
GPT-6 Astra
OpenAI
- Fenêtre de contexte
- 1M 1 050 000 jetons
- Sortie maximale
- 128K 128 000 jetons
- Entrée / Sortie
- texte, image → texte
Tarifs API
USD / 1 million de tokens
| Entrée | Sortie | Entrée en cache |
|---|---|---|
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Chronologie
- · Disponibilité API · lien de référence · lien de référence
- · Disponibilité API · lien de référence
Prix entrée/sortie · USD / 1 million de tokens
| Modèle | Liens de référence | Prix entrée/sortie |
|---|---|---|
gpt-6-astrabatch · long context | openai Route API indisponible | $10,00 (Entrée > 272 000 jetons) / $37,50 (Entrée > 272 000 jetons) |
gpt-6-astrabatch · short context | openai Route API indisponible | $5,00 (Entrée ≤ 272 000 jetons) / $25,00 (Entrée ≤ 272 000 jetons) |
gpt-6-astrafast · long context | openai Route API indisponible | $40,00 (Entrée > 272 000 jetons) / $150,00 (Entrée > 272 000 jetons) |
gpt-6-astrafast · short context | openai Route API indisponible | $20,00 (Entrée ≤ 272 000 jetons) / $100,00 (Entrée ≤ 272 000 jetons) |
gpt-6-astraflex · long context | openai Route API indisponible | $10,00 (Entrée > 272 000 jetons) / $37,50 (Entrée > 272 000 jetons) |
gpt-6-astraflex · short context | openai Route API indisponible | $5,00 (Entrée ≤ 272 000 jetons) / $25,00 (Entrée ≤ 272 000 jetons) |
gpt-6-astrastandard · long context | openai Route API indisponible | $20,00 (Entrée > 272 000 jetons) / $75,00 (Entrée > 272 000 jetons) |
gpt-6-astrastandard · short context | openai Route API indisponible | $10,00 (Entrée ≤ 272 000 jetons) / $50,00 (Entrée ≤ 272 000 jetons) |
gpt-6-astraultrafast · long context | openai Route API indisponible | $120,00 (Entrée > 272 000 jetons) / $450,00 (Entrée > 272 000 jetons) |
gpt-6-astraultrafast · short context | openai Route API indisponible | $60,00 (Entrée ≤ 272 000 jetons) / $300,00 (Entrée ≤ 272 000 jetons) |
openai/gpt-6-astra-prostandard | openrouter | $10,00 / $50,00 |
openai/gpt-6-astra-pro:batchbatch | openrouter | $5,00 / $25,00 |
- · Utilisation confirmée · OpenAI · official articles · A model guide for the GPT-6 family
- · Liens de référence · OpenAI · official articles
Extrait
When we introduced GPT‑6 Astra, we demonstrated how far our models have come in using computers for professional work, from preparing documents to testing websites
- · Utilisation confirmée · OpenAI · official articles · How Jump Trading is scaling quant research with ChatGPT
Extrait
Jump Trading uses GPT‑6 Astra to take on longer, more ambiguous research problems
- · Liens de référence · OpenAI · official articles
Extrait
Jump Trading uses GPT‑6 Astra to take on longer, more ambiguous research problems
- · Liens de référence · OpenAI · official articles
- · Liens de référence · OpenAI · official articles
Extrait
Making longer videos possible with GPT‑6 Astra
- · Utilisation confirmée · OpenAI · official articles · Asana cuts model costs 76x in browser tests with GPT-6.1 Sol
- · Liens de référence · OpenAI · official articles
Extrait
We used some of our most capable and aligned models, including our upcoming GPT‑6 Astra Cyber model and an internal frontier model
- · Utilisation confirmée · OpenAI · official articles · Greptile takes bug detection beyond code review with GPT-6 Astra
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How Greptile uses GPT‑6 Astra to test user workflows, Daybreak to strengthen security, and Codex to reduce rework
- · Utilisation confirmée · OpenAI · official articles · Retell uses OpenAI models to help power 100M monthly calls
- · Utilisation confirmée · OpenAI · official articles · Qodo builds context into AI code review with Codex
- · Utilisation confirmée · OpenAI · official articles · DevRev delivers autonomous self-service with GPT-6.1 Sol
Extrait
DevRev’s sales engineers also use GPT‑6 Astra to create demos for the company’s booths at international conferences
- · Utilisation confirmée · OpenAI · official articles · Merge builds product and business tools with OpenAI technology
Extrait
For its own product development, Merge uses GPT‑6 Astra
- · Liens de référence · OpenAI · official articles
- · Liens de référence · OpenAI · official articles
- · Utilisation confirmée · OpenAI · official articles · Introducing Astra for Law
- · Liens de référence · OpenAI · official articles
Extrait
It will appear in the model picker as “GPT‑6 Astra Law” and in the API as gpt-6-astra-law
- · Liens de référence · OpenAI · official articles
Extrait
We’ve also brought GPT‑6 Astra’s improved communication style to Sol and Luna, which we think will be especially noticeable in technical and coding conversations
- · Entrée du catalogue · GitHub · openai/openai-node · code
Extrait
ils and * recommended replacements. * - "gpt-3.5-turbo-1106": Announced 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-5-20
- · Utilisation confirmée · OpenAI · official articles · Cogent and OpenAI build cyber defense factories for enterprises
- · Entrée du catalogue · GitHub · openai/codex · code
Extrait
es::start_mock_server().await; let board = responses::start_mock_server().await; let url = board.uri(); let root = test_codex() .with_model("gpt-6-astra") .with_config(move |config| { configure(config); config.ephemeral = true; for feature in [ Feature::CodeMode, Feature::CodeModeOnly, Feature::CodeModeHost, ] { config .features
Cette référence dans le code ne confirme pas un identifiant de modèle utilisé.
- · Entrée du catalogue · GitHub · openai/codex · code
Extrait
EL_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", /*priority*/ 1, ), bedrock_mod
- · Entrée du catalogue · GitHub · openai/openai-agents-python · code
Extrait
ody={"reasoning_effort": "low"}), False, "low", ), ("gpt-6-sol", "string", "none", ModelSettings(), False, None), ("gpt-6.1-sol", "string", "function", ModelSettings(), False, None), ("gpt-6-astra", "string", "function", ModelSettings(), False, None), ("gpt-6-sol-unknown", "string", "function", ModelSettings(), False, None), ("gpt-6-sol", "string", "function", ModelSettings(), True, None), ], ) @pytest.mark.parametrize("stream", [False, True]) async def test_gpt6_tool_request_defaults( name: str, entry: str, tools: str, settings: ModelSettings, responses: bool, expected: str | None, stream: bool, ) -> None: if responses and stream: pytest.skip("Responses preservation is covered by the non-streaming request.") before = settings.to_json_dict() bodies: list[dic
Cette référence dans le code ne confirme pas un identifiant de modèle utilisé.
- · Entrée du catalogue · GitHub · openai/openai-python · code
Extrait
ormat, and querying for objects via API or the dashboard. Keys are strings with a maximum length of 64 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-
- · Entrée du catalogue · GitHub · openai/openai-agents-js · code
Extrait
(): boolean { return isGpt5OrNewerReasoningModel(getDefaultModel()); } const DEFAULT_REASONING_EFFORT_PATTERNS: Array< readonly [ RegExp, Exclude<ModelSettingsReasoningEffort, 'minimal' | 'xhigh' | 'max' | null>, ] > = [ [/^gpt-6-astra$/, 'low'], [/^gpt-5(?:-\d{4}-\d{2}-\d{2})?$/, 'low'], [/^gpt-5\.1(?:-\d{4}-\d{2}-\d{2})?$/, 'none'], [/^gpt-5\.2(?:-\d{4}-\d{2}-\d{2})?$/, 'none'], [/^gpt-5\.2-pro(?:-\d{4}-\d{2}-\d{2})?$/, 'medium'], [/^gpt-5\.2-codex$/, 'low'], [/^gpt-5\.3-codex$/, 'none'], [/^gpt-5\.4(?:-\d{4}-\d{2}-\d{2})?$/, 'none'], [/^gpt-5\.4-pro(?:-\d{4}-\d{2}-\d{2})?$/, 'medium'], [/^gpt-5\.4-mini(?:-\d{4}-\d{2}-\d{2})?$/, 'none'], [/^gpt-5\.4-nano(?:-\d{4}-\d{2}-\d{2})?$/, 'none'], [/^gpt-5\.5(?:-\d{4}-\d{2}-\d{2})?$/, 'none'], [/^gpt-5\.6$/, 'none'], [/^gpt-5\.6-sol(?:-\d{4}-\d{2}-\d{2})?$/, 'none'], [/^gpt-5\.6-terra(?:-\d{4
- · Entrée du catalogue · Vertex AI · quotas
- · Publications d'Alex · Alex Getman
Extrait
Kimi K3.1 Pro benchmarks are out! Of all these benchmarks, I trust Terminal-Bench 4.0 the most. And the results are impressive: Kimi K3.1 Pro scores 65.7, just 0.7 points behind the leader, Opus 5.5, while outperforming GPT-6 Astra by 7.5 points.
- · Publications d'Alex · gamme · Alex Getman
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Looks like Astra 6.1 is coming OpenAI rolled out a private test model gpt-6-astra-api-priv-ev3
- · Liens de référence · OpenAI · news
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Higgsfield brings creators longer videos with GPT-6 Astra, precise visuals with GPT-Image-2.5, and a path to voice filmmaking with GPT-Live
- · Publications d'Alex · Alex Getman
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Meta just released Muse Wonder According to the benchmarks, it's right up there with GPT 6 Astra and Claude Opus 5.5. The results look impressive, but the model might be heavily optimized for benchmarks. It's still unclear how well it actually performs in real world use. And yeah, most of you probably won't be able to try it through a subscription, since Muse is still only available in the US.
- · Publications d'Alex · Alex Getman
Extrait
🚨 The French at Mistral just dropped Large 4 Looks like Europe’s biggest hope in frontier AI is still alive. 1 trillion parameters, with 49B active at a time. In some benchmarks, it already beats GPT 6 Astra and competes with the strongest open weight models. The API is live now, with weights coming by the end of October. And yes, Mistral internally calls it Le Chonk. After the fat cat meme. https://www.youtube.com/watch?v=hD51W2txi1Y
- · Publications d'Alex · Alex Getman
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🚨 Gemini 4 Argon scores 53 and ties for 3rd place with Fable 5.1 and GPT 6 Astra on the AA Intelligence Index
- · Publications d'Alex · Alex Getman
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🚨 Sonnet 5.5 Max beats GPT-6 Astra Max on the Intelligence Index vs. cost curve A few other things stand out: 1. At medium, GPT-6 Sol is much cheaper than Sonnet 5.5 at a fairly similar intelligence level. 2. Around the Pareto line, GPT-6 Sol Max and Sonnet 5.5 High are basically neck and neck. 3. GPT-6 Astra Max lands roughly around Sonnet 5.5 XHigh. + Sonnet 5.5 Max is in a league of its own at the top.
- · Publications d'Alex · Alex Getman
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🚨 Gemini 4.0 Pro specs leaked • Pricing: $2.25/$11.25 • 2M token context window • Beats GPT-6 Astra and Claude Fable 5.1 on almost every reported benchmark • While being significantly cheaper than both
- · Publications d'Alex · Alex Getman
Extrait
🚨 Union Alpha just dropped in stealth on OpenCode It scores around 51% on Terminal Bench v4 at roughly $1.5 per task, putting it close to GPT 6 Astra high for much less. My guess is this is a new Chinese model, possibly Kimi. Kimi has also brought its paid plans back to the site after pausing new memberships. The timing lines up.
- · Publications d'Alex · Alex Getman
Extrait
OpenAI has a new internal model that is way ahead of GPT 6 Astra in math On a curated set of open math problems, it reaches about 48% pass rate with more test time compute. GPT 6 Astra peaks at around 17%.
- · Publications d'Alex · Alex Getman
Extrait
🚨 OpenAI’s new internal model solved the Navier-Stokes Millennium Prize Problem Around 10,000 agents worked on the solution for 88 hours, powered by a model significantly more capable than GPT 6 Astra. After the solution was found, GPT 6 Astra formalized and verified the proof in Lean.
- · Publications d'Alex · Alex Getman
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🚨 Fable 5.2 could launch this month after Astra’s strong debut Anthropic is reportedly preparing its first fresh pretrain for Fable ahead of its IPO. People there are confident it can dethrone Astra. For context: Fable 5.1 and GPT 6 Astra currently share #1 on AA, with Fable slightly ahead in coding and Astra much stronger on 3D tasks.
- · Publications d'Alex · Alex Getman
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🚨 GPT-6 Astra is officially #1 on the updated Artificial Analysis Intelligence Index, sharing the top spot with Claude Fable 5.1.
- · Publications d'Alex · Alex Getman
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GPT 6 Astra set a new record in MazeBench, a 3D puzzle benchmark It explored 40% of all rooms and collected 14% of gems Fable 5.1 reached just 4.3% of rooms and collected 2% of gems
- · Publications d'Alex · Alex Getman
Extrait
GPT-6 Astra Fast mode quietly went from 1.5x to 2x speed, with the same 2.5x usage multiplier. It’s still pretty expensive though. A task that would count as 1,000 usage units on Standard would count as 2,500 on Fast, so that’s still 150% more usage. *My previous post was deleted because I got the math wrong. I misled some of you, and I’m sorry about that.
- · Publications d'Alex · Alex Getman
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Correction: I got the calculation in this post wrong. A 2.5× usage multiplier means 150% more usage, not 25%. Corrected calculation: https://alexgetman.com/403/gpt-6-astra-fast-mode-quietly-went-from-1-5x-to-2x-speed-with-the-same-2-5x-usag/ GPT-6 Astra Fast mode quietly went from 1.5x to 2x speed, with usage still at 2.5x So you’re getting double the speed for just 25% extra usage. At this point, there’s very little reason to turn Fast mode off.
- · Publications d'Alex · Alex Getman
Extrait
GPT 6 Astra and Fable 5.1 got 20 attempts to pick up a block and place it into a bowl Astra: 95% success, 2.5 min, $0.94 per run Fable 5.1: 40% success, 6.8 min, $2.12 per run Astra also used 6× fewer output tokens, just 2.1k per run.
- · Publications d'Alex · Alex Getman
Extrait
Claude is no longer the best model for frontend GPT-6 Astra just took the #1 spot, knocking Claude Fable 5.1 off the top The jump is massive: the previous GPT generation, GPT-5.6 Sol, was #13 A GPT model hasn’t led frontend since August 2025
- · Publications d'Alex · Alex Getman
Extrait
GPT 6 Astra and Fable 5.1 got 20 attempts to pick up a block and place it into a bowl Astra: 95% success, 2.5 min, $0.94 per run Fable 5.1: 40% success, 6.8 min, $2.12 per run Astra also used 6× fewer output tokens, just 2.1k per run.
- · Publications d'Alex · Alex Getman
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🚨 Plus users got access to GPT-6 Astra
- · Publications d'Alex · Alex Getman
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🚨 GPT-6 Astra is out for Pro users
- · Publications d'Alex · Alex Getman
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GPT-6 Astra looked like a generational leap on OpenAI’s benchmarks. Artificial Analysis puts it closer to old Fable 5 territory.
- · Publications d'Alex · Alex Getman
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🚨 GPT-6 Astra is officially out https://openai.com/index/gpt-6-astra/
- · Publications d'Alex · Alex Getman
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🚨 GPT-6 Astra is absolutely crushing everyone on the benchmarks
- · Publications d'Alex · Alex Getman
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🚨 GPT-6 Astra has been added to the OpenAI API Launch in less than 24 hours
- · Publications d'Alex · Alex Getman
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🚨 OpenAI is launching GPT 6 Astra next week It is a brand new model trained from scratch and the company’s largest since GPT 4.5. The latest internal build, codenamed mewfour, is already the release candidate.
Le calendrier prévu ne s’est pas confirmé ; conservé comme mention précoce, pas comme prédiction réussie.
Signaux 1
Caractéristiques
GPT-6 Astra est un modèle de OpenAI, sorti le 2026-09-03. La fenêtre de contexte est de 1 050 000 jetons. La sortie est limitée à 128 000 jetons. Le tarif par million de jetons est de $10,00 en entrée et de $50,00 en sortie.
- Fenêtre de contexte
- 1 050 000
- Sortie maximale
- 128 000
- Entrée
- texte · image
- Sortie
- texte
- Entrée · USD / 1 million de tokens
- $10,00
- Sortie · USD / 1 million de tokens
- $50,00
- Entrée en cache · USD / 1 million de tokens
- $1,00
Questions
Quelle est la fenêtre de contexte de GPT-6 Astra ?
La fenêtre de contexte est de 1 050 000 jetons. La sortie est limitée à 128 000 jetons.
Combien coûte GPT-6 Astra ?
Le tarif par million de jetons est de $10,00 en entrée et de $50,00 en sortie. L'entrée en cache coûte $1,00 par million.
Quand GPT-6 Astra est-il sorti ?
Le 2026-09-03.