Alex GetmanAI 早期訊號

GPT-6 Luna

OpenAI

已發布 更新於
上下文視窗
1M
1,050,000 token
最大輸出
128K
128,000 token
輸入 / 輸出
文字, 影像 → 文字

API 價格

USD / 百萬 token

輸入輸出快取輸入
  • $0.10
openrouter
  • $0.50
openrouter
  • $0.01
openrouter

時間軸

  1. · API 開放 · 參考連結
  2. · 產品更新 · 參考連結
輸入/輸出價格 · USD / 百萬 token
模型參考連結輸入/輸出價格
gpt-6-luna
batch · long context
openai
API 路由無法使用
$0.10 (輸入 > 272,000 token) / $0.375 (輸入 > 272,000 token)
gpt-6-luna
batch · short context
openai
API 路由無法使用
$0.05 (輸入 ≤ 272,000 token) / $0.25 (輸入 ≤ 272,000 token)
gpt-6-luna
fast · long context
openai
API 路由無法使用
$0.40 (輸入 > 272,000 token) / $1.50 (輸入 > 272,000 token)
gpt-6-luna
fast · short context
openai
API 路由無法使用
$0.20 (輸入 ≤ 272,000 token) / $1.00 (輸入 ≤ 272,000 token)
gpt-6-luna
flex · long context
openai
API 路由無法使用
$0.10 (輸入 > 272,000 token) / $0.375 (輸入 > 272,000 token)
gpt-6-luna
flex · short context
openai
API 路由無法使用
$0.05 (輸入 ≤ 272,000 token) / $0.25 (輸入 ≤ 272,000 token)
gpt-6-luna
standard · long context
openai
API 路由無法使用
$0.20 (輸入 > 272,000 token) / $0.75 (輸入 > 272,000 token)
gpt-6-luna
standard · short context
openai
API 路由無法使用
$0.10 (輸入 ≤ 272,000 token) / $0.50 (輸入 ≤ 272,000 token)
gpt-6-luna
standard · 文字
opencode-go$0.10 / $0.50
openai/gpt-6-luna-pro
standard
openrouter$0.10 / $0.50
openai/gpt-6-luna-pro:batch
batch
openrouter$0.05 / $0.25
  1. · 已確認使用 · OpenAI · official articles · How Amplitude ships product improvements in 1–2 days with OpenAI
    摘錄
    For high-volume work such as scanning code and running small evaluation checks, Amplitude uses GPT‑6 Luna to keep latency and cost low
  2. · 目錄記錄 · GitHub · openai/openai-node · code
    摘錄
    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
  3. · 目錄記錄 · GitHub · openai/openai-agents-python · code
    摘錄
    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
  4. · 目錄記錄 · GitHub · openai/codex · code
    摘錄
    _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",
  5. · 目錄記錄 · GitHub · openai/openai-agents-python · code
    摘錄
    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

    此程式碼引用並不能證實這是實際使用中的模型識別碼。

  6. · 目錄記錄 · GitHub · openai/openai-python · code
    摘錄
    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"
  7. · 目錄記錄 · GitHub · openai/openai-agents-js · code
    摘錄
    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'
  8. · Alex 的文章 · Alex Getman
    摘錄
    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.
  9. · 目錄記錄 · Vertex AI · quotas
  10. · Alex 的文章 · Alex Getman
    摘錄
    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
  11. · 目錄記錄 · OpenAI API
  12. · Alex 的文章 · Alex Getman
    摘錄
    Little Haiku is finally coming back. I think it’ll give GPT-6 Luna some solid competition.
  13. · Alex 的文章 · Alex Getman
    摘錄
    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.
  14. · Alex 的文章 · Alex Getman
    摘錄
    🚨 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.

參考連結

訊號 1

OpenAI已發布

GPT-6 Luna

已確認15個參考連結
規格

GPT-6 Luna 是 OpenAI 的 AI 模型,於 2026-09-22 發布。 上下文視窗為1,050,000 token。 最大輸出為128,000 token。 每百萬 token 的價格為:輸入 $0.10,輸出 $0.50。

上下文視窗
1,050,000
最大輸出
128,000
輸入
文字 · 影像
輸出
文字
輸入 · USD / 百萬 token
$0.10
輸出 · USD / 百萬 token
$0.50
快取輸入 · USD / 百萬 token
$0.01

常見問題

GPT-6 Luna 的上下文視窗有多大?

上下文視窗為1,050,000 token。 最大輸出為128,000 token。

GPT-6 Luna 的價格是多少?

每百萬 token 的價格為:輸入 $0.10,輸出 $0.50。 快取輸入價格為每百萬 token $0.01。

GPT-6 Luna 何時發布?

2026-09-22。