GPT-5.6 Terra (Xhigh)
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 | 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 | $13.20 | |
| 2 | 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. | $2.00 | $12.00 | |
| 3 | Azurevia OpenRouter — Price via OpenRouter: OpenRouter's price for Azure's endpoint (https://openrouter.ai/openai/gpt-5.6-terra/providers), collected 2026-11-03. | via OpenRouter — Price via OpenRouter: OpenRouter's price for Azure's endpoint (https://openrouter.ai/openai/gpt-5.6-terra/providers), collected 2026-11-03. | $2.00 | $12.00 | |
| 4 | Amazon Bedrockvia OpenRouter — Price via OpenRouter: OpenRouter's price for Amazon Bedrock's endpoint (https://openrouter.ai/openai/gpt-5.6-terra/providers), collected 2026-11-03. | via OpenRouter — Price via OpenRouter: OpenRouter's price for Amazon Bedrock's endpoint (https://openrouter.ai/openai/gpt-5.6-terra/providers), collected 2026-11-03. | $2.20 | $13.20 | |
| 5 | 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. | $3.95 | $17.74 |
Composite
7 of 7 inputs · 4 from the model family6 radar axes: DesignArena's two boards share one56.9
AA Coding v4.x 70.6Coding Agent v1.4 56.0AA Intelligence (est.) 27.8AA Agentic —Epoch ECI 160.1Software ECI 159.6DesignArena 1105/1061
Radar: percentile among all models measured on each input; a gap means not measured.
Benchmark sheet
36 of 319 registered benchmark versions · bars show the percentile among all models measured on each benchmark.
6 of 37 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-Briefcase771,337 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 v2851,479 Elo
GDPval-AA v2 v2 → · Published board — Tests professional knowledge-work deliverables across occupations using AA's Stirrup harness.
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)8180.1%
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)6810.1%
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.
τ^τ-bench (Hyper-τ), release v1 (Sierra)no percentile18.0%
τ^τ-bench (Hyper-τ), release v1 (Sierra) release-v1 → · Codex — 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.
Scale SEAL: SWE-Bench Pro V2 HARD5086.3
Scale SEAL: SWE-Bench Pro V2 HARD published 2026-09-22 → · Published board — Scale SEAL: SWE-Bench Pro V2 HARD results published by Scale AI.
LMArena Agent Arena (overall net improvement)110.8%
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 v1.46456.0%
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) v1.0.16652.3%
SciCode (AA subproblems) v1.0.1 → · Published board — Tests scientific Python programming with scientist-annotated background information.
CursorBench 4.0 (Cursor)developer's claim33.6%† 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)5260.2%
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 claim38.8%† 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.
VulcanBench Frontier v45983.5%
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%.
FrontierCode 1.1 Extended (Cognition)developer's claim52.6%† 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.
Scale SEAL: SWE-Bench Pro V2 Full1192.4%
Scale SEAL: SWE-Bench Pro V2 Full published 2026-09-26 → · Published board — Scale AI’s refreshed public SWE-Bench Pro split (642 long-horizon tasks in 11 copyleft repositories) run under a locked protocol, scored by resolve rate.
LMArena WebDev (Code Arena, overall)201,521 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 2026-10-278170.6
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
CursorBench 4.0 cost per task (Cursor)developer's claim$1.81† 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$1.38† 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.
FrontierCode 1.1 Extended cost per rollout (Cognition)developer's claim$1.17† 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.
Instruction-following
IFBench (AA single-turn)7866.3%
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)9141.9%
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 Index77-2.98
AA-Omniscience Index published 2026-09-10 → · Published board — Tests factual reliability while rewarding correct answers and penalizing hallucinations.
UGI NatInt9067.1
UGI NatInt published 2026-09-10 → · Published board — A private-question evaluation of general knowledge and reasoning across textbook, popular-culture and world-model topics.
Long-context
GDP.pdf (AA)9024.6%
GDP.pdf (AA) published 2026-09-10 → · Published board — Tests professional reasoning over long PDFs with AA document preparation and grading.
AA-LCR v1.18479.0%
AA-LCR v1.1 v1.1 → · Published board — Tests reasoning across multiple long documents with corrected answer keys and grading.
MLCR-AA7621.7%
MLCR-AA published 2026-09-10 → · Published board — Tests medical-record synthesis and reasoning across long, fragmented case documents.
Science
CritPt (AA)9527.1%
CritPt (AA) published 2026-09-10 → · Published board — Tests research-level physics reasoning with Python, symbolic and numerical answers.
GPQA Diamond (AA)9190.8%
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 v1.0.66447.1%
AutomationBench-AA v1.0.6 → · Published board — Tests multi-app SaaS workflows through REST tools on a held-out AutomationBench split.
τ²-Bench Telecom (AA)7080.4%
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) v1.0.16729.7%
τ³-Banking (AA) v1.0.1 → · Published board — Tests banking support agents that retrieve policies and change account state through tools.
Uncensored
UGI Willingness222.20
UGI Willingness published 2026-09-10 → · Published board — A private-question evaluation of how far a model follows challenging instructions before refusing or deviating.
UGI7547.7
UGI published 2026-09-10 → · Published board — A private-question suite combining sensitive-topic knowledge with willingness to follow controversial instructions.
Vision
MMMU Pro (AA)8379.5%
MMMU Pro (AA) published 2026-09-10 → · Published board — Tests multimodal understanding using challenging ten-option questions.
Writing
UGI Writing8958.9
UGI Writing published 2026-09-10 → · Published board — A maintainer-owned writing evaluation considering intelligence, style, repetition and length adherence, informed by human preferences.
Unusual results
2 threshold-crossing signals flagged · 24 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 0.04412 · peer sd 0.08179 · n 537 · families 370Directed z 2.779 · baseline z 0.858 · gap 1.922 · profile n 230.27143 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:9e30696f-16fa-4b4f-ba53-161895a85fed:critpt - 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 0.864 · gap 1.755 · profile n 230.62879 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:9e30696f-16fa-4b4f-ba53-161895a85fed:terminalbenchHard
Missing coverage · 283 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-5.6 Terra (Max) | 76.7 | 32.2est. |
| GPT-5.6 Terra (Xhigh) | 70.6 | 27.8est. |
| GPT-5.6 Terra (High) | 67.1 | 24.0est. |
| GPT-5.6 Terra (Medium) | 64.7 | 18.4est. |
| GPT-5.6 Terra (Low) | 58.1 | 17.3est. |
| GPT-5.6 Terra (Non-reasoning) | 52.3 | 9.8est. |
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 · 8 offers (Adjusted $/task)
Click any underlined price to see how it is estimated and where each input comes from. How we calculate adjusted cost.
8 offers within the active global filters, 2 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.
AWS Bedrock (1)
Direct prices from AWS Bedrock's own price list. Source: aws.amazon.com/bedrock/pricing/, collected 2026-11-03.
| AWS Bedrock | us-east-1 | $2.20 raw in $/1M | $13.20 raw out $/1M |
Azure AI Foundry (2)
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 | $2.00 raw in $/1M | $12.00 raw out $/1M | |
| Azure AI Foundry | euEU | $2.20 raw in $/1M | $13.20 raw out $/1M |
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-5.6-terra/providers, collected 2026-11-03.
| Azureconditional | globalazure | $2.00 raw in $/1M | $12.00 raw out $/1M | |
| Azureconditional | globalazure/us | $2.20 raw in $/1M | $13.20 raw out $/1M | |
| Amazon Bedrockconditional | globalamazon-bedrock/us-east-1 | $2.20 raw in $/1M | $13.20 raw out $/1M | |
| Azureconditional | euazure/euEU | $2.20 raw in $/1M | $13.20 raw out $/1M |
T-Systems LLM Hub (1)
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 | euEU | $3.95 raw in $/1M | $17.74 raw out $/1M |