GPT-5.6 Terra (Low)

★ featured

OpenAI · released 2026-07-09 · 10 offers

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
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	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
3	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
4	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
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 one

47.8

AA Coding v4.x 58.1Coding Agent v1.4 38.6AA Intelligence (est.) 17.3AA 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.

Composite attachments (used in the score, not counted as exact benchmarks):

Epoch ECI · attached
Software ECI · attached
DesignArena Web Apps (agentic) · attached
DesignArena Full-Stack · attached

Compare this model →

Agentic

AA-Briefcase551,014 Elo2026-09-10
AA-Briefcase published 2026-09-10 → · Published board — Tests multi-week professional knowledge-work projects with linked tasks and large source collections.
GDPval-AA v2621,178 Elo2026-09-10
GDPval-AA v2 v2 → · Published board — Tests professional knowledge-work deliverables across occupations using AA's Stirrup harness.
Terminal-Bench Hard (AA)9143.9%2026-09-10
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)6262.5%2026-09-10
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)511.5%2026-09-10
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.

Coding

Artificial Analysis Coding Agent Index v1.41438.6%2026-09-09
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) v1.0.15349.9%2026-09-10
SciCode (AA subproblems) v1.0.1 → · Published board — Tests scientific Python programming with scientist-annotated background information.
CursorBench 4.0 (Cursor)developer's claim25.2%^{† self-reported by the developer}2026-10-27
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)324.1%2026-09-15
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 claim24.1%^{† self-reported by the developer}2026-09-13
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 v41459.7%2026-09-18
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 claim37.8%^{† self-reported by the developer}2026-09-26
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.
AA Coding Index v4.x · frozen 2026-10-276658.12026-10-27
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$0.52^{† self-reported by the developer}2026-10-27
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$0.5^{† self-reported by the developer}2026-09-13
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$0.45^{† self-reported by the developer}2026-09-26
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)7159.7%2026-09-10
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)8029.2%2026-09-10
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 Index74-6.832026-09-10
AA-Omniscience Index published 2026-09-10 → · Published board — Tests factual reliability while rewarding correct answers and penalizing hallucinations.
UGI NatInt8964.22026-09-10
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)7117.6%2026-09-10
GDP.pdf (AA) published 2026-09-10 → · Published board — Tests professional reasoning over long PDFs with AA document preparation and grading.
AA-LCR v1.16871.3%2026-09-10
AA-LCR v1.1 v1.1 → · Published board — Tests reasoning across multiple long documents with corrected answer keys and grading.
MLCR-AA318.9%2026-09-10
MLCR-AA published 2026-09-10 → · Published board — Tests medical-record synthesis and reasoning across long, fragmented case documents.

Reasoning

Chess Puzzles (Epoch AI)4822.0%2026-09-18
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)2719.0%2026-09-18
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)5929.1%2026-09-15
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)6247.0%2026-09-15
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)839.4%2026-09-10
CritPt (AA) published 2026-09-10 → · Published board — Tests research-level physics reasoning with Python, symbolic and numerical answers.
GPQA Diamond (AA)7684.3%2026-09-10
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)4687.4%2026-09-18
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 v1.0.65129.1%2026-09-10
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)5760.5%2026-09-10
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) v1.0.15118.8%2026-09-10
τ³-Banking (AA) v1.0.1 → · Published board — Tests banking support agents that retrieve policies and change account state through tools.

Uncensored

UGI Willingness222.202026-09-10
UGI Willingness published 2026-09-10 → · Published board — A private-question evaluation of how far a model follows challenging instructions before refusing or deviating.
UGI8250.92026-09-10
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)7276.1%2026-09-10
MMMU Pro (AA) published 2026-09-10 → · Published board — Tests multimodal understanding using challenging ten-option questions.

Writing

UGI Writing8556.82026-09-10
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

1 threshold-crossing signal flagged · 28 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 DeepSWE (Datacurve, via Epoch AI) published 2026-09-15
Why
Observed: 0.24053 fraction
Peer mean 0.56136 · peer sd 0.161 · n 63 · families 21
Directed z -1.993 · baseline z 0.423 · gap -2.415 · profile n 27
0.24053 fractionmeasuredobserved 2026-09-15epoch.ai ↗
Evidence
Axis: DeepSWE (Datacurve, via Epoch AI) · published 2026-09-15 · mini-SWE-agent
Exact value: 0.24053452115812918 fraction
Evaluation harness: mini-SWE-agent
Observed: 2026-09-15T09:05:24Z · publication date: not recorded
Observation id: public:c6c9d25cff4a24103d9a5625
Source: https://epoch.ai/data/benchmark_data.zip
Exact observation and full protocol ↗

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.

Input $2.00 / 1M

Cached input $0.200 / 1M

Cache write $2.50 / 1M

Output $12.00 / 1M

Status GA

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

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

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

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