GPT-6 Luna
Bekreftet15 kildelenker
Engelsk original

OpenAI
USD / 1 mill. tokener
| Inndata | Utdata | Bufrede inndata |
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| Modell | Dokumentasjonslenker | Pris for inndata / utdata |
|---|---|---|
gpt-6-lunabatch · long context | openai API-ruten er ikke tilgjengelig | $0,10 (Inndata > 272 000 tokener) / $0,375 (Inndata > 272 000 tokener) |
gpt-6-lunabatch · short context | openai API-ruten er ikke tilgjengelig | $0,05 (Inndata ≤ 272 000 tokener) / $0,25 (Inndata ≤ 272 000 tokener) |
gpt-6-lunafast · long context | openai API-ruten er ikke tilgjengelig | $0,40 (Inndata > 272 000 tokener) / $1,50 (Inndata > 272 000 tokener) |
gpt-6-lunafast · short context | openai API-ruten er ikke tilgjengelig | $0,20 (Inndata ≤ 272 000 tokener) / $1,00 (Inndata ≤ 272 000 tokener) |
gpt-6-lunaflex · long context | openai API-ruten er ikke tilgjengelig | $0,10 (Inndata > 272 000 tokener) / $0,375 (Inndata > 272 000 tokener) |
gpt-6-lunaflex · short context | openai API-ruten er ikke tilgjengelig | $0,05 (Inndata ≤ 272 000 tokener) / $0,25 (Inndata ≤ 272 000 tokener) |
gpt-6-lunastandard · long context | openai API-ruten er ikke tilgjengelig | $0,20 (Inndata > 272 000 tokener) / $0,75 (Inndata > 272 000 tokener) |
gpt-6-lunastandard · short context | openai API-ruten er ikke tilgjengelig | $0,10 (Inndata ≤ 272 000 tokener) / $0,50 (Inndata ≤ 272 000 tokener) |
gpt-6-lunastandard · tekst | opencode-go | $0,10 / $0,50 |
openai/gpt-6-luna-prostandard | openrouter | $0,10 / $0,50 |
openai/gpt-6-luna-pro:batchbatch | openrouter | $0,05 / $0,25 |
For high-volume work such as scanning code and running small evaluation checks, Amplitude uses GPT‑6 Luna to keep latency and cost low
shutdown date: 2026-09-28. See * https://developers.openai.com/api/docs/deprecations for details and * recommended replacements. */ model: | 'gpt-6-astra' | 'gpt-6.1-sol' | 'gpt-6.1-terra' | 'gpt-6-sol' | 'gpt-6-luna' | 'gpt-5.6-sol' | 'gpt-5.6-terra' | 'gpt-5.6-luna' | 'gpt-5.5' | 'gpt-5.5-2026-04-23' | 'gpt-5.4' | 'gpt-5.4-mini' | 'gpt-5.4-nano' | 'gpt-5.4-mini-2026-03-17' | 'gpt-5.4-nano-2026-03-17' | 'gpt-5.3-chat-latest' | 'gpt-5.2' | 'gpt-5.2-2025-12-11' | 'gpt-5.2-chat-latest' | 'gpt-5.2-pro' | 'gpt-5.2-pro-2025-12-11' | 'gpt-5.1' | 'gpt-5.1-2025-11-13' | 'gpt-5.1-codex' | 'gpt-5.1-mini' | 'gpt-5.1-chat-latest' | 'gpt-5' | 'gpt-5-mini' | 'gpt-5-nano' | 'gpt-5-2025-08-07' | 'gpt-5-mini-2025-08-07' | 'gpt-5-nano-2025-08-07' | 'gp
ry and should be used only when that history may be sent. """ def __init__( self, session_id: str, underlying_session: Session, *, client: AsyncOpenAI | None = None, model: str = "gpt-6-luna", compaction_mode: OpenAIResponsesCompactionMode = "auto", should_trigger_compaction: Callable[[dict[str, Any]], bool] | None = None, max_rollback_items: int | None = None, ): """Initialize the compaction session. Args: session_id: Identifier for this session. underlying_session: Session store that holds the compacted history. Cannot be OpenAIConversationsSession. client: OpenAI client for responses.compact API calls. Defaults to get_default_openai_client() or new AsyncOpenAI(). model: Model to use for respon
_ID: &str = "gpt-5.6-luna"; const GPT_6_1_SOL_OPENAI_MODEL_ID: &str = "gpt-6.1-sol"; const GPT_6_1_TERRA_OPENAI_MODEL_ID: &str = "gpt-6.1-terra"; const GPT_6_SOL_OPENAI_MODEL_ID: &str = "gpt-6-sol"; const GPT_6_LUNA_OPENAI_MODEL_ID: &str = "gpt-6-luna"; const GPT_6_ASTRA_OPENAI_MODEL_ID: &str = "gpt-6-astra"; const GPT_5_5_OPENAI_MODEL_ID: &str = "gpt-5.5"; pub(crate) fn static_model_catalog() -> ModelsResponse { let catalog = ModelsResponse { models: vec![ bedrock_model( bundled_openai_model(GPT_6_1_SOL_OPENAI_MODEL_ID), AMAZON_BEDROCK_GPT_6_1_SOL_MODEL_ID, "GPT-6.1 Sol", /*priority*/ 0, ), bedrock_model( bundled_openai_model(GPT_6_ASTRA_OPENAI_MODEL_ID), AMAZON_BEDROCK_GPT_6_ASTRA_MODEL_ID, "GPT-6-Astra",
s` リストが含まれます。質問名で回答をインデックス化し、型固有のフィールドを読み取る前に、各回答の `type` を確認します。 ```python from openai import AsyncOpenAI async def is_support_request(client: AsyncOpenAI, text: str) -> bool: decision = await client.decisions.create( model="gpt-6-luna", input=text, questions=[ { "type": "predicate", "name": "in_scope", "instructions": "Is this a request for help with a software product?", } ], ) answers = {answer.name: answer for answer in decision.answers} answer = answers.get("in_scope") if answer is None or answer.type != "predicate": return False return answer.probability >= 0.8 ``` 上記のしきい値は例示です。アプリケーションのラベル付きサンプルを使用してしきい値を選択してください。拒否は 1 つの質問に適用されます。同じレスポンス内の別の質問は、引き続き回答を返す可能性があります。拒否、回答の欠落、API エラーを各ワークフローでどのように処理するかを個別に決定してください。コード例では、利用できない分類器を肯定的な回答
Denne referansen i koden bekrefter ikke en modellidentifikator i bruk.
characters. Values are strings with a maximum length of 512 characters. """ model: Union[ Literal[ "gpt-6-astra", "gpt-6.1-sol", "gpt-6.1-terra", "gpt-6-sol", "gpt-6-luna", "gpt-5.6-sol", "gpt-5.6-terra", "gpt-5.6-luna", "gpt-5.5", "gpt-5.5-2026-04-23", "gpt-5.4", "gpt-5.4-mini", "gpt-5.4-nano", "gpt-5.4-mini-2026-03-17", "gpt-5.4-nano-2026-03-17", "gpt-5.3-chat-latest", "gpt-5.2", "gpt-5.2-2025-12-11", "gpt-5.2-chat-latest", "gpt-5.2-pro", "gpt-5.2-pro-2025-12-11", "gpt-5.1", "gpt-5.1-2025-11-13", "gpt-5.1-codex", "gpt-5.1-mini", "gpt-5.1-chat-latest"
derPrefix.toLowerCase(); const withoutPinnedDate = normalized.replace(/-\d{4}-\d{2}-\d{2}$/u, ''); return [...new Set([normalized, withoutPinnedDate])]; } const SANDBOX_CONTEXT_WINDOWS_1M = new Set([ 'gpt-6-astra', 'gpt-6-sol', 'gpt-6-luna', 'gpt-6.1-sol', 'gpt-5.6', 'gpt-5.6-sol', 'gpt-5.6-terra', 'gpt-5.6-luna', 'gpt-5.4', 'gpt-5.4-2026-03-05', 'gpt-5.4-pro', 'gpt-5.4-pro-2026-03-05', 'gpt-4.1', 'gpt-4.1-2025-04-14', 'gpt-4.1-mini', 'gpt-4.1-mini-2025-04-14', 'gpt-4.1-nano', 'gpt-4.1-nano-2025-04-14', ]); const SANDBOX_CONTEXT_WINDOWS_400K = new Set([ 'gpt-5', 'gpt-5-codex', 'gpt-5-mini', 'gpt-5-nano', 'gpt-5-pro', 'gpt-5.1', 'gpt-5.1-codex', 'gpt-5.1-codex-max', 'gpt-5.1-codex-mini', 'gpt-5.2', 'gpt-5.2-codex', 'gpt-5.2-codex-cyber', 'gpt-5.2-pro', 'gpt-5.3-codex', 'gpt-5.3-codex-spark', 'gpt-5.4-mini'
Meta just launched Muse Ember, a new competitor to GPT-6 Luna and Claude Haiku 5.5. It scores 36 points on the AA Intelligence Index, matching Claude Haiku 5.5 while costing 3x less per task.
AI subscription buying guide: $1 - Command Code $10 - OpenCode $20 - Claude $40 - Claude + GPT $120 - Claude Max + GPT At $1 and $10, you’re basically just paying for DeepSeek through these providers and getting it in bulk. For $1, you get $10 of DeepSeek and for $10, you get $60 of DeepSeek, which is basically impossible to burn through. DeepSeek obviously isn’t an S-tier model. I’d put it somewhere around B-tier, but at these prices it makes a lot of sense. At $20, Claude Pro. Probably the best value subscription on the market. Opus got cheaper, and the model itself is stronger than Astra, so there’s not much to think about here. At $40, I’d go with Claude Pro + ChatGPT Plus. ChatGPT
Little Haiku is finally coming back. I think it’ll give GPT-6 Luna some solid competition.
GPT-6 Luna may already be in A/B testing. Some GPT-5.6 Luna requests are being served as GPT-6 Luna behind the scenes.
🚨 GPT-6 Sol is already being tested internally There is a good chance it drops on DevDay, Sep 29. Tibo said Astra pulled some OpenAI releases forward by six months. Sol feels like the obvious candidate. GPT-6 Luna could show up too.
gpt-6-lunaGPT-6 Luna er en modell fra OpenAI, lansert 2026-09-22. Kontekstvinduet er 1 050 000 tokener. Maksimal utdatalengde er 128 000 tokener. Prisen er $0,10 per million inndatatokener og $0,50 per million utdatatokener.
Kontekstvinduet er 1 050 000 tokener. Maksimal utdatalengde er 128 000 tokener.
Prisen er $0,10 per million inndatatokener og $0,50 per million utdatatokener. Bufrede inndata koster $0,01 per million tokener.
Den 2026-09-22.