Alex Getmansinyal AI awal

GPT-6 Luna

OpenAI

Dirilis Diperbarui
Jendela konteks
1M
1.050.000 token
Keluaran maksimal
128K
128.000 token
Masukan / Keluaran
teks, gambar → teks

Harga API

USD / 1 juta token

MasukanKeluaranMasukan dalam cache
  • $0,10
openrouter
  • $0,50
openrouter
  • $0,01
openrouter

Linimasa

  1. · Ketersediaan API · tautan bukti
  2. · Pembaruan produk · tautan bukti
Harga masukan / keluaran · USD / 1 juta token
ModelTautan buktiHarga masukan / keluaran
gpt-6-luna
batch · long context
openai
Rute API tidak tersedia
$0,10 (Masukan > 272.000 token) / $0,375 (Masukan > 272.000 token)
gpt-6-luna
batch · short context
openai
Rute API tidak tersedia
$0,05 (Masukan ≤ 272.000 token) / $0,25 (Masukan ≤ 272.000 token)
gpt-6-luna
fast · long context
openai
Rute API tidak tersedia
$0,40 (Masukan > 272.000 token) / $1,50 (Masukan > 272.000 token)
gpt-6-luna
fast · short context
openai
Rute API tidak tersedia
$0,20 (Masukan ≤ 272.000 token) / $1,00 (Masukan ≤ 272.000 token)
gpt-6-luna
flex · long context
openai
Rute API tidak tersedia
$0,10 (Masukan > 272.000 token) / $0,375 (Masukan > 272.000 token)
gpt-6-luna
flex · short context
openai
Rute API tidak tersedia
$0,05 (Masukan ≤ 272.000 token) / $0,25 (Masukan ≤ 272.000 token)
gpt-6-luna
standard · long context
openai
Rute API tidak tersedia
$0,20 (Masukan > 272.000 token) / $0,75 (Masukan > 272.000 token)
gpt-6-luna
standard · short context
openai
Rute API tidak tersedia
$0,10 (Masukan ≤ 272.000 token) / $0,50 (Masukan ≤ 272.000 token)
gpt-6-luna
standard · teks
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. · Penggunaan terkonfirmasi · OpenAI · official articles · How Amplitude ships product improvements in 1–2 days with OpenAI
    Kutipan
    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. · Entri katalog · GitHub · openai/openai-node · code
    Kutipan
    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. · Entri katalog · GitHub · openai/openai-agents-python · code
    Kutipan
    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. · Entri katalog · GitHub · openai/codex · code
    Kutipan
    _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. · Entri katalog · GitHub · openai/openai-agents-python · code
    Kutipan
    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

    Referensi dalam kode ini tidak mengonfirmasi pengenal model yang digunakan.

  6. · Entri katalog · GitHub · openai/openai-python · code
    Kutipan
    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. · Entri katalog · GitHub · openai/openai-agents-js · code
    Kutipan
    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. · Postingan Alex · Alex Getman
    Kutipan
    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. · Entri katalog · Vertex AI · quotas
  10. · Postingan Alex · Alex Getman
    Kutipan
    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. · Entri katalog · OpenAI API
  12. · Postingan Alex · Alex Getman
    Kutipan
    Little Haiku is finally coming back. I think it’ll give GPT-6 Luna some solid competition.
  13. · Postingan Alex · Alex Getman
    Kutipan
    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. · Postingan Alex · Alex Getman
    Kutipan
    🚨 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.

Tautan bukti

Sinyal 1

OpenAIDirilis

GPT-6 Luna

Dikonfirmasi15 tautan bukti
Spesifikasi

GPT-6 Luna adalah model AI dari OpenAI, dirilis pada 2026-09-22. Jendela konteksnya sebesar 1.050.000 token. Keluaran maksimalnya 128.000 token. Harga per satu juta token adalah $0,10 untuk input dan $0,50 untuk output.

Jendela konteks
1.050.000
Keluaran maksimal
128.000
Masukan
teks · gambar
Keluaran
teks
Masukan · USD / 1 juta token
$0,10
Keluaran · USD / 1 juta token
$0,50
Masukan dalam cache · USD / 1 juta token
$0,01

Pertanyaan

Seberapa besar jendela konteks GPT-6 Luna?

Jendela konteksnya sebesar 1.050.000 token. Keluaran maksimalnya 128.000 token.

Berapa biaya GPT-6 Luna?

Harga per satu juta token adalah $0,10 untuk input dan $0,50 untuk output. Masukan dari cache berharga $0,01 per juta token.

Kapan GPT-6 Luna dirilis?

2026-09-22.