GPT-5.6 Luna observert på Artificial Analysis
Bekreftet3 kildelenker
Engelsk original

OpenAI
USD / 1 mill. tokener
| Inndata | Utdata | Bufrede inndata |
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| Modell | Dokumentasjonslenker | Pris for inndata / utdata |
|---|---|---|
gpt-5.6-lunabatch · long context | openai API-ruten er ikke tilgjengelig | $0,20 (Inndata > 272 000 tokener) / $0,90 (Inndata > 272 000 tokener) |
gpt-5.6-lunabatch · short context | openai API-ruten er ikke tilgjengelig | $0,10 (Inndata ≤ 272 000 tokener) / $0,60 (Inndata ≤ 272 000 tokener) |
gpt-5.6-lunafast · long context | openai API-ruten er ikke tilgjengelig | $0,80 (Inndata > 272 000 tokener) / $3,60 (Inndata > 272 000 tokener) |
gpt-5.6-lunafast · short context | openai API-ruten er ikke tilgjengelig | $0,40 (Inndata ≤ 272 000 tokener) / $2,40 (Inndata ≤ 272 000 tokener) |
gpt-5.6-lunaflex · long context | openai API-ruten er ikke tilgjengelig | $0,20 (Inndata > 272 000 tokener) / $0,90 (Inndata > 272 000 tokener) |
gpt-5.6-lunaflex · short context | openai API-ruten er ikke tilgjengelig | $0,10 (Inndata ≤ 272 000 tokener) / $0,60 (Inndata ≤ 272 000 tokener) |
gpt-5.6-lunastandard · long context | openai API-ruten er ikke tilgjengelig | $0,40 (Inndata > 272 000 tokener) / $1,80 (Inndata > 272 000 tokener) |
gpt-5.6-lunastandard · short context | openai API-ruten er ikke tilgjengelig | $0,20 (Inndata ≤ 272 000 tokener) / $1,20 (Inndata ≤ 272 000 tokener) |
gpt-5.6-lunastandard · tekst | opencode-go | $0,20 / $1,20 |
openai/gpt-5.6-luna-prostandard | openrouter | $0,20 / $1,20 |
openai/gpt-5.6-luna-pro:batchbatch | openrouter | $0,10 / $0,60 |
For real-time interactions, Ringg uses GPT‑5.6 Luna and other models to interpret customer requests, select tools, and guide customers through multi-step workflows
ai.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' | 'gpt-5-chat-latest' | 'gpt-4.1' | 'gpt-4.1-mini' | 'gp
""" model: str | Model | None = None """The model implementation to use when invoking the LLM. By default, if not set, the agent will use the default model configured in `agents.models.get_default_model()` (currently "gpt-5.6-luna"). """ model_settings: ModelSettings = field(default_factory=_default_agent_model_settings) """Configures model-specific tuning parameters (e.g. temperature, top_p). Accepts a ``ModelSettings`` instance or a dictionary containing its fields. """ input_guardrails: list[InputGuardrail[TContext]] = field(default_factory=list) """A list of checks that run in parallel to the agent's execution, before generating a response. Runs only if the agent is the first agent in the chain. """ output_guardrails: list[OutputGuardrail[TContext]] = field(default_factory=list) """A list of checks that run
").plan_type("pro"), AuthCredentialsStoreMode::File, )?; let config = load_default_config_for_test(&codex_home).await; let models = [MODEL, "gpt-5.6-luna", "gpt-6.1-sol"] .into_iter() .map(|slug| { let mut info = codex_core::test_support::construct_model_info_offline(slug, &config); if slug == MODEL { info.auto_review_model_override = Some("gpt-6.1-sol".to_owned()); } info })
Denne referansen i koden bekrefter ikke en modellidentifikator i bruk.
se super::BedrockEndpoint; const GPT_5_BEDROCK_CONTEXT_WINDOW: i64 = 272_000; const GPT_5_6_SOL_OPENAI_MODEL_ID: &str = "gpt-5.6-sol"; const GPT_5_6_TERRA_OPENAI_MODEL_ID: &str = "gpt-5.6-terra"; const GPT_5_6_LUNA_OPENAI_MODEL_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",
#third-party-adapters) | ## OpenAI モデル {#openai-models} OpenAI のみを使用するほとんどのアプリでは、デフォルトの OpenAI プロバイダーで文字列のモデル名を使用し、Responses モデル経路を維持する方法を推奨します。 [`Agent`][agents.agent.Agent] でモデルを指定しない場合、Agents SDK はコスト重視で大量処理を行うエージェントワークフロー向けに、デフォルトで [`gpt-5.6-luna`](https://developers.openai.com/api/docs/models/gpt-5.6-luna) を `reasoning.effort="none"` および `verbosity="low"` とともに使用します。最先端の能力が必要なアプリケーションでは、`model="gpt-5.6-sol"` を明示的に設定し、ワークロードに適した `model_settings` を選択できます。 `gpt-5.6-sol` などの別のモデルへ切り替える場合、エージェントを設定する方法は 2 つあります。 ### デフォルトモデル {#default-model} まず、カスタムモデルを設定していないすべてのエージェントで特定のモデルを一貫して使用する場合は、エージェントを実行する前に `OPENAI_DEFAULT_MODEL` 環境変数を設定します。 ```bash export OPENAI_DEFAULT_MODEL=gpt-5.6-sol python3 my_awesome_agent.py ``` 次に、`RunConfig` を使用して、実行単位のデフォルトモデルを設定できます。エージェントにモデルを設定していない場合、この実行のモデルが使用されます。 ```python from agents import Agent, RunConfig, Runner agent = Agent( name="
Denne referansen i koden bekrefter ikke en modellidentifikator i bruk.
" 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", "gpt-5", "gpt-5-mini", "gpt-5-nano",
t5ReasoningSettingsRequired(getDefaultModel()); } /** * Returns the default model name. */ export function getDefaultModel(): string { const env = loadEnv(); return ( env[OPENAI_DEFAULT_MODEL_ENV_VARIABLE_NAME]?.toLowerCase() ?? 'gpt-5.6-luna' ); } /** * Returns the default model settings. * GPT-5-and-newer reasoning models receive model-specific defaults when known. * Otherwise, returns the legacy default model settings. */ export function getDefaultModelSettings(model?: string): ModelSettings { const _model = model ?? getDefaultModel(); if (isGpt5OrNewerReasoningModel(_model)) { const effort = getDefaultReasoningEffort(_model); if (effort !== undefined) { return { reasoning: { effort }, text: { verbosity: 'low' }, }; } return { // Keep the shared text verbosity default, but omit reasoning.effort for //
GPT‑5.6 Luna will become the default model for Free and Go users this week
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.
⚡️ OpenAI added Luna Reserve after you hit your usage limits The official docs now mention Luna Reserve. Selected Plus and Pro accounts can keep working in Codex and ChatGPT Work with GPT 5.6 Luna after hitting their regular usage limit. Luna Reserve has its own separate limit and isn't available to everyone yet.
GPT 5.6 Luna is now a native subagent It can now work alongside Sol and Terra. Until now, Luna was on the previous subagent system, so users had to rely on workarounds to plug it in.
Over the last few days, I burned through around 1.5 billion tokens using GPT-5.6 Luna. At first, I ran it on Max reasoning because that’s what everyone was recommending. Later I switched to xHigh. Max costs about twice as much as xHigh and, from what I can tell, also takes about twice as long to think. My main takeaway is that the model is genuinely very good. For short and medium tasks, I often had Claude Opus 5 double check Luna’s work, and most of the time it agreed with the result. Longer tasks are a different story. Luna can overthink things, lose track of what it was doing at the beginning, handle the middle well, and then fail to finish the last part properly. On these longer task
⚡️ GPT 5.6 Luna is becoming the default model for ChatGPT Free and Go users Starting next week, it will also come with unlimited text chats and a new Think button for harder questions.
⚡️ Alibaba released Qwen 3.8 Max The new 2.4T parameter flagship benchmarks in the same league as GPT-5.6 Sol, Claude Opus 4.8 and Fable 5. API pricing is $2/M input and $6/M output, roughly half the cost of GPT-5.6 Terra and Claude Sonnet. Now it’s up to users to see whether Qwen can beat DeepSeek-V4-Flash and GPT-5.6 Luna on price to performance.
Yesterday GPT 5.6 Luna pushed the Pareto frontier for intelligence and cost. Today DeepSeek V4 Flash did it again and pushed it even further.
Using GPT 5.6 Luna Max, you get the power of March’s flagship GPT 5.4 xhigh for one thirteenth of its price.
GPT-5.6 Luna er en modell fra OpenAI, lansert 2026-07-09. Kontekstvinduet er 1 050 000 tokener. Maksimal utdatalengde er 128 000 tokener. Prisen er $0,20 per million inndatatokener og $1,20 per million utdatatokener.
Kontekstvinduet er 1 050 000 tokener. Maksimal utdatalengde er 128 000 tokener.
Prisen er $0,20 per million inndatatokener og $1,20 per million utdatatokener. Bufrede inndata koster $0,02 per million tokener.
Den 2026-07-09.