{ "id": "gpt-5.6-terra", "language": "ta", "url": "https://alexgetman.com/ta/models/openai/gpt-5-6-terra/", "name": "GPT-5.6 Terra", "model_identity": { "id": "gpt-5.6-terra", "name": "GPT-5.6 Terra", "maker": { "id": "openai", "name": "OpenAI" }, "version": "5.6", "checkpoint": null, "first_seen_at": "2026-07-10T16:34:15.332Z" }, "catalogue_section": "main", "stage": "released", "expectation": { "state": "released", "last_evidence_at": "2026-11-12T18:45:20.401Z", "related_model_id": null, "evidence": [], "claims": [ { "reference": "post:53", "outcome": "unresolved" }, { "reference": "post:79", "outcome": "unresolved" }, { "reference": "post:142", "outcome": "unresolved" }, { "reference": "post:182", "outcome": "unresolved" }, { "reference": "post:196", "outcome": "unresolved" }, { "reference": "post:382", "outcome": "unresolved" }, { "reference": "post:423", "outcome": "unresolved" }, { "reference": "code:github:openai/openai-agents-js:models:gpt-5.6-terra", "outcome": "confirmed" }, { "reference": "code:github:openai/openai-python:models:gpt-5.6-terra", "outcome": "confirmed" }, { "reference": "code:github:openai/openai-agents-python:models:gpt-5.6-terra", "outcome": "confirmed" }, { "reference": "code:github:openai/codex:models:gpt-5.6-terra:Production", "outcome": "confirmed" }, { "reference": "code:github:openai/codex:models:gpt-5.6-terra:Test", "outcome": "unresolved" }, { "reference": "code:github:openai/openai-node:models:gpt-5.6-terra:Production:753c855a3d9eeee52ecb3c923e6eabe4fe82658ffd6297e55ee3cbc9d0b1fc1b", "outcome": "confirmed" }, { "reference": "record:openai-articles:https://openai.com/index/retell-ai:usage:gpt-5.6-terra", "outcome": "related" }, { "reference": "record:openai-articles:https://openai.com/index/how-we-detect-frontier-model-misalignment:usage:gpt-5.6-terra", "outcome": "related" } ] }, "watch_presentation": { "placement": "expected", "family": { "key": "openai:gpt-terra", "name": "GPT Terra" } }, "observations": [], "timeline": [ { "reference": "post:53", "kind": "editorial_mention", "at": "2026-07-10T16:34:15.332Z", "event_at": { "precision": "time", "value": "2026-07-10T16:34:15.332Z" }, "historical": false, "source": "editorial", "source_label": "Alex Getman", "url": "https://alexgetman.com/53/grok-4-5-a-new-competitor-to-gpt-and-claude/", "quote": "Grok 4.5: a new competitor to GPT and Claude\n\nPosting this a little late, but I prepared something interesting. Grok 4.5 is temporarily available to test for free in Grok Build and Cursor.\n\nThe model runs at around 80 tokens per second, supports a context window of up to 500,000 tokens, and costs $2 per million input tokens and $6 per million output tokens. According to Musk, Grok 4.5 was trained from scratch on SpaceXAI’s own foundation and is not built on top of Kimi like Composer.\n\nIn terms of quality, Grok 4.5 comes close to GPT-5.6 Terra, while its pricing is closer to Luna. Among Anthropic models, it sits between Haiku and Sonnet, making it especially attractive in terms of price-to-pe", "co_mentions": [ "claude-opus-4-8", "grok-4.3", "grok-4.5", "gpt-5" ] }, { "reference": "post:79", "kind": "editorial_mention", "at": "2026-07-16T17:56:24.898Z", "event_at": { "precision": "time", "value": "2026-07-16T17:56:24.898Z" }, "historical": false, "report_intent": "incidental", "source": "editorial", "source_label": "Alex Getman", "url": "https://alexgetman.com/79/release-kimi-k3/", "quote": "⚡️ RELEASE: KIMI K3\n\nMoonshot just dropped its new flagship: 2.8T parameters, a 1M-token context window, native vision, and a focus on large projects, coding, games, and 3D. Full weights are expected in the next few days.\n\nAPI: $3 / $15 per million input/output tokens. Pricing-wise, that puts it around Sonnet 5 or GPT-5.6 Terra, while Moonshot’s own benchmarks have it taking shots at Opus 4.8 and Sol.\n\nSo basically: Opus-class performance at Sonnet pricing. You can already try it for free on the Kimi website or through Kimi Code CLI.", "co_mentions": [ "claude-opus-4-8", "claude-sonnet-5", "gpt-5" ] }, { "reference": "post:142", "kind": "editorial_mention", "at": "2026-08-03T08:01:30.947Z", "event_at": { "precision": "time", "value": "2026-08-03T08:01:30.947Z" }, "historical": false, "source": "editorial", "source_label": "Alex Getman", "url": "https://alexgetman.com/142/alibaba-released-qwen-3-8-max/", "quote": "⚡️ Alibaba released Qwen 3.8 Max\n\nThe new 2.4T parameter flagship benchmarks in the same league as GPT-5.6 Sol, Claude Opus 4.8 and Fable 5.\n\nAPI pricing is $2/M input and $6/M output, roughly half the cost of GPT-5.6 Terra and Claude Sonnet.\n\nNow it’s up to users to see whether Qwen can beat DeepSeek-V4-Flash and GPT-5.6 Luna on price to performance.", "co_mentions": [ "claude-opus-4-8", "deepseek-v4-flash", "gpt-5.6-luna", "gpt-5.6-sol", "qwen3.8-max", "gpt-5" ] }, { "reference": "post:182", "kind": "editorial_mention", "at": "2026-08-14T05:00:00Z", "event_at": { "precision": "time", "value": "2026-08-14T05:00:00Z" }, "historical": false, "source": "editorial", "source_label": "Alex Getman", "url": "https://alexgetman.com/182/very-few-people-know-this-but-muse-spark-1-2-might-be-the-best-value-model-on-th/", "quote": "Very few people know this, but Muse Spark 1.2 might be the best value model on the market right now.\n\nIts intelligence is around GPT-5.6 Terra.\n\nBut if you use Muse Code and agree to code analysis through the Contributor tier, the price drops 10–20x.\n\nSo you basically get Terra-level intelligence at Luna-level cost.", "co_mentions": [ "muse-spark-1.2", "gpt-5" ] }, { "reference": "post:196", "kind": "editorial_mention", "at": "2026-08-18T05:00:00Z", "event_at": { "precision": "time", "value": "2026-08-18T05:00:00Z" }, "historical": false, "report_intent": "incidental", "source": "editorial", "source_label": "Alex Getman", "url": "https://alexgetman.com/196/qwen-3-8-27b-beat-gpt-5-6-terra/", "quote": "⚡️ Qwen 3.8 27B beat GPT 5.6 Terra\n\nThis happened in the AA Agentic Index, a benchmark that tests how well models handle agentic tasks. And you can run Qwen 3.8 27B locally on a single RTX 3090.", "co_mentions": [ "qwen3.8", "gpt-5" ] }, { "reference": "post:382", "kind": "editorial_mention", "at": "2026-09-02T15:31:23.681Z", "event_at": { "precision": "time", "value": "2026-09-02T15:31:23.681Z" }, "historical": false, "report_intent": "incidental", "source": "editorial", "source_label": "Alex Getman", "url": "https://alexgetman.com/382/google-released-gemini-3-8-flash/", "quote": "🚨 Google released Gemini 3.8 Flash\n\n• still $0.75 per 1M input tokens\n• at the same price, it is noticeably stronger than Gemini 3.7 Flash across almost the entire table\n• especially big gains in autonomous computer use and complex scientific tasks\n• beats GPT 5.6 Terra, a model in the same class, on almost every benchmark", "co_mentions": [ "gemini-3.8-flash", "gpt-5" ] }, { "reference": "post:423", "kind": "editorial_mention", "at": "2026-09-16T15:54:37.278Z", "event_at": { "precision": "time", "value": "2026-09-16T15:54:37.278Z" }, "historical": false, "source": "editorial", "source_label": "Alex Getman", "url": "https://alexgetman.com/423/jev-is-out-a-new-ai-model-from-startup-typesafe-ai/", "quote": "Jev is out, a new AI model from startup TypeSafe AI\n\nIt is built for fast decision making inside apps. You give it context and possible actions, and it picks the best option with probability and confidence.\n\nTypeSafe says Jev reaches GPT 5.6 Terra level on these tasks, responds in 70 to 500ms, and costs $0.042 per 1M input tokens. Output is free.\n\nIt can route support tickets, score risk, and check AI agent actions.", "co_mentions": [ "gpt-5" ] }, { "reference": "code:github:openai/openai-agents-js:models:gpt-5.6-terra", "kind": "catalogue_listed", "at": "2026-11-10T17:58:10.980Z", "historical": false, "code_usage": "production", "source": "github:openai/openai-agents-js:models", "source_label": "GitHub · openai/openai-agents-js · code", "url": "https://github.com/openai/openai-agents-js/blob/7589b9c40120b89a7d2d28a5a60b4defe1ed7bf5/packages/agents-core/src/sandbox/capabilities/compaction.ts", "quote": ".replace(/-\\d{4}-\\d{2}-\\d{2}$/u, '');\n\n return [...new Set([normalized, withoutPinnedDate])];\n}\n\nconst SANDBOX_CONTEXT_WINDOWS_1M = new Set([\n 'gpt-6-astra',\n 'gpt-6-sol',\n 'gpt-6-luna',\n 'gpt-6.1-sol',\n 'gpt-5.6',\n 'gpt-5.6-sol',\n 'gpt-5.6-terra',\n 'gpt-5.6-luna',\n 'gpt-5.4',\n 'gpt-5.4-2026-03-05',\n 'gpt-5.4-pro',\n 'gpt-5.4-pro-2026-03-05',\n 'gpt-4.1',\n 'gpt-4.1-2025-04-14',\n 'gpt-4.1-mini',\n 'gpt-4.1-mini-2025-04-14',\n 'gpt-4.1-nano',\n 'gpt-4.1-nano-2025-04-14',\n]);\n\nconst SANDBOX_CONTEXT_WINDOWS_400K = new Set([\n 'gpt-5',\n 'gpt-5-codex',\n 'gpt-5-mini',\n 'gpt-5-nano',\n 'gpt-5-pro',\n 'gpt-5.1',\n 'gpt-5.1-codex',\n 'gpt-5.1-codex-max',\n 'gpt-5.1-codex-mini',\n 'gpt-5.2',\n 'gpt-5.2-codex',\n 'gpt-5.2-codex-cyber',\n 'gpt-5.2-pro',\n 'gpt-5.3-codex',\n 'gpt-5.3-codex-spark',\n 'gpt-5.4-mini',\n 'gpt-5.4-nano',\n]);\n\nconst SANDBOX_CONTEXT_WINDOWS_200K = new ", "co_mentions": [] }, { "reference": "code:github:openai/openai-python:models:gpt-5.6-terra", "kind": "catalogue_listed", "at": "2026-11-10T17:58:16.002Z", "historical": false, "code_usage": "production", "source": "github:openai/openai-python:models", "source_label": "GitHub · openai/openai-python · code", "url": "https://github.com/openai/openai-python/blob/0ebd00647f6088fb100b03440c6c4554bbab549d/src/openai/types/beta/beta_responses_client_event.py", "quote": "gth of 512 characters.\n \"\"\"\n\n model: Union[\n Literal[\n \"gpt-6-astra\",\n \"gpt-6.1-sol\",\n \"gpt-6.1-terra\",\n \"gpt-6-sol\",\n \"gpt-6-luna\",\n \"gpt-5.6-sol\",\n \"gpt-5.6-terra\",\n \"gpt-5.6-luna\",\n \"gpt-5.5\",\n \"gpt-5.5-2026-04-23\",\n \"gpt-5.4\",\n \"gpt-5.4-mini\",\n \"gpt-5.4-nano\",\n \"gpt-5.4-mini-2026-03-17\",\n \"gpt-5.4-nano-2026-03-17\",\n \"gpt-5.3-chat-latest\",\n \"gpt-5.2\",\n \"gpt-5.2-2025-12-11\",\n \"gpt-5.2-chat-latest\",\n \"gpt-5.2-pro\",\n \"gpt-5.2-pro-2025-12-11\",\n \"gpt-5.1\",\n \"gpt-5.1-2025-11-13\",\n \"gpt-5.1-codex\",\n \"gpt-5.1-mini\",\n \"gpt-5.1-chat-latest\",\n \"gpt-5\",\n \"gpt-5-mini\",\n ", "co_mentions": [] }, { "reference": "code:github:openai/openai-agents-python:models:gpt-5.6-terra", "kind": "catalogue_listed", "at": "2026-11-10T17:59:50.472Z", "historical": false, "code_usage": "production", "source": "github:openai/openai-agents-python:models", "source_label": "GitHub · openai/openai-agents-python · code", "url": "https://github.com/openai/openai-agents-python/blob/d68961657843c7d81dfc25834484f8aac2957eb3/src/agents/sandbox/capabilities/compaction.py", "quote": " \"gpt-5.4-pro\",\n \"gpt-5.4-pro-2026-03-05\",\n \"gpt-5.5\",\n \"gpt-5.5-2026-04-23\",\n \"gpt-5.5-pro\",\n \"gpt-5.5-pro-2026-04-23\",\n \"gpt-5.6\",\n \"gpt-5.6-sol\",\n \"gpt-5.6-terra\",\n \"gpt-5.6-luna\",\n \"gpt-4.1\",\n \"gpt-4.1-2025-04-14\",\n \"gpt-4.1-mini\",\n \"gpt-4.1-mini-2025-04-14\",\n \"gpt-4.1-nano\",\n \"gpt-4.1-nano-2025-04-14\",\n ),\n 1_047_576,\n ),\n **_model_context_windows(\n (\n \"gpt-5\",\n \"gpt-5-2025-08-07\",\n \"gpt-5-codex\",\n \"gpt-5-mini\",\n \"gpt-5-mini-2025-08-07\",\n \"gpt-5-nano\",\n \"gpt-5-nano-2025-08-07\",\n \"gpt-5-pro\",\n \"gpt-5-pro-2025-10-06\",\n \"gpt-5.1\",\n \"gpt-5.1-2025-11-13\",\n \"gpt-", "co_mentions": [] }, { "reference": "code:github:openai/codex:models:gpt-5.6-terra:Production", "kind": "catalogue_listed", "at": "2026-11-10T18:00:44.369Z", "historical": false, "code_usage": "production", "source": "github:openai/codex:models", "source_label": "GitHub · openai/codex · code", "url": "https://github.com/openai/codex/blob/82e6bacb9c6950d3b56cb153847fa80bdd698053/codex-rs/model-provider/src/amazon_bedrock/catalog.rs", "quote": "se;\nuse codex_protocol::openai_models::WebSearchToolType;\n\nuse super::BedrockEndpoint;\n\nconst GPT_5_BEDROCK_CONTEXT_WINDOW: i64 = 272_000;\nconst GPT_5_6_SOL_OPENAI_MODEL_ID: &str = \"gpt-5.6-sol\";\nconst GPT_5_6_TERRA_OPENAI_MODEL_ID: &str = \"gpt-5.6-terra\";\nconst GPT_5_6_LUNA_OPENAI_MODEL_ID: &str = \"gpt-5.6-luna\";\nconst GPT_6_1_SOL_OPENAI_MODEL_ID: &str = \"gpt-6.1-sol\";\nconst GPT_6_1_TERRA_OPENAI_MODEL_ID: &str = \"gpt-6.1-terra\";\nconst GPT_6_SOL_OPENAI_MODEL_ID: &str = \"gpt-6-sol\";\nconst GPT_6_LUNA_OPENAI_MODEL_ID: &str = \"gpt-6-luna\";\nconst GPT_6_ASTRA_OPENAI_MODEL_ID: &str = \"gpt-6-astra\";\nconst GPT_5_5_OPENAI_MODEL_ID: &str = \"gpt-5.5\";\n\npub(crate) fn static_model_catalog() -> ModelsResponse {\n let catalog = ModelsResponse {\n models: vec![\n bedrock_model(\n bundled_openai_model(GPT_6_1_SOL_OPENAI_MODEL_ID),\n AMAZON_BEDROCK_GPT_6_", "co_mentions": [] }, { "reference": "code:github:openai/codex:models:gpt-5.6-terra:Test", "kind": "catalogue_listed", "at": "2026-11-10T18:00:44.369Z", "historical": false, "code_usage": "test", "source": "github:openai/codex:models", "source_label": "GitHub · openai/codex · code", "url": "https://github.com/openai/codex/blob/627b579219d492b5445d6d433d3110eb53e507dc/codex-rs/core/src/config/config_tests.rs", "quote": "cfg = ConfigToml {\n agents: Some(AgentsToml {\n enabled: Some(false),\n max_depth: Some(2),\n default_subagent_model: Some(\"gpt-5.6-terra\".to_string()),\n default_subagent_reasoning_effort: Some(ReasoningEffort::High),\n interrupt_message: Some(false),\n ..Default::default()\n }),\n ..Default::default()\n };\n\n let config = Config::load_from_base_config_with_overrides(\n cfg,\n ConfigOverrides::d", "co_mentions": [] }, { "reference": "code:github:openai/openai-node:models:gpt-5.6-terra:Production:753c855a3d9eeee52ecb3c923e6eabe4fe82658ffd6297e55ee3cbc9d0b1fc1b", "kind": "catalogue_listed", "at": "2026-11-12T18:45:20.401Z", "historical": false, "code_usage": "production", "source": "github:openai/openai-node:models", "source_label": "GitHub · openai/openai-node · code", "url": "https://github.com/openai/openai-node/blob/b579bcb3e586d22269ffe6fe504653a0e05acbe8/src/resources/beta/responses/responses.ts", "quote": "ttps://developers.openai.com/api/docs/deprecations for details and\n * recommended replacements.\n */\n model:\n | 'gpt-6-astra'\n | 'gpt-6.1-sol'\n | 'gpt-6.1-terra'\n | 'gpt-6-sol'\n | 'gpt-6-luna'\n | 'gpt-5.6-sol'\n | 'gpt-5.6-terra'\n | 'gpt-5.6-luna'\n | 'gpt-5.5'\n | 'gpt-5.5-2026-04-23'\n | 'gpt-5.4'\n | 'gpt-5.4-mini'\n | 'gpt-5.4-nano'\n | 'gpt-5.4-mini-2026-03-17'\n | 'gpt-5.4-nano-2026-03-17'\n | 'gpt-5.3-chat-latest'\n | 'gpt-5.2'\n | 'gpt-5.2-2025-12-11'\n | 'gpt-5.2-chat-latest'\n | 'gpt-5.2-pro'\n | 'gpt-5.2-pro-2025-12-11'\n | 'gpt-5.1'\n | 'gpt-5.1-2025-11-13'\n | 'gpt-5.1-codex'\n | 'gpt-5.1-mini'\n | 'gpt-5.1-chat-latest'\n | 'gpt-5'\n | 'gpt-5-mini'\n | 'gpt-5-nano'\n | 'gpt-5-2025-08-07'\n | 'gpt-5-mini-2025-08-07'\n | 'gpt-5-nano-2025-08-07'\n | 'gpt-5-chat-latest'\n | 'gpt-4.1'\n | 'gp", "co_mentions": [] }, { "reference": "record:openai-articles:https://openai.com/index/how-we-detect-frontier-model-misalignment:usage:gpt-5.6-terra", "kind": "usage_confirmed", "at": "2026-11-14T08:23:25.536Z", "event_at": { "precision": "time", "value": "2026-10-29T09:00:00Z" }, "historical": true, "source": "openai-articles", "source_label": "OpenAI · official articles · How we detect frontier model misalignment", "url": "https://openai.com/index/how-we-detect-frontier-model-misalignment", "quote": null, "co_mentions": [] }, { "reference": "record:openai-articles:https://openai.com/index/retell-ai:usage:gpt-5.6-terra", "kind": "usage_confirmed", "at": "2026-11-14T08:45:27.686Z", "event_at": { "precision": "time", "value": "2026-10-27T15:00:00Z" }, "historical": true, "source": "openai-articles", "source_label": "OpenAI · official articles · Retell uses OpenAI models to help power 100M monthly calls", "url": "https://openai.com/index/retell-ai", "quote": "After a call, Retell uses GPT‑5.6 Terra to analyze the transcript and extract outcomes and other data", "co_mentions": [] } ], "offers": [ { "id": "[\"openai\",\"gpt-5.6-terra\",\"batch\",\"long context\"]", "model_id": "gpt-5.6-terra", "provider_id": "openai", "api_id": "gpt-5.6-terra", "mode": "batch", "context_band": "long context", "available": false, "prices": { "currency": "USD", "unit": "per_million_tokens", "input": { "amount": 2.0, "mode": "batch", "source": "pricing:openai-pricing:batch", "observed_at": "2026-11-12T16:08:47.129Z", "evidence": [ { "source": "openai-pricing", "url": "https://developers.openai.com/api/docs/pricing", "authority": "first_party", "scope": { "kind": "offer", "id": "[\"openai\",\"gpt-5.6-terra\",\"batch\",\"long context\"]" }, "detected_at": null, "checked_at": "2026-11-12T16:08:47.129Z" } ], "condition": { "label": "for prompts over 272000 tokens", "input_tokens": { "min_exclusive": 272000, "max_inclusive": null } } }, "output": { "amount": 9.0, "mode": "batch", "source": "pricing:openai-pricing:batch", "observed_at": "2026-11-12T16:08:47.129Z", "evidence": [ { "source": "openai-pricing", "url": "https://developers.openai.com/api/docs/pricing", "authority": "first_party", "scope": { "kind": "offer", "id": "[\"openai\",\"gpt-5.6-terra\",\"batch\",\"long context\"]" }, "detected_at": null, "checked_at": "2026-11-12T16:08:47.129Z" } ], "condition": { "label": "for prompts over 272000 tokens", "input_tokens": { "min_exclusive": 272000, "max_inclusive": null } } }, "cached_input": { "amount": 0.2, "mode": "batch", "source": "pricing:openai-pricing:batch", "observed_at": "2026-11-12T16:08:47.129Z", "evidence": [ { "source": 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