Claude Sonnet 5 (Max)
Context 1M tokens
Top 5 cheapest providers (Adjusted $/task)
The same list price can give a different adjusted $/task (caching, token efficiency) — click a price for its inputs.
Within the active global provider, residency and confidentiality filters.
| # | Provider | Price channel | Raw input $/1M | Raw output $/1M | Adjusted $/task |
|---|---|---|---|---|---|
| 1 | Azurevia OpenRouter — Price via OpenRouter: OpenRouter's price for Azure's endpoint (https://openrouter.ai/anthropic/claude-sonnet-5/providers), collected 2026-11-03. | via OpenRouter — Price via OpenRouter: OpenRouter's price for Azure's endpoint (https://openrouter.ai/anthropic/claude-sonnet-5/providers), collected 2026-11-03. | $2.00 | $10.00 | |
| 2 | Googlevia OpenRouter — Price via OpenRouter: OpenRouter's price for Google's endpoint (https://openrouter.ai/anthropic/claude-sonnet-5/providers), collected 2026-11-03. | via OpenRouter — Price via OpenRouter: OpenRouter's price for Google's endpoint (https://openrouter.ai/anthropic/claude-sonnet-5/providers), collected 2026-11-03. | $2.00 | $10.00 | |
| 3 | Amazon Bedrockvia OpenRouter — Price via OpenRouter: OpenRouter's price for Amazon Bedrock's endpoint (https://openrouter.ai/anthropic/claude-sonnet-5/providers), collected 2026-11-03. | via OpenRouter — Price via OpenRouter: OpenRouter's price for Amazon Bedrock's endpoint (https://openrouter.ai/anthropic/claude-sonnet-5/providers), collected 2026-11-03. | $2.00 | $10.00 | |
| 4 | Google Vertex AIdirect — Direct price: Google Vertex AI's own price list (https://cloud.google.com/vertex-ai/generative-ai/pricing), collected 2026-11-03. | direct — Direct price: Google Vertex AI's own price list (https://cloud.google.com/vertex-ai/generative-ai/pricing), collected 2026-11-03. | $2.00 | $10.00 | |
| 5 | AWS Bedrockdirect — Direct price: AWS Bedrock's own price list (https://aws.amazon.com/bedrock/pricing/), collected 2026-11-03. | direct — Direct price: AWS Bedrock's own price list (https://aws.amazon.com/bedrock/pricing/), collected 2026-11-03. | $2.20 | $11.00 |
Composite
6 of 7 inputs · 4 from the model family6 radar axes: DesignArena's two boards share one63.2
AA Coding v4.x 71.5Coding Agent v1.4 —AA Intelligence (est.) 28.0AA Agentic —Epoch ECI 157.0Software ECI 155.2DesignArena 1228/1249
Radar: percentile among all models measured on each input; a gap means not measured.
Benchmark sheet
52 of 319 registered benchmark versions · bars show the percentile among all models measured on each benchmark.
7 of 53 values are Anthropic's own claims (†), not independent measurements; a matching independent result replaces a claim as soon as one exists.
- Epoch ECI · attached
- Software ECI · attached
- DesignArena Web Apps (agentic) · attached
- DesignArena Full-Stack · attached
Agentic
AA-AnalystAgent7746.3%
AA-AnalystAgent published 2026-09-10 → · Published board — Tests analyst tasks using agentic Python execution across fourteen domains.
AA-Briefcase791,355 Elo
AA-Briefcase published 2026-09-10 → · Published board — Tests multi-week professional knowledge-work projects with linked tasks and large source collections.
GDPval-AA v2871,501 Elo
GDPval-AA v2 v2 → · Published board — Tests professional knowledge-work deliverables across occupations using AA's Stirrup harness.
Harvey LAB-AA6490.1%
Harvey LAB-AA published 2026-09-10 → · Published board — Tests legal-work deliverables across practice areas on Harvey's private task set. Artificial Analysis' run, graded by one LLM judge against task rubrics — not the same run or scale as Vals AI's HLAB row.
Terminal-Bench v2.1 (AA)8280.5%
Terminal-Bench v2.1 (AA) v2.1 → · Published board — Tests terminal-based work on the 89-task verified refresh using Terminus 2.
Terminal-Bench v4.0 (AA)7614.1%
Terminal-Bench v4.0 (AA) v4.0 → · Published board — Tests terminal-based work on the 66-task release using mini-SWE-agent v2.4.6.
ApprenticeBench API (NeoCognition)5426.0%
ApprenticeBench API (NeoCognition) published 2026-09-14 → · Claude Code — An agent completes the same 100 sequential accounts-payable tasks in the Odoo ERP with diminishing mentoring, using dedicated application API calls instead of the screen interface.
ApprenticeBench CUA (NeoCognition)2316.0%
ApprenticeBench CUA (NeoCognition) published 2026-09-14 → · Claude Code — A computer-use agent operates the Odoo ERP through its screens across 100 sequential accounts-payable tasks with diminishing mentoring.
τ^τ-bench (Hyper-τ), release v1 (Sierra)no percentile14.9%
τ^τ-bench (Hyper-τ), release v1 (Sierra) release-v1 → · Claude Code — A coding agent builds a working customer-service agent from realistic evidence (policies, transcripts, recordings, a client API), and is scored by how well that agent then serves simulated customers on 53 held-out tasks.
Terminal-Bench v4.0developer's claim12.4%† self-reported by the developer
Terminal-Bench v4.0 → · Claude Code — A benchmark to measure and evolve with the frontier of agent work, whose homepage leaderboard reports resolution rate on Terminal-Bench 4.0 tasks.
Finance Agent v2 (Vals Index v2)4953.9%
Finance Agent v2 (Vals Index v2) v2 → · Published board — Multi-step financial reasoning tasks.
HLAB — Harvey's Legal Agent Benchmark (Vals Index v2)425.0%
HLAB — Harvey's Legal Agent Benchmark (Vals Index v2) v2 → · Published board — Long-horizon legal work product creation. The index column is Harvey's Legal Agent Benchmark's own published standalone score, reported as accuracy — not comparable with Artificial Analysis' Harvey LAB-AA row.
Terminal-Bench 2.1 (Vals Index v2)5974.5%
Terminal-Bench 2.1 (Vals Index v2) v2 → · Published board — Command-line interface problem solving; the page states that each index column is that benchmark's own published standalone score, so the runner is not asserted here.
Vals Index v2 (Vals AI)6559.6%
Vals Index v2 (Vals AI) v2 → · Published board — GDP-weighted average of agentic model performance across finance, coding and legal tasks.
Coding
SciCode (AA subproblems) v1.0.17454.3%
SciCode (AA subproblems) v1.0.1 → · Published board — Tests scientific Python programming with scientist-annotated background information.
CursorBench 4.0 (Cursor)developer's claim34.1%† self-reported by the developer
CursorBench 4.0 (Cursor) v4.0 → · Published board — Agent evaluation on ambiguous, multi-file tasks drawn from real Cursor sessions.
DeepSWE (Datacurve, via Epoch AI)3953.8%
DeepSWE (Datacurve, via Epoch AI) published 2026-09-15 → · mini-SWE-agent — Pass rate of coding agents on original, long-horizon software engineering tasks, run by Datacurve with the mini-swe-agent harness.
FrontierCode 1.1 Main (Cognition)developer's claim42.4%† self-reported by the developer
FrontierCode 1.1 Main (Cognition) v1.1 → · Claude Code — Whether a maintainer would merge the agent's pull request, on tasks crafted by open-source maintainers and graded with tests, rubrics and verifiers.
Code Migration (Vals Index v2 subset)6344.1%
Code Migration (Vals Index v2 subset) v2 → · Published board — Porting projects to another language, including COBOL modernization.
Vibe Code Bench (Vals Index v2)6881.3%
Vibe Code Bench (Vals Index v2) v2 → · Published board — End-to-end app-building tasks.
MLS-Bench-Lite 30-tasks031.4
MLS-Bench-Lite 30-tasks → · Claude Code (max effort) — AI agents get a fixed ML research scaffold with strong baselines and must invent one algorithmic change — a loss, optimizer, sampler or training procedure — whose gain holds across settings, seeds, datasets and scales; Lite is the 30-task subset over all 12 research domains.
FrontierCode 1.1 Extended (Cognition)developer's claim54.9%† self-reported by the developer
FrontierCode 1.1 Extended (Cognition) v1.1 → · Claude Code — Whether a maintainer would merge the agent's pull request, on the full 150-task FrontierCode set crafted by open-source maintainers and graded with tests, rubrics and verifiers.
AA Coding Index v4.x · frozen 2026-10-278371.5
AA Coding Index v4.x · frozen 2026-10-27 → · Published board — Artificial Analysis withdrew the Coding Index with Intelligence Index v5.0 (2026-10-28). These are the last v4.x values, frozen with their own date (2026-10-27).
Efficiency
ApprenticeBench API cost per task (NeoCognition)38$1.91
ApprenticeBench API cost per task (NeoCognition) published 2026-09-14 → · Claude Code — ApprenticeBench's published USD cost per task for each API-board model-harness-effort configuration on the 100-task accounts-payable job.
ApprenticeBench CUA cost per task (NeoCognition)85$14.62
ApprenticeBench CUA cost per task (NeoCognition) published 2026-09-14 → · Claude Code — ApprenticeBench's published USD cost per task for each CUA model-harness-effort configuration on the 100-task accounts-payable job.
CursorBench 4.0 cost per task (Cursor)developer's claim$7.17† self-reported by the developer
CursorBench 4.0 cost per task (Cursor) v4.0 → · Published board — Cursor's published USD cost per task for each CursorBench 4.0 model-effort configuration.
FrontierCode 1.1 Main cost per rollout (Cognition)developer's claim$17.12† self-reported by the developer
FrontierCode 1.1 Main cost per rollout (Cognition) v1.1 → · Claude Code — Cognition's published mean USD spend per rollout for each FrontierCode 1.1 Main model and reasoning effort.
Vals Index v2 cost per test (Vals AI)14$17.61
Vals Index v2 cost per test (Vals AI) v2 → · Published board — Vals AI's published USD cost per test for each model on the Vals Index v2.
FrontierCode 1.1 Extended cost per rollout (Cognition)developer's claim$14.09† self-reported by the developer
FrontierCode 1.1 Extended cost per rollout (Cognition) v1.1 → · Claude Code — Cognition's published mean USD spend per rollout for each FrontierCode 1.1 Extended model and reasoning effort.
Knowledge
Humanity's Last Exam (AA text-only)9141.3%
Humanity's Last Exam (AA text-only) published 2026-09-10 → · Published board — Tests expert-level knowledge on AA's text-only Humanity's Last Exam subset.
AA-Omniscience Index8916.4
AA-Omniscience Index published 2026-09-10 → · Published board — Tests factual reliability while rewarding correct answers and penalizing hallucinations.
SimpleQA Verified (run by Epoch AI)1833.7%
SimpleQA Verified (run by Epoch AI) published 2026-09-16 → · Published board — Short fact-seeking questions answered without tools, testing whether a model knows a fact rather than guessing; Google DeepMind's cleaned version of OpenAI's SimpleQA, run by Epoch AI.
Legal Research Bench (Vals Index v2)6741.8%
Legal Research Bench (Vals Index v2) v2 → · Published board — Case and statute research with citation-backed answers.
Long-context
GDP.pdf (AA)5913.2%
GDP.pdf (AA) published 2026-09-10 → · Published board — Tests professional reasoning over long PDFs with AA document preparation and grading.
AA-LCR v1.19382.0%
AA-LCR v1.1 v1.1 → · Published board — Tests reasoning across multiple long documents with corrected answer keys and grading.
MLCR-AA9355.0%
MLCR-AA published 2026-09-10 → · Published board — Tests medical-record synthesis and reasoning across long, fragmented case documents.
Context Arena — MRCR v2 (8-needle)5280.0%
Context Arena — MRCR v2 (8-needle) 8-needle → · Published board — The model must find and reproduce the right one of eight near-identical earlier replies hidden in a long conversation, averaged over context lengths from 8k to 128k tokens.
Math
FrontierMath Tier 4 v2 (Epoch AI)3529.3%
FrontierMath Tier 4 v2 (Epoch AI) v2 → · Published board — The hardest, research-level tier of Epoch AI's unpublished FrontierMath problems, run by Epoch AI on its private v2 set.
FrontierMath Tiers 1–3 v2 (Epoch AI)4665.6%
FrontierMath Tiers 1–3 v2 (Epoch AI) v2 → · Published board — Unpublished, expert-written mathematics problems from undergraduate to research level with automatically checkable answers, run by Epoch AI on its private v2 set.
Reasoning
Chess Puzzles (Epoch AI)2816.0%
Chess Puzzles (Epoch AI) published 2026-09-18 → · Published board — Best-move selection on 100 novel chess positions generated programmatically by Epoch AI, each with a single Stockfish-verified best move; probes spatial reasoning and planning.
Mystery Game Puzzles (Epoch AI)6935.0%
Mystery Game Puzzles (Epoch AI) published 2026-09-18 → · Published board — Best-move selection on 100 mid-game positions of a well-known game whose identity Epoch deliberately keeps undisclosed, generated programmatically like Chess Puzzles.
Safety/Alignment
BullshitBench V1 (clear pushback)9061.8%
BullshitBench V1 (clear pushback) published 2026-09-10 → · Published board — Whether a model rejects the broken premise of 55 deliberately nonsensical prompts (V1 question set) instead of answering them confidently.
BullshitBench V2 (clear pushback)9578.0%
BullshitBench V2 (clear pushback) published 2026-09-10 → · Published board — Whether a model rejects the broken premise of 100 deliberately nonsensical prompts (V2 question set) instead of answering them confidently.
Science
CritPt (AA)8916.9%
CritPt (AA) published 2026-09-10 → · Published board — Tests research-level physics reasoning with Python, symbolic and numerical answers.
GPQA Diamond (AA)9291.1%
GPQA Diamond (AA) published 2026-09-10 → · Published board — Tests graduate-level biology, physics and chemistry knowledge on the Diamond subset.
GPQA Diamond (Epoch AI run)2980.3%
GPQA Diamond (Epoch AI run) published 2026-09-18 → · Published board — Epoch AI's own inspect-ai runs of GPQA Diamond, the 198-question graduate-level science multiple-choice set.
Tool-use
AutomationBench-AA v1.0.65736.5%
AutomationBench-AA v1.0.6 → · Published board — Tests multi-app SaaS workflows through REST tools on a held-out AutomationBench split.
EnterpriseOps-Gym-AA7444.7%
EnterpriseOps-Gym-AA published 2026-09-10 → · Published board — Tests enterprise workflows through MCP tools against resettable application environments.
τ³-Banking (AA) v1.0.18137.3%
τ³-Banking (AA) v1.0.1 → · Published board — Tests banking support agents that retrieve policies and change account state through tools.
Toolathlon-Verified (HKUST NLP) 2026-06-306371.6%
Toolathlon-Verified (HKUST NLP) 2026-06-30 → · Published board — An agent completes 108 real-world tool-use tasks across 32 MCP servers and 7 local toolkits, and each task is graded by executing the resulting state against the task's ground truth.
Excel Modeling Benchmark (Vals Index v2)6266.3%
Excel Modeling Benchmark (Vals Index v2) v2 → · Published board — Building and editing financial models in spreadsheets.
Vision
MMMU Pro (AA)7577.3%
MMMU Pro (AA) published 2026-09-10 → · Published board — Tests multimodal understanding using challenging ten-option questions.
Chartography 100-tasks1816.6%
Chartography 100-tasks → · Published board — Can a model read the charts professionals rely on — Kaplan-Meier curves, candlesticks, contour maps, Sankey diagrams, Bode plots, wind roses — from the image alone, to an expert-set precision?
Unusual results
1 threshold-crossing signal flagged · 38 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.
- unusually strong MLCR-AA published 2026-09-10
Why
Observed: 0.55 fractionPeer mean 0.18737 · peer sd 0.17142 · n 84 · families 61Directed z 2.116 · baseline z 0.477 · gap 1.638 · profile n 370.55 fractionmeasuredobserved 2026-09-10artificialanalysis.ai ↗Evidence
Axis: MLCR-AA · published 2026-09-10 · Published boardExact value:0.55fractionObserved: 2026-09-10T21:47:16.627Z · publication date: not recordedObservation id:aa:23c86e4a-c769-43c0-a056-79e3cd15834f:mlcrOverall
Missing coverage · 267 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
Artificial Analysis snapshot 2026-11-03 · Intelligence Index v5.0 (est. = estimated from v4, not measured) · Coding Index v4.x frozen 2026-10-27 · Data: Artificial Analysis · Data: Epoch AI (CC BY)
| Variant | AA Coding | AA Intelligence |
|---|---|---|
| Claude Sonnet 5 (Max) | 71.5 | 28.0est. |
| Claude Sonnet 5 (Non-reasoning, High) | 66.4 | 11.9est. |
| Claude Sonnet 5 (High) | — | 20.1est. |
| Claude Sonnet 5 (Low) | — | 12.3est. |
| Claude Sonnet 5 (Medium) | — | 17.6est. |
| Claude Sonnet 5 (Xhigh) | — | 24.0est. |
SUBSCRIPTION PLAN
GitHub Copilot
Current usage-based billing · model token cost is converted to AI Credits at 1 credit = $0.01.
Token offers by platform · 11 offers (Adjusted $/task)
Click any underlined price to see how it is estimated and where each input comes from. How we calculate adjusted cost.
11 offers within the active global filters, 3 more outside them; “price n/a” means the provider serves the model but publishes no direct token price we could collect — no other channel's price is shown in its place.
OpenRouter (8)
Prices via OpenRouter — what OpenRouter charges for each provider's endpoint, not the provider's own direct price. Source: openrouter.ai/anthropic/claude-sonnet-5/providers, collected 2026-11-03.
| Azure | globalazure/global | $2.00 raw in $/1M | $10.00 raw out $/1M | |
| globalgoogle-vertex/global | $2.00 raw in $/1M | $10.00 raw out $/1M | ||
| Amazon Bedrock | globalamazon-bedrock/global | $2.00 raw in $/1M | $10.00 raw out $/1M | |
| Amazon Bedrock | euamazon-bedrock/eu-west-1EU | $2.20 raw in $/1M | $11.00 raw out $/1M | |
| Azure | globalazure/us | $2.20 raw in $/1M | $11.00 raw out $/1M | |
| globalgoogle-vertex/us | $2.20 raw in $/1M | $11.00 raw out $/1M | ||
| eugoogle-vertex/europeEU | $2.20 raw in $/1M | $11.00 raw out $/1M | ||
| Amazon Bedrock | globalamazon-bedrock/us-east-1 | $2.20 raw in $/1M | $11.00 raw out $/1M |
Google Vertex AI (2)
Direct prices from Google Vertex AI's own price list. Source: cloud.google.com/vertex-ai/generative-ai/pricing, collected 2026-11-03.
| Google Vertex AI | global | $2.00 raw in $/1M | $10.00 raw out $/1M | |
| Google Vertex AI | euEU | $2.20 raw in $/1M | $11.00 raw out $/1M |
AWS Bedrock (1)
Direct prices from AWS Bedrock's own price list. Source: aws.amazon.com/bedrock/pricing/, collected 2026-11-03.
| AWS Bedrock | eu-central-1 (EU cross-region inference profile)EU | $2.20 raw in $/1M | $11.00 raw out $/1M |