GPT-5.5 (xhigh)
Context 922K 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 | Platform | Raw input $/1M | Raw output $/1M | Adjusted $/task |
|---|---|---|---|---|---|
| 1 | Azure | OpenRouter | $5.00 | $30.00 | |
| 2 | Amazon Bedrock | OpenRouter | $5.50 | $33.00 | |
| 3 | Azure AI Foundry | Azure AI Foundry | $5.00 | $30.00 | |
| 4 | AWS Bedrock | AWS Bedrock | $5.50 | $33.00 | |
| 5 | T-Systems LLM Hub | T-Systems LLM Hub | $5.54 | $33.20 |
Composite
7 of 7 inputs · 4 from the model family6 radar axes: DesignArena's two boards share one80.5
AA Coding 74.9Coding Agent v1.4 61.0AA Intelligence 38.6AA Agentic —Epoch ECI 159.1Software ECI 158.9DesignArena 1132/1099
Radar: percentile among all models measured on each input; a gap means not measured.
Benchmark sheet
54 of 140 registered benchmark versions · bars show the percentile among all models measured on each benchmark.
- Epoch ECI · attached
- Software ECI · attached
- DesignArena Web Apps (agentic) · attached
- DesignArena Full-Stack · attached
Agentic
AA-AnalystAgent8750.0%
AA-AnalystAgent published 2026-09-10 ↗ · Published board — Tests analyst tasks using agentic Python execution across fourteen domains.
APEX-Agents-AA9037.7%
APEX-Agents-AA published 2026-09-10 ↗ · Published board — Tests professional-service tasks that require agents to produce locally graded deliverables.
AA-Briefcase631,136 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 v2771,396 Elo
GDPval-AA v2 v2 ↗ · Published board — Tests professional knowledge-work deliverables across occupations using AA's Stirrup harness.
Harvey LAB-AA6086.3%
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.
ITBench-AA8845.8%
ITBench-AA published 2026-09-10 ↗ · Published board — Tests root-cause diagnosis from offline Kubernetes incident snapshots.
Terminal-Bench Hard (AA)9860.6%
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)8784.3%
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)7814.6%
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 CUA (NeoCognition)6820.0%
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.
ApprenticeBench API (NeoCognition)5027.0%
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.
Vals Index v2 (Vals AI)5357.4%
Vals Index v2 (Vals AI) v2 ↗ · Published board — GDP-weighted average of agentic model performance across finance, coding and legal tasks.
Finance Agent v2 (Vals Index v2)3751.8%
Finance Agent v2 (Vals Index v2) v2 ↗ · Published board — Multi-step financial reasoning tasks.
HLAB — Harvey's Legal Agent Benchmark (Vals Index v2)333.8%
HLAB — Harvey's Legal Agent Benchmark (Vals Index v2) v2 ↗ · Published board — Long-horizon legal work product creation. Vals AI's run of Harvey's Legal Agent Benchmark, reported as accuracy — not comparable with Artificial Analysis' Harvey LAB-AA row.
OSWorld 2.0, June 2026 task release (XLANG Lab) v2026.06.24no percentile13.0%
OSWorld 2.0, June 2026 task release (XLANG Lab) v2026.06.24 ↗ · batch tool — A computer-use agent completes 108 long-horizon, real-world workflows across 31 self-hosted websites and desktop applications, each taking a person about 1.6 hours.
EBR-bench (Earthborne Rangers, Epoch AI)6234.3%
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 v1.1no percentile27.2%
PostTrainBench v1.1 ↗ · Codex CLI — 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.
Coding
Artificial Analysis Coding Agent Index v1.47761.0%
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.
SciCode (AA subproblems) v1.0.18455.8%
SciCode (AA subproblems) v1.0.1 ↗ · Published board — Tests scientific Python programming with scientist-annotated background information.
Vibe Code Bench (Vals Index v2)4269.8%
Vibe Code Bench (Vals Index v2) v2 ↗ · Published board — End-to-end app-building tasks.
Code Migration (Vals Index v2 subset)7545.5%
Code Migration (Vals Index v2 subset) v2 ↗ · Published board — Porting projects to another language, including COBOL modernization.
FrontierCode 1.1 Main (Cognition) v1.1no percentile43.0%
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.
DeepSWE (Datacurve, via Epoch AI)6567.0%
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.
SWE Atlas Codebase QnA (Scale AI)4445.4%
SWE Atlas Codebase QnA (Scale AI) published 2026-09-15 ↗ · Published board — How well a coding agent answers deep questions about a real codebase, graded against expert rubrics.
SWE Atlas Test Writing (Scale AI)3342.6%
SWE Atlas Test Writing (Scale AI) published 2026-09-15 ↗ · Published board — Whether a coding agent writes production-grade tests for real repositories, graded with rubrics and LLM judges.
SWE Atlas Refactoring (Scale AI)4044.8%
SWE Atlas Refactoring (Scale AI) published 2026-09-15 ↗ · Published board — Whether a coding agent restructures production code while preserving its behaviour, graded by tests and rubrics.
GSO software optimization, Opt@1 (UC Berkeley) vopt1-1028940.2%
GSO software optimization, Opt@1 (UC Berkeley) vopt1-102 ↗ · OpenHands — An agent gets a real codebase and a performance test and must make the code as fast as an expert developer's optimization; 102 tasks across 10 codebases and 5 languages.
VulcanBench Frontier v45078.5%
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%.
AA Coding Index9074.9
AA Coding Index published 2026-09-19 ↗ · Published board — Artificial Analysis publishes this board without a version number; we keep the date each result was retained.
Efficiency
ApprenticeBench CUA cost per task (NeoCognition)18$12.68
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.
ApprenticeBench API cost per task (NeoCognition)25$2.82
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.
Vals Index v2 cost per test (Vals AI)33$6.14
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 Main cost per rollout (Cognition) v1.1no percentile$4.03
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.
Instruction-following
IFBench (AA single-turn)9475.9%
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)9645.8%
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 Index9220.5
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)5940.4%
Legal Research Bench (Vals Index v2) v2 ↗ · Published board — Case and statute research with citation-backed answers.
SimpleQA Verified (run by Epoch AI)7663.0%
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.
Long-context
GDP.pdf (AA)8121.2%
GDP.pdf (AA) published 2026-09-10 ↗ · Published board — Tests professional reasoning over long PDFs with AA document preparation and grading.
AA-LCR v1.19984.3%
AA-LCR v1.1 v1.1 ↗ · Published board — Tests reasoning across multiple long documents with corrected answer keys and grading.
MLCR-AA6317.8%
MLCR-AA published 2026-09-10 ↗ · Published board — Tests medical-record synthesis and reasoning across long, fragmented case documents.
Math
ArXivMath 06/2026 (MathArena) v2026-066083.6%
ArXivMath 06/2026 (MathArena) v2026-06 ↗ · Published board — Research-level math problems with a checkable final answer, drawn from arXiv papers submitted in June 2026, so they postdate most training data.
BrokenArXiv 06/2026 (MathArena) v2026-067069.4%
BrokenArXiv 06/2026 (MathArena) v2026-06 ↗ · 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 Tiers 1–3 v2 (Epoch AI)7985.3%
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.
FrontierMath Tier 4 v2 (Epoch AI)6972.5%
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.
Reasoning
Mystery Game Puzzles (Epoch AI)8956.0%
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 Index9338.6
AA Intelligence Index published 2026-09-19 ↗ · Published board — Artificial Analysis publishes this board without a version number; we keep the date each result was retained.
Safety/Alignment
BullshitBench V2 (clear pushback)6247.0%
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)9627.1%
CritPt (AA) published 2026-09-10 ↗ · Published board — Tests research-level physics reasoning with Python, symbolic and numerical answers.
GPQA Diamond (AA)9793.5%
GPQA Diamond (AA) published 2026-09-10 ↗ · Published board — Tests graduate-level biology, physics and chemistry knowledge on the Diamond subset.
Tool-use
AutomationBench-AA v1.0.67047.3%
AutomationBench-AA v1.0.6 ↗ · Published board — Tests multi-app SaaS workflows through REST tools on a held-out AutomationBench split.
EnterpriseOps-Gym-AA8146.6%
EnterpriseOps-Gym-AA published 2026-09-10 ↗ · Published board — Tests enterprise workflows through MCP tools against resettable application environments.
τ²-Bench Telecom (AA)9193.9%
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) v1.0.18339.0%
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)5664.5%
Excel Modeling Benchmark (Vals Index v2) v2 ↗ · Published board — Building and editing financial models in spreadsheets.
Vision
MMMU Pro (AA)8679.9%
MMMU Pro (AA) published 2026-09-10 ↗ · Published board — Tests multimodal understanding using challenging ten-option questions.
Unusual results
2 threshold-crossing signals 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 CritPt (AA) published 2026-09-10
Why
Observed: 0.27143 fractionPeer mean 0.03928 · peer sd 0.07596 · n 522 · families 369Directed z 3.056 · baseline z 0.907 · gap 2.15 · profile n 370.27143 fractionmeasuredobserved 2026-09-10artificialanalysis.ai ↗Evidence
Axis: CritPt (AA) · published 2026-09-10 · Published boardExact value:0.271428571428571fractionObserved: 2026-09-10T21:47:16.627Z · publication date: not recordedObservation id:aa:1f054429-397e-4fdb-9e71-67bc92c1735e:critpt - unusually strong Terminal-Bench Hard (AA)
Why
Observed: 0.60606 fractionPeer mean 0.18472 · peer sd 0.16951 · n 432 · families 315Directed z 2.486 · baseline z 0.922 · gap 1.563 · profile n 370.60606 fractionmeasuredobserved 2026-09-10artificialanalysis.ai ↗Evidence
Axis: Terminal-Bench Hard (AA) · pinned revision 74221fb · Published boardExact value:0.606060606060606fractionObserved: 2026-09-10T21:47:16.627Z · publication date: not recordedObservation id:aa:1f054429-397e-4fdb-9e71-67bc92c1735e:terminalbenchHard
Missing coverage · 89 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 2026-09-19 · Data: Artificial Analysis · Data: Epoch AI (CC BY)
| Variant | AA Coding | AA Intelligence |
|---|---|---|
| GPT-5.5 (xhigh) | 74.9 | 38.6 |
| GPT-5.5 (high) | 71.6 | 37.3 |
| GPT-5.5 (medium) | 71.5 | 34.2 |
| GPT-5.5 (low) | 60.9 | 30.7 |
| GPT-5.5 (Non-reasoning) | 56.5 | 23.2 |
SUBSCRIPTION PLAN
GitHub Copilot
Current usage-based billing · model token cost is converted to AI Credits at 1 credit = $0.01.
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Token offers by platform · 10 offers (Adjusted $/task)
Click any underlined price to see how it is estimated and where each input comes from. How we calculate adjusted cost.
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OpenRouter (4)
| Azure | globalazure | $5.00 raw in $/1M | $30.00 raw out $/1M | |
| Azure | globalazure/us | $5.50 raw in $/1M | $33.00 raw out $/1M | |
| Azure | euazure/euEU | $5.50 raw in $/1M | $33.00 raw out $/1M | |
| Amazon Bedrock | globalamazon-bedrock/us-east-1 | $5.50 raw in $/1M | $33.00 raw out $/1M |
Azure AI Foundry (4)
| Azure AI Foundry | globalshort context | $5.00 raw in $/1M | $30.00 raw out $/1M | |
| Azure AI Foundry | eushort contextEU | $5.50 raw in $/1M | $33.00 raw out $/1M | |
| Azure AI Foundry | globallong context | $10.00 raw in $/1M | $45.00 raw out $/1M | |
| Azure AI Foundry | eulong contextEU | $11.00 raw in $/1M | $49.50 raw out $/1M |
AWS Bedrock (1)
| AWS Bedrock | us-east-1 | $5.50 raw in $/1M | $33.00 raw out $/1M |
T-Systems LLM Hub (1)
| T-Systems LLM Hub | euEU | $5.54 raw in $/1M | $33.20 raw out $/1M |