GPT-6 Astra (Max)
Output 59 tokens/sFirst token 213 sContext 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/openai/gpt-6-astra/providers), collected 2026-11-03. | via OpenRouter — Price via OpenRouter: OpenRouter's price for Azure's endpoint (https://openrouter.ai/openai/gpt-6-astra/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/openai/gpt-6-astra/providers), collected 2026-11-03. | via OpenRouter — Price via OpenRouter: OpenRouter's price for Amazon Bedrock's endpoint (https://openrouter.ai/openai/gpt-6-astra/providers), collected 2026-11-03. | $11.00 | $55.00 | |
| 3 | Azure AI Foundrydirect — Direct price: Azure AI Foundry's own price list (https://prices.azure.com/api/retail/prices), collected 2026-11-03. | direct — Direct price: Azure AI Foundry's own price list (https://prices.azure.com/api/retail/prices), collected 2026-11-03. | $10.00 | $50.00 | |
| 4 | T-Systems LLM Hubdirect — Direct price: T-Systems LLM Hub's own price list (https://docs.llmhub.t-systems.net/models/llms/), collected 2026-11-03. | direct — Direct price: T-Systems LLM Hub's own price list (https://docs.llmhub.t-systems.net/models/llms/), collected 2026-11-03. | $10.86 | $54.29 |
Composite
7 of 7 inputs · 4 from the model family6 radar axes: DesignArena's two boards share one93.9
AA Coding v4.x 76.9Coding Agent v1.4 67.0AA Intelligence 56.9AA Agentic —Epoch ECI 169.1Software ECI 167.9DesignArena 1356/1357
Radar: percentile among all models measured on each input; a gap means not measured.
Benchmark sheet
107 of 319 registered benchmark versions · bars show the percentile among all models measured on each benchmark.
13 of 111 values are OpenAI'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-AnalystAgent9051.2%
AA-AnalystAgent published 2026-09-10 → · Published board — Tests analyst tasks using agentic Python execution across fourteen domains.
AA-Briefcase v1.1no percentile1,569 Elo
AA-Briefcase v1.1 v1.1 → · Published board — Tests multi-week professional knowledge-work projects with linked tasks and large source collections.
AA-Briefcase951,562 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 v2911,580 Elo
GDPval-AA v2 v2 → · Published board — Tests professional knowledge-work deliverables across occupations using AA's Stirrup harness.
GDPval-AA v2.1no percentile1,542 Elo
GDPval-AA v2.1 v2.1 → · Published board — Tests professional knowledge-work deliverables across occupations using AA's Stirrup harness.
Terminal-Bench v2.1 (AA)9688.4%
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)9959.1%
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.
Terminal-Bench v4.0 (AA, upstream timeouts)8659.1%
Terminal-Bench v4.0 (AA, upstream timeouts) 4.0-upstream-timeouts → · Published board — Tests terminal-based work on the 66-task release using AA's mini-swe-agent harness with the tasks' own timeouts.
ApprenticeBench API (NeoCognition)10065.0%
ApprenticeBench API (NeoCognition) published 2026-09-14 → · Codex — 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)10068.0%
ApprenticeBench CUA (NeoCognition) published 2026-09-14 → · Codex — 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)10076.2%
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.
RSI-Exam 0.1 (aiming-lab)1000.51
RSI-Exam 0.1 (aiming-lab) v0.1 → · Codex — An agent spends a long, budgeted run improving an inherited, working-but-weak executable research method or harness on a visible split, and the single artifact it submits is re-run once on a sealed hidden split across 88 executable research tasks in six domains.
Terminal-Bench v4.0developer's claim58.2%† self-reported by the developer
Terminal-Bench v4.0 → · Codex — 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)4153.5%
Finance Agent v2 (Vals Index v2) v2 → · Published board — Multi-step financial reasoning tasks.
HLAB — Harvey's Legal Agent Benchmark (Vals Index v2)465.4%
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)9787.3%
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)9266.6%
Vals Index v2 (Vals AI) v2 → · Published board — GDP-weighted average of agentic model performance across finance, coding and legal tasks.
AutomationBench 1.0.6developer's claim41.4%† self-reported by the developer
AutomationBench 1.0.6 v1.0.6 → · Vendor-reported by OpenAI — AutomationBench 1.0.6 score OpenAI reports for its own GPT-6 models in the 2026-09-22 GPT-6 Sol and Luna launch post.
Agents' Last Exam V1developer's claim59.3%† self-reported by the developer
Agents' Last Exam V1 v1 → · Vendor-reported by OpenAI — Agents' Last Exam V1 score OpenAI reports for its own GPT-6 models in the 2026-09-22 GPT-6 Sol and Luna launch post.
OSWorld 2.0 offline (v2026.08.08 release)developer's claim73.5%† self-reported by the developer
OSWorld 2.0 offline (v2026.08.08 release) v2026.08.08 → · Vendor-reported by OpenAI — OSWorld 2.0 offline partial reward OpenAI reports for its own GPT-6 models in the 2026-09-22 GPT-6 Sol and Luna launch post.
CUA-bench10019.2%
CUA-bench published 2026-09-18 → · Published board — CUA-bench results published by Vals AI.
SRE Benchno percentile56.9%
SRE Bench published 2026-09-22 → · Published board — SRE Bench results published by Vals AI.
Terminal-Bench 4.0no percentile57.1%
Terminal-Bench 4.0 published 2026-09-21 → · Published board — Terminal-Bench 4.0 results published by Vals AI.
Terminal-Bench Scienceno percentile65.7%
Terminal-Bench Science published 2026-09-21 → · Published board — Terminal-Bench Science results published by Vals AI.
Time Horizon Index: KSP10090.5%
Time Horizon Index: KSP published 2026-09-14 → · Published board — Time Horizon Index: KSP results published by Vals AI.
Terminal-Bench 4.08857.1%
Terminal-Bench 4.0 published 2026-09-22 → · Published board — Terminal-Bench 4.0 results published by Vals AI.
Terminal-Bench Science10065.7%
Terminal-Bench Science published 2026-09-23 → · Published board — Terminal-Bench Science results published by Vals AI.
Tax Agent Bench3363.3%
Tax Agent Bench published 2026-09-23 → · Published board — Tax Agent Bench results published by Vals AI.
LMArena Agent Arena (overall net improvement)9510.8%
LMArena Agent Arena (overall net improvement) published 2026-09-26 → · Published board — Ranking of models as the orchestrator in LMArena’s Agent Mode, scored by the causal net improvement over the average model across behavioural signals from real sessions.
Coding
Artificial Analysis Coding Agent Index v1.410067.0%
Artificial Analysis Coding Agent Index v1.4 v1.4 → · Codex — The retained AA Coding Agent Index measures coding-agent systems using the earlier three-component implementation.
Artificial Analysis Coding Agent Index v1.510061.6%
Artificial Analysis Coding Agent Index v1.5 v1.5 → · Codex — Measures coding-agent systems on DeepSWE v1.1, Terminal-Bench 4.0 and SWE-Atlas-QnA.
Artificial Analysis Coding Agent Index v2.010054.7%
Artificial Analysis Coding Agent Index v2.0 v2.0 → · Codex — Measures coding-agent systems on FrontierCode v1.1 Main, Terminal-Bench 4.0 and SWE-Atlas-QnA-AA.
SciCode (AA subproblems) v1.0.18656.5%
SciCode (AA subproblems) v1.0.1 → · Published board — Tests scientific Python programming with scientist-annotated background information.
DeepSWE (Datacurve, via Epoch AI)9473.2%
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 claim53.3%† self-reported by the developer
FrontierCode 1.1 Main (Cognition) v1.1 → · Codex — 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)9868.5%
Code Migration (Vals Index v2 subset) v2 → · Published board — Porting projects to another language, including COBOL modernization.
Vibe Code Bench (Vals Index v2)9289.6%
Vibe Code Bench (Vals Index v2) v2 → · Published board — End-to-end app-building tasks.
VulcanBench Frontier v410089.3%
VulcanBench Frontier v4 v4 → · Codex — 23 behavioural-reconstruction tasks: the model must repair a replacement implementation of a legacy program until hidden tests confirm it reproduces the program’s real drift from its written spec; the combined score weights functional correctness 50%, lint/complexity 8.5%, security 8.5% and judged Code quality 33%.
DeepSWE v1.1developer's claim73.2%† self-reported by the developer
DeepSWE v1.1 v1.1 → · Vendor-reported by OpenAI — DeepSWE v1.1 score OpenAI reports for its own GPT-6 models in the 2026-09-22 GPT-6 Sol and Luna launch post.
ProgramBenchno percentile5.5%
ProgramBench published 2026-09-21 → · Published board — ProgramBench results published by Vals AI.
Vibe Code Bench 1-1006727.6%
Vibe Code Bench 1-100 published 2026-09-22 → · Published board — Vibe Code Bench 1-100 results published by Vals AI.
Vibe Code Bench v1.18289.6%
Vibe Code Bench v1.1 v1.1 → · Published board — Vibe Code Bench v1.1 results published by Vals AI.
Code Migration (standalone Vals board, 2026-09-21 snapshot)no percentile67.7%
Code Migration (standalone Vals board, 2026-09-21 snapshot) published 2026-09-21 → · Published board — Standalone Code Migration results published by Vals AI, distinct from its Vals Index v2 subset.
FrontierCode 1.1 Extended (Cognition)developer's claim64.5%† self-reported by the developer
FrontierCode 1.1 Extended (Cognition) v1.1 → · Codex — 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.
ProgramBench825.5%
ProgramBench published 2026-09-23 → · Published board — ProgramBench results published by Vals AI.
Code Migration (standalone Vals board, 2026-09-22 snapshot)10067.7%
Code Migration (standalone Vals board, 2026-09-22 snapshot) published 2026-09-22 → · Published board — Standalone Code Migration results published by Vals AI, distinct from its Vals Index v2 subset.
CyberBench v1.1041.1%
CyberBench v1.1 v1.1 → · Published board — CyberBench v1.1 results published by Vals AI.
LMArena WebDev (Code Arena, overall)1001,792 Elo
LMArena WebDev (Code Arena, overall) published 2026-09-26 → · Codex harness — Community pairwise-vote ranking of models on front-end web development tasks, including agentic multi-step coding, published by LMArena as a Bradley-Terry rating.
AA Coding Index v4.x · frozen 2026-10-279676.9
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).
DesignArena Web Apps (agentic)1001,356 Elo
DesignArena Web Apps (agentic) published 2026-11-03 → · Published board — Published Elo. Exact source attachment is retained; fewer than 200 battles excludes a row from radar normalization and anomaly peers.
Efficiency
ApprenticeBench API cost per task (NeoCognition)0$9.62
ApprenticeBench API cost per task (NeoCognition) published 2026-09-14 → · Codex — 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)0$20.51
ApprenticeBench CUA cost per task (NeoCognition) published 2026-09-14 → · Codex — 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$4.59† self-reported by the developer
FrontierCode 1.1 Main cost per rollout (Cognition) v1.1 → · Codex — 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)8$19.09
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.
AutomationBench 1.0.6 cost per taskdeveloper's claim$1.73† self-reported by the developer
AutomationBench 1.0.6 cost per task v1.0.6 → · Published board — USD cost per AutomationBench 1.0.6 task OpenAI reports for its own GPT-6 models in the 2026-09-22 GPT-6 Sol and Luna launch post.
Cost to run AA Intelligence Index (total) v4.3.25$5,324
Cost to run AA Intelligence Index (total) v4.3.2 → · Published board — Cost to run AA Intelligence Index (total) results published by Artificial Analysis.
Cost per AA Intelligence Index task v4.3.2103.26
Cost per AA Intelligence Index task v4.3.2 → · Published board — Cost per AA Intelligence Index task results published by Artificial Analysis.
FrontierCode 1.1 Extended cost per rollout (Cognition)developer's claim$3.93† self-reported by the developer
FrontierCode 1.1 Extended cost per rollout (Cognition) v1.1 → · Codex — Cognition's published mean USD spend per rollout for each FrontierCode 1.1 Extended model and reasoning effort.
Agents' Last Exam V1 cost per taskdeveloper's claim$6.23† self-reported by the developer
Agents' Last Exam V1 cost per task v1 → · Published board — USD cost per Agents' Last Exam V1 task OpenAI reports for its own GPT-6 models in the 2026-09-22 GPT-6 Sol and Luna launch post.
DeepSWE v1.1 cost per taskdeveloper's claim$7.50† self-reported by the developer
DeepSWE v1.1 cost per task v1.1 → · Published board — USD cost per DeepSWE v1.1 task OpenAI reports for its own GPT-6 models in the 2026-09-22 GPT-6 Sol and Luna launch post.
OSWorld 2.0 offline (v2026.08.08 release) cost per taskdeveloper's claim$9.07† self-reported by the developer
OSWorld 2.0 offline (v2026.08.08 release) cost per task v2026.08.08 → · Published board — USD cost per OSWorld 2.0 offline (v2026.08.08 release) task OpenAI reports for its own GPT-6 models in the 2026-09-22 GPT-6 Sol and Luna launch post.
Knowledge
Humanity's Last Exam (AA text-only)9954.7%
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 Index9943.4
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)10075.6%
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)5439.4%
Legal Research Bench (Vals Index v2) v2 → · Published board — Case and statute research with citation-backed answers.
MedScribeno percentile87.9%
MedScribe published 2026-09-21 → · Published board — MedScribe results published by Vals AI.
MedScribe6087.9%
MedScribe published 2026-09-22 → · Published board — MedScribe results published by Vals AI.
MedCode7048.5%
MedCode published 2026-09-22 → · Published board — MedCode results published by Vals AI.
Long-context
GDP.pdf (AA)9931.0%
GDP.pdf (AA) published 2026-09-10 → · Published board — Tests professional reasoning over long PDFs with AA document preparation and grading.
GDP.pdf (AA)no percentile31.0%
GDP.pdf (AA) published 2026-09-21 → · Published board — Tests professional reasoning over long PDFs with AA document preparation and grading.
AA-LCR v1.19080.7%
AA-LCR v1.1 v1.1 → · Published board — Tests reasoning across multiple long documents with corrected answer keys and grading.
MLCR-AA8435.0%
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)9797.6%
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)10093.7%
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)10094.4%
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.
ArXivMath 08/2026 (MathArena)8888.6%
ArXivMath 08/2026 (MathArena) 2026-08 → · Published board — Research-level math problems with a checkable final answer, drawn from arXiv papers submitted in August 2026; each edition is restricted to papers published within the last month to reduce training-data contamination.
BrokenArXiv 06/2026 (MathArena)9399.1%
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.
BrokenArXiv 08/2026 (MathArena)10081.9%
BrokenArXiv 08/2026 (MathArena) 2026-08 → · Published board — Plausible but false statements taken from August 2026 arXiv papers; a model scores by refusing to prove them and saying the statement is false as written.
IOIno percentile100.0%
IOI published 2026-09-21 → · Published board — IOI results published by Vals AI.
ProofBench v1.18099.0%
ProofBench v1.1 v1.1 → · Published board — ProofBench v1.1 results published by Vals AI.
IOI100100.0%
IOI published 2026-09-23 → · Published board — IOI results published by Vals AI.
SAGE5746.4%
SAGE published 2026-09-22 → · Published board — SAGE results published by Vals AI.
FrontierMath Erdős (Epoch AI)1002.9%
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.
Other
LMArena Text (overall)no percentile1,480 Elo
LMArena Text (overall) published 2026-09-22 → · Published board — LMArena Text (overall) results published by LMArena.
LMArena Visionno percentile1,284 Elo
LMArena Vision published 2026-09-22 → · Published board — LMArena Vision results published by LMArena.
BALROG (average progress)no percentile68.3%
BALROG (average progress) published 2026-09-22 → · Published board — BALROG (average progress) results published by BALROG.
Reasoning
ARC-AGI-17497.5%
ARC-AGI-1 v1 → · Published board — The first-generation ARC-AGI benchmark measuring passive fluid intelligence, with leaderboard score plotted against cost-per-task.
ARC-AGI-210095.0%
ARC-AGI-2 v2 → · Published board — The second-generation ARC-AGI benchmark of passive fluid intelligence, with leaderboard score plotted against cost-per-task.
Chess Puzzles (Epoch AI)10072.0%
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 2026-06-259182.2
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)10084.0%
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.
AA Intelligence Index v5.0 · snapshot-2026-11-039656.9
AA Intelligence Index v5.0 · snapshot-2026-11-03 → · Published board — Artificial Analysis Intelligence Index v5.0. Models AA has not rescored on v5.0 are listed as estimates from their frozen v4.x value (isotonic fit over the models measured on both versions), never as measurements.
Safety/Alignment
BullshitBench V1 (clear pushback)7447.3%
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)8469.0%
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)10031.7%
CritPt (AA) published 2026-09-10 → · Published board — Tests research-level physics reasoning with Python, symbolic and numerical answers.
GPQA Diamond (AA)10096.1%
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)10095.8%
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.
Scale SEAL: DrugDiscoveryBenchno percentile65.4
Scale SEAL: DrugDiscoveryBench published 2026-09-22 → · Codex — Scale SEAL: DrugDiscoveryBench results published by Scale AI.
Scale SEAL: DrugDiscoveryBenchno percentile68.7
Scale SEAL: DrugDiscoveryBench published 2026-09-22 → · mini-SWE-agent — Scale SEAL: DrugDiscoveryBench results published by Scale AI.
BioMysteryBenchno percentile79.3%
BioMysteryBench published 2026-09-21 → · Published board — BioMysteryBench results published by Vals AI.
MysteryMechanismno percentile53.2%
MysteryMechanism published 2026-09-21 → · Published board — MysteryMechanism results published by Vals AI.
BioMysteryBench9279.3%
BioMysteryBench published 2026-09-22 → · Published board — BioMysteryBench results published by Vals AI.
MysteryMechanism10053.2%
MysteryMechanism published 2026-09-23 → · Published board — MysteryMechanism results published by Vals AI.
Tool-use
AutomationBench-AA v1.0.69968.5%
AutomationBench-AA v1.0.6 → · Published board — Tests multi-app SaaS workflows through REST tools on a held-out AutomationBench split.
τ³-Banking (AA) v1.0.18841.4%
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)8571.7%
Excel Modeling Benchmark (Vals Index v2) v2 → · Published board — Building and editing financial models in spreadsheets.
Excel Modeling Benchmark (standalone Vals board, 2026-09-22 snapshot)7371.7%
Excel Modeling Benchmark (standalone Vals board, 2026-09-22 snapshot) published 2026-09-22 → · Published board — Standalone Excel Modeling Benchmark results published by Vals AI, distinct from its Vals Index v2 subset.
Vision
MMMU Pro (AA)10086.9%
MMMU Pro (AA) published 2026-09-10 → · Published board — Tests multimodal understanding using challenging ten-option questions.
Chartography 100-tasks10071.0%
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-tasks9734.2%
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)9580.0%
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
4 threshold-crossing signals flagged · 41 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: 19.08878 USDPeer mean 6.89364 · peer sd 7.83661 · n 38 · families 37Directed z -1.556 · baseline z 1.497 · gap -3.053 · profile n 4019.08878 USDmeasured· 19.09 USD per rolloutobserved 2026-09-26vals.ai ↗Evidence
Axis: Vals Index v2 cost per test (Vals AI) · v2 · Published boardExact value:19.088776USDPublished mean cost: 19.088776 USD per rolloutObserved: 2026-09-26T04:22:13.903077+00:00 · publication date: not recordedObservation id:public:951ce6690d69cd50f95fe408 - unusually strong CritPt (AA) published 2026-09-10
Why
Observed: 0.31714 fractionPeer mean 0.04412 · peer sd 0.08179 · n 537 · families 370Directed z 3.338 · baseline z 1.375 · gap 1.963 · profile n 400.31714 fractionmeasuredobserved 2026-09-10artificialanalysis.ai ↗Evidence
Axis: CritPt (AA) · published 2026-09-10 · Published boardExact value:0.317142857142857fractionObserved: 2026-09-10T21:47:16.627Z · publication date: not recordedObservation id:aa:2f339a97-9a0d-499a-9cb5-e0db665bfa25:critpt - unusually strong Terminal-Bench v4.0 (AA)
Why
Observed: 0.59091 fractionPeer mean 0.10118 · peer sd 0.15754 · n 147 · families 107Directed z 3.109 · baseline z 1.402 · gap 1.706 · profile n 400.59091 fractionmeasuredobserved 2026-09-10artificialanalysis.ai ↗Evidence
Axis: Terminal-Bench v4.0 (AA) · v4.0 · Published boardExact value:0.590909090909091fractionObserved: 2026-09-10T21:47:16.627Z · publication date: not recordedObservation id:aa:2f339a97-9a0d-499a-9cb5-e0db665bfa25:terminalbenchV40 - unusually strong Mystery Game Puzzles (Epoch AI) published 2026-09-18
Why
Observed: 0.84 fractionPeer mean 0.31241 · peer sd 0.17484 · n 38 · families 28Directed z 3.018 · baseline z 1.383 · gap 1.635 · profile n 400.84 fractionmeasuredobserved 2026-09-18epoch.ai ↗Evidence
Axis: Mystery Game Puzzles (Epoch AI) · published 2026-09-18 · Published boardExact value:0.84fractionObserved: 2026-09-18T23:49:00Z · publication date: not recordedObservation id:public:55a84368f006dde9d6900b85
Missing coverage · 212 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 |
|---|---|---|
| GPT-6 Astra (High) | 77.1 | 54.8 |
| GPT-6 Astra (Max) | 76.9 | 56.9 |
| GPT-6 Astra (Medium) | 76.7 | 51.5 |
| GPT-6 Astra (Xhigh) | 75.9 | 55.3 |
| GPT-6 Astra (Low) | 75.7 | 43.0 |
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 · 7 offers (Adjusted $/task)
Click any underlined price to see how it is estimated and where each input comes from. How we calculate adjusted cost.
7 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/openai/gpt-6-astra/providers, collected 2026-11-03.
| Azureconditional | globalazure | $10.00 raw in $/1M | $50.00 raw out $/1M | |
| Azureconditional | globalazure/us | $11.00 raw in $/1M | $55.00 raw out $/1M | |
| Amazon Bedrockconditional | globalamazon-bedrock/us-west-2 | $11.00 raw in $/1M | $55.00 raw out $/1M | |
| Amazon Bedrockconditional | globalamazon-bedrock/global | $10.00 raw in $/1M | $50.00 raw out $/1M |
Azure AI Foundry (1)
Direct prices from Azure AI Foundry's own price list. Source: prices.azure.com/api/retail/prices, collected 2026-11-03.
| Azure AI Foundry | global | $10.00 raw in $/1M | $50.00 raw out $/1M |
T-Systems LLM Hub (2)
Direct prices from T-Systems LLM Hub's own price list. Source: docs.llmhub.t-systems.net/models/llms/, collected 2026-11-03.
| T-Systems LLM Hub | euup to 272k inputEU | $10.86 raw in $/1M | $54.29 raw out $/1M | |
| T-Systems LLM Hub | euabove 272k inputEU | $21.71 raw in $/1M | $81.43 raw out $/1M |