-work deliverables across occupations using AA's Stirrup harness.

1145.04 Elomeasuredobserved 2026-09-10artificialanalysis.ai
Evidence
Axis: GDPval-AA v2 · 2 · Published board
Exact value: 1145.04 Elo
Observed: 2026-09-10T21:47:16.627Z · publication date: not recorded
Observation id: aa:142b93bf-09c4-42dc-9c3a-50b1a222cbd4:gdpval
Terminal-Bench v4.0 (AA)

Version 4.0

Published board

Tests terminal-based work on the 66-task release using mini-SWE-agent v2.4.6.

0.02525 fractionmeasuredobserved 2026-09-10artificialanalysis.ai
Evidence
Axis: Terminal-Bench v4.0 (AA) · 4.0 · Published board
Exact value: 0.0252525252525253 fraction
Observed: 2026-09-10T21:47:16.627Z · publication date: not recorded
Observation id: aa:142b93bf-09c4-42dc-9c3a-50b1a222cbd4:terminalbenchV40

Coding

Coding: every observation for this exact model configuration
Benchmark / versionEvaluation groupScore / provenance
SciCode (AA subproblems)

Version 1.0.1

Published board

Tests scientific Python programming with scientist-annotated background information.

0.50116 fractionmeasuredobserved 2026-09-10artificialanalysis.ai
Evidence
Axis: SciCode (AA subproblems) · 1.0.1 · Published board
Exact value: 0.501157407407407 fraction
Observed: 2026-09-10T21:47:16.627Z · publication date: not recorded
Observation id: aa:142b93bf-09c4-42dc-9c3a-50b1a222cbd4:scicode

Knowledge

Knowledge: every observation for this exact model configuration
Benchmark / versionEvaluation groupScore / provenance
Humanity's Last Exam (AA text-only)

Version snapshot-2026-09-10

Published board

Tests expert-level knowledge on AA's text-only Humanity's Last Exam subset.

0.21918 fractionmeasuredobserved 2026-09-10artificialanalysis.ai
Evidence
Axis: Humanity's Last Exam (AA text-only) · snapshot-2026-09-10 · Published board
Exact value: 0.219184430027804 fraction
Observed: 2026-09-10T21:47:16.627Z · publication date: not recorded
Observation id: aa:142b93bf-09c4-42dc-9c3a-50b1a222cbd4:hle
AA-Omniscience Index

Version snapshot-2026-09-10

Published board

Tests factual reliability while rewarding correct answers and penalizing hallucinations.

-8.23333 pointsmeasuredobserved 2026-09-10artificialanalysis.ai
Evidence
Axis: AA-Omniscience Index · snapshot-2026-09-10 · Published board
Exact value: -8.23333333333333 points
Observed: 2026-09-10T21:47:16.627Z · publication date: not recorded
Observation id: aa:142b93bf-09c4-42dc-9c3a-50b1a222cbd4:omniscience

Long-context

Long-context: every observation for this exact model configuration
Benchmark / versionEvaluation groupScore / provenance
GDP.pdf (AA)

Version snapshot-2026-09-10

Published board

Tests professional reasoning over long PDFs with AA document preparation and grading.

0.094 fractionmeasuredobserved 2026-09-10artificialanalysis.ai
Evidence
Axis: GDP.pdf (AA) · snapshot-2026-09-10 · Published board
Exact value: 0.094 fraction
Observed: 2026-09-10T21:47:16.627Z · publication date: not recorded
Observation id: aa:142b93bf-09c4-42dc-9c3a-50b1a222cbd4:gdpPdfAllPass
AA-LCR v1.1

Version 1.1

Published board

Tests reasoning across multiple long documents with corrected answer keys and grading.

0.67333 fractionmeasuredobserved 2026-09-10artificialanalysis.ai
Evidence
Axis: AA-LCR v1.1 · 1.1 · Published board
Exact value: 0.673333333333333 fraction
Observed: 2026-09-10T21:47:16.627Z · publication date: not recorded
Observation id: aa:142b93bf-09c4-42dc-9c3a-50b1a222cbd4:lcr

Reasoning

Reasoning: every observation for this exact model configuration
Benchmark / versionEvaluation groupScore / provenance
AA Intelligence Index

Version snapshot-2026-09-10 (unversioned)

Published board

Published AA index from the retained API snapshot. No verified semantic version was supplied.

24.7 pointsmeasuredobserved 2026-09-10artificialanalysis.ai
Evidence
Axis: AA Intelligence Index · snapshot-2026-09-10 (unversioned) · Published board
Exact value: 24.7 points
Observed: 2026-09-10 · publication date: not recorded
Observation id: legacy:aa_intelligence_index:claude-sonnet-5::low
Protocol: inspect · file data/raw/artificialanalysis.json

Science

Science: every observation for this exact model configuration
Benchmark / versionEvaluation groupScore / provenance
CritPt (AA)

Version snapshot-2026-09-10

Published board

Tests research-level physics reasoning with Python, symbolic and numerical answers.

0.04571 fractionmeasuredobserved 2026-09-10artificialanalysis.ai
Evidence
Axis: CritPt (AA) · snapshot-2026-09-10 · Published board
Exact value: 0.0457142857142857 fraction
Observed: 2026-09-10T21:47:16.627Z · publication date: not recorded
Observation id: aa:142b93bf-09c4-42dc-9c3a-50b1a222cbd4:critpt

Tool-use

Tool-use: every observation for this exact model configuration
Benchmark / versionEvaluation groupScore / provenance
AutomationBench-AA

Version 1.0.6

Published board

Tests multi-app SaaS workflows through REST tools on a held-out AutomationBench split.

0.19902 fractionmeasuredobserved 2026-09-10artificialanalysis.ai
Evidence
Axis: AutomationBench-AA · 1.0.6 · Published board
Exact value: 0.19901936568973871 fraction
Observed: 2026-09-10T21:47:16.627Z · publication date: not recorded
Observation id: aa:142b93bf-09c4-42dc-9c3a-50b1a222cbd4:automationBenchPartialScore
Missing coverage · 66 benchmark versions

No result does not mean a zero, or that the model was never tested. Collection failures and disputed versions retain their distinct status.

Variants / reasoning settings

VariantCoding · snapshot 2026-09-10Intelligence · snapshot 2026-09-10
Claude Sonnet 5 (Adaptive Reasoning, Max Effort)71.538.4
Claude Sonnet 5 (Non-reasoning, High Effort)66.428.9
Claude Sonnet 5 (Adaptive Reasoning, Medium Effort)28.4
Claude Sonnet 5 (Adaptive Reasoning, High Effort)
Claude Sonnet 5 (Adaptive Reasoning, Xhigh Effort)
Claude Sonnet 5 (Adaptive Reasoning, Low Effort)24.7

GitHub Copilot

Current usage-based billing · model token cost is converted to AI Credits at 1 credit = $0.01.

Input $2.00 / 1M
Cached input $0.200 / 1M
Cache write $2.50 / 1M
Output $10.00 / 1M
Status GA

Token offers by platform — Adjusted $/task

Adjusted costs are modeled USD per task: AA output tokens × OpenRouter usage I/O (Chutes global fallback). These are general usage and benchmark proxies for coding-agent work. Missing AA data assumes 1,000 output tokens/task; unknown cache hit assumes 0%; unmeasured additional cache writes assume 0 tokens. Click any underlined price for exact inputs, dates and assumptions. Raw list prices use the selected fixed input/output blend, in USD per million tokens.

14 offers within the active global filters; “—” means the catalog is active but no public token price is available.

Google Vertex AI (2)

Google Vertex AIglobal$2.00 raw in $/1M$10.00 raw out $/1M
Google Vertex AIeuEU$2.20 raw in $/1M$11.00 raw out $/1M

Anthropic (1)

Anthropicglobal$2.00 raw in $/1M$10.00 raw out $/1M

OpenRouter (9)

Claude Platform on AWSglobalclaude-on-aws$2.00 raw in $/1M$10.00 raw out $/1M
Azureglobalazure/us$2.00 raw in $/1M$10.00 raw out $/1M
Azureglobalazure/global$2.00 raw in $/1M$10.00 raw out $/1M
Googleglobalgoogle-vertex/global$2.00 raw in $/1M$10.00 raw out $/1M
Amazon Bedrockglobalamazon-bedrock/global$2.00 raw in $/1M$10.00 raw out $/1M
Anthropicglobalanthropic$2.00 raw in $/1M$10.00 raw out $/1M
Googleglobalgoogle-vertex/us$2.20 raw in $/1M$11.00 raw out $/1M
Googleeugoogle-vertex/europeEU$2.20 raw in $/1M$11.00 raw out $/1M
Amazon Bedrockglobalamazon-bedrock/us-east-1$2.20 raw in $/1M$11.00 raw out $/1M

AWS Bedrock (1)

AWS Bedrockeu-central-1 (EU cross-region inference profile)EU$2.20 raw in $/1M$11.00 raw out $/1M

T-Systems LLM Hub (1)

T-Systems LLM HubeuEU$3.45 raw in $/1M$17.26 raw out $/1M
Benchmark Heaven — Model benchmarks & costs