Claude Fable 5 (Max, Opus 4.8 Fallback)
Context 1M tokens
Top 4 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-fable-5/providers), collected 2026-11-03. | via OpenRouter — Price via OpenRouter: OpenRouter's price for Azure's endpoint (https://openrouter.ai/anthropic/claude-fable-5/providers), collected 2026-11-03. | $10.00 | $50.00 | |
| 2 | Amazon Bedrockvia OpenRouter — Price via OpenRouter: OpenRouter's price for Amazon Bedrock's endpoint (https://openrouter.ai/anthropic/claude-fable-5/providers), collected 2026-11-03. | via OpenRouter — Price via OpenRouter: OpenRouter's price for Amazon Bedrock's endpoint (https://openrouter.ai/anthropic/claude-fable-5/providers), collected 2026-11-03. | $10.00 | $50.00 | |
| 3 | Googlevia OpenRouter — Price via OpenRouter: OpenRouter's price for Google's endpoint (https://openrouter.ai/anthropic/claude-fable-5/providers), collected 2026-11-03. | via OpenRouter — Price via OpenRouter: OpenRouter's price for Google's endpoint (https://openrouter.ai/anthropic/claude-fable-5/providers), collected 2026-11-03. | $10.00 | $50.00 | |
| 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. | $10.00 | $50.00 |
Composite
7 of 7 inputs · 4 from the model family6 radar axes: DesignArena's two boards share one82.4
AA Coding v4.x 76.5Coding Agent v1.4 67.2AA Intelligence (est.) 46.0AA Agentic —Epoch ECI 163.0Software ECI 164.4DesignArena 1247/1280
Radar: percentile among all models measured on each input; a gap means not measured.
Benchmark sheet
57 of 319 registered benchmark versions · bars show the percentile among all models measured on each benchmark.
8 of 59 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-AnalystAgent8448.8%
AA-AnalystAgent published 2026-09-10 → · Published board — Tests analyst tasks using agentic Python execution across fourteen domains.
AA-Briefcase911,530 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 v2941,631 Elo
GDPval-AA v2 v2 → · Published board — Tests professional knowledge-work deliverables across occupations using AA's Stirrup harness.
Harvey LAB-AA9693.6%
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 Hard (AA)10062.9%
Terminal-Bench Hard (AA) pinned revision 74221fb → · Published board — Tests a pinned 44-task hard subset of terminal-based work using Terminus 2.
Terminal-Bench v2.1 (AA)8984.6%
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)9242.4%
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)8545.0%
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)6234.0%
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.
EBR-bench (Earthborne Rangers, Epoch AI)6039.5%
EBR-bench (Earthborne Rangers, Epoch AI) published 2026-09-18 → · Published board — Learning-capability test: models repeatedly play the obscure campaign board game Earthborne Rangers with note-taking, and the score measures whether results improve across playthroughs.
PostTrainBench v1.110041.8%
PostTrainBench v1.1 → · Claude Code — Agents retrain four small base models (gemma-3-4b-pt, SmolLM3-3B-Base, Qwen3-1.7B-Base, Qwen3-4B-Base) for each of 7 benchmark families; the leaderboard value is the weighted mean over base models × benchmarks, aggregated over the 2–3 listed runs per agent.
Terminal-Bench v4.0developer's claim44.5%† 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.
Terminal-Bench v4.0developer's claim42.0%† self-reported by the developer
Terminal-Bench v4.0 → · Claude Code in --bare mode — 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)7056.3%
Finance Agent v2 (Vals Index v2) v2 → · Published board — Multi-step financial reasoning tasks.
HLAB — Harvey's Legal Agent Benchmark (Vals Index v2)7911.3%
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)8180.5%
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)8966.0%
Vals Index v2 (Vals AI) v2 → · Published board — GDP-weighted average of agentic model performance across finance, coding and legal tasks.
Coding
Artificial Analysis Coding Agent Index v1.49267.2%
Artificial Analysis Coding Agent Index v1.4 v1.4 → · Claude Code — The retained AA Coding Agent Index measures coding-agent systems using the earlier three-component implementation.
SciCode (AA subproblems) v1.0.19861.0%
SciCode (AA subproblems) v1.0.1 → · Published board — Tests scientific Python programming with scientist-annotated background information.
DeepSWE (Datacurve, via Epoch AI)8169.7%
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 claim51.6%† 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.
SWE-bench Multilingualdeveloper's claim86.6%† self-reported by the developer
SWE-bench Multilingual published 2026-09-10 → · Published board — A 300-instance SWE-bench variant with tasks from 42 repositories across 9 programming languages.
SWE-bench Multimodaldeveloper's claim54.1%† self-reported by the developer
SWE-bench Multimodal published 2026-09-10 → · Published board — A 480-instance SWE-bench variant whose issue descriptions include visual elements.
Code Migration (Vals Index v2 subset)8854.6%
Code Migration (Vals Index v2 subset) v2 → · Published board — Porting projects to another language, including COBOL modernization.
Vibe Code Bench (Vals Index v2)10090.4%
Vibe Code Bench (Vals Index v2) v2 → · Published board — End-to-end app-building tasks.
FrontierCode 1.1 Extended (Cognition)developer's claim63.6%† 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 2026-10-279476.5
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)0$7.33
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)8$28.68
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.
FrontierCode 1.1 Main cost per rollout (Cognition)developer's claim$19.07† 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)3$28.73
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$15.49† 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.
Instruction-following
IFBench (AA single-turn)7563.5%
IFBench (AA single-turn) published 2026-09-10 → · Published board — Tests precise single-turn instructions with deterministic rule checks.
Knowledge
Humanity's Last Exam (AA text-only)9955.5%
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 Index9943.3
AA-Omniscience Index published 2026-09-10 → · Published board — Tests factual reliability while rewarding correct answers and penalizing hallucinations.
Legal Research Bench (Vals Index v2)9049.5%
Legal Research Bench (Vals Index v2) v2 → · Published board — Case and statute research with citation-backed answers.
Long-context
GDP.pdf (AA)8824.0%
GDP.pdf (AA) published 2026-09-10 → · Published board — Tests professional reasoning over long PDFs with AA document preparation and grading.
AA-LCR v1.19482.3%
AA-LCR v1.1 v1.1 → · Published board — Tests reasoning across multiple long documents with corrected answer keys and grading.
MLCR-AA9964.4%
MLCR-AA published 2026-09-10 → · Published board — Tests medical-record synthesis and reasoning across long, fragmented case documents.
Math
FrontierMath Tier 4 v2 (Epoch AI)8890.2%
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)8987.0%
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.
ArXivMath 06/2026 (MathArena)7585.4%
ArXivMath 06/2026 (MathArena) 2026-06 → · Published board — Research-level math problems with a checkable final answer, drawn from arXiv papers submitted in June 2026; each edition is restricted to papers published within the last month to reduce training-data contamination.
BrokenArXiv 06/2026 (MathArena)4047.8%
BrokenArXiv 06/2026 (MathArena) 2026-06 → · Published board — Plausible but false proof statements taken from June 2026 arXiv papers; a model scores by refusing to prove them and saying the statement is false as written.
FrontierMath Erdős (Epoch AI)380.0%
FrontierMath Erdős (Epoch AI) published 2026-09-26 → · Published board — 68 open problems posed or studied by Paul Erdős, formalised in Lean 4, where a model agent must produce a complete Lean proof or disproof that passes the Comparator checker.
Reasoning
Chess Puzzles (Epoch AI)8041.0%
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.
LiveBench 2026-06-259483.0
LiveBench 2026-06-25 → · Published board — A periodically refreshed suite of objectively graded tasks with separate category scores and an overall category mean.
Mystery Game Puzzles (Epoch AI)8552.0%
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.
Science
CritPt (AA)9728.6%
CritPt (AA) published 2026-09-10 → · Published board — Tests research-level physics reasoning with Python, symbolic and numerical answers.
GPQA Diamond (AA)9592.6%
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)4085.9%
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 v1.0.67654.1%
AutomationBench-AA v1.0.6 → · Published board — Tests multi-app SaaS workflows through REST tools on a held-out AutomationBench split.
EnterpriseOps-Gym-AA10051.1%
EnterpriseOps-Gym-AA published 2026-09-10 → · Published board — Tests enterprise workflows through MCP tools against resettable application environments.
τ²-Bench Telecom (AA)9998.5%
τ²-Bench Telecom (AA) published 2026-09-10 → · Published board — Tests dual-control telecom agents that coordinate tool use with a simulated user.
τ³-Banking (AA) v1.0.18238.1%
τ³-Banking (AA) v1.0.1 → · Published board — Tests banking support agents that retrieve policies and change account state through tools.
Excel Modeling Benchmark (Vals Index v2)9573.7%
Excel Modeling Benchmark (Vals Index v2) v2 → · Published board — Building and editing financial models in spreadsheets.
MCPMark Verified5086.6%
MCPMark Verified verified → · Published board — AI agents complete realistic multi-step tasks through Model Context Protocol servers for Notion, GitHub, a filesystem, Postgres and a Playwright browser, each checked by the task's own verification script; Verified is the maintainers' version-pinned, stabilized 127-task set.
Vision
Chartography 100-tasks6734.8%
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?
GDP.pdf 100-tasks8629.8%
GDP.pdf 100-tasks → · Published board — Can a model answer real professional questions about the PDFs work runs on — manuals, wiring diagrams, filings, forms — so that every rubric criterion an expert wrote is met?
Furniture Assembly Benchmark (Epoch AI)4535.8%
Furniture Assembly Benchmark (Epoch AI) published 2026-09-26 → · Published board — Spatial-reasoning test by Epoch AI: given a photo of a partly or fully assembled IKEA product and its official manual, the model must say whether the build is correct and, if not, name the step with the mistake.
Unusual results
5 threshold-crossing signals flagged · 40 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 weak Vals Index v2 cost per test (Vals AI)
Why
Observed: 28.72507 USDPeer mean 6.89364 · peer sd 7.83661 · n 38 · families 37Directed z -2.786 · baseline z 1.238 · gap -4.023 · profile n 3928.72507 USDmeasured· 28.73 USD per rolloutobserved 2026-09-26vals.ai ↗Evidence
Axis: Vals Index v2 cost per test (Vals AI) · v2 · Published boardExact value:28.725071USDPublished mean cost: 28.725071 USD per rolloutObserved: 2026-09-26T04:22:13.903077+00:00 · publication date: not recordedObservation id:public:8ff5dba3134e2db88a520a2b - unusually strong CritPt (AA) published 2026-09-10
Why
Observed: 0.28571 fractionPeer mean 0.04412 · peer sd 0.08179 · n 537 · families 370Directed z 2.954 · baseline z 1.09 · gap 1.864 · profile n 390.28571 fractionmeasuredobserved 2026-09-10artificialanalysis.ai ↗Evidence
Axis: CritPt (AA) · published 2026-09-10 · Published boardExact value:0.2857142857fractionObserved: 2026-09-10T21:47:16.627Z · publication date: not recordedObservation id:aa:cd55210d-358e-4df1-ba9c-9acb5f186cc9:critpt - unusually strong Humanity's Last Exam (AA text-only) published 2026-09-10
Why
Observed: 0.55468 fractionPeer mean 0.15894 · peer sd 0.14559 · n 623 · families 450Directed z 2.718 · baseline z 1.096 · gap 1.622 · profile n 390.55468 fractionmeasuredobserved 2026-09-10artificialanalysis.ai ↗Evidence
Axis: Humanity's Last Exam (AA text-only) · published 2026-09-10 · Published boardExact value:0.554680259499537fractionObserved: 2026-09-10T21:47:16.627Z · publication date: not recordedObservation id:aa:cd55210d-358e-4df1-ba9c-9acb5f186cc9:hle - unusually strong MLCR-AA published 2026-09-10
Why
Observed: 0.64444 fractionPeer mean 0.18737 · peer sd 0.17142 · n 84 · families 61Directed z 2.666 · baseline z 1.098 · gap 1.569 · profile n 390.64444 fractionmeasuredobserved 2026-09-10artificialanalysis.ai ↗Evidence
Axis: MLCR-AA · published 2026-09-10 · Published boardExact value:0.644444444444444fractionObserved: 2026-09-10T21:47:16.627Z · publication date: not recordedObservation id:aa:cd55210d-358e-4df1-ba9c-9acb5f186cc9:mlcrOverall - unusually strong Terminal-Bench Hard (AA)
Why
Observed: 0.62879 fractionPeer mean 0.18472 · peer sd 0.16951 · n 432 · families 315Directed z 2.62 · baseline z 1.099 · gap 1.521 · profile n 390.62879 fractionmeasuredobserved 2026-09-10artificialanalysis.ai ↗Evidence
Axis: Terminal-Bench Hard (AA) · pinned revision 74221fb · Published boardExact value:0.628787878787879fractionObserved: 2026-09-10T21:47:16.627Z · publication date: not recordedObservation id:aa:cd55210d-358e-4df1-ba9c-9acb5f186cc9:terminalbenchHard
Missing coverage · 262 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 Fable 5 (Max, Opus 4.8 Fallback) | 76.5 | 46.0est. |
| Fable 5 (low) (with fallback) | — | — |
| Fable 5 (xhigh) (with fallback) | — | — |
| Fable 5 (medium) (with fallback) | — | — |
| Fable 5 (high) (with fallback) | — | — |
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 · 6 offers (Adjusted $/task)
Click any underlined price to see how it is estimated and where each input comes from. How we calculate adjusted cost.
6 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 (4)
Prices via OpenRouter — what OpenRouter charges for each provider's endpoint, not the provider's own direct price. Source: openrouter.ai/anthropic/claude-fable-5/providers, collected 2026-11-03.
| Azure | globalazure | $10.00 raw in $/1M | $50.00 raw out $/1M | |
| Amazon Bedrock | globalamazon-bedrock | $10.00 raw in $/1M | $50.00 raw out $/1M | |
| globalgoogle-vertex/global | $10.00 raw in $/1M | $50.00 raw out $/1M | ||
| eugoogle-vertex/europeEU | $11.00 raw in $/1M | $55.00 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 | $10.00 raw in $/1M | $50.00 raw out $/1M | |
| Google Vertex AI | euEU | $11.00 raw in $/1M | $55.00 raw out $/1M |