
GPT-6 Astra
OpenAI
- Ventana de contexto
- 1M 1.050.000 tokens
- Salida máxima
- 128K 128.000 tokens
- Entrada / Salida
- texto, imagen → texto
Precios de API
USD / 1 millón de tokens
| Entrada | Salida | Entrada en caché |
|---|---|---|
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Cronología
- · Disponibilidad en API · enlace de referencia · enlace de referencia
- · Disponibilidad en API · enlace de referencia
Precio entrada/salida · USD / 1 millón de tokens
| Modelo | Enlaces de referencia | Precio entrada/salida |
|---|---|---|
gpt-6-astrabatch · long context | openai Ruta de API no disponible | $10,00 (Entrada > 272.000 tokens) / $37,50 (Entrada > 272.000 tokens) |
gpt-6-astrabatch · short context | openai Ruta de API no disponible | $5,00 (Entrada ≤ 272.000 tokens) / $25,00 (Entrada ≤ 272.000 tokens) |
gpt-6-astrafast · long context | openai Ruta de API no disponible | $40,00 (Entrada > 272.000 tokens) / $150,00 (Entrada > 272.000 tokens) |
gpt-6-astrafast · short context | openai Ruta de API no disponible | $20,00 (Entrada ≤ 272.000 tokens) / $100,00 (Entrada ≤ 272.000 tokens) |
gpt-6-astraflex · long context | openai Ruta de API no disponible | $10,00 (Entrada > 272.000 tokens) / $37,50 (Entrada > 272.000 tokens) |
gpt-6-astraflex · short context | openai Ruta de API no disponible | $5,00 (Entrada ≤ 272.000 tokens) / $25,00 (Entrada ≤ 272.000 tokens) |
gpt-6-astrastandard · long context | openai Ruta de API no disponible | $20,00 (Entrada > 272.000 tokens) / $75,00 (Entrada > 272.000 tokens) |
gpt-6-astrastandard · short context | openai Ruta de API no disponible | $10,00 (Entrada ≤ 272.000 tokens) / $50,00 (Entrada ≤ 272.000 tokens) |
gpt-6-astraultrafast · long context | openai Ruta de API no disponible | $120,00 (Entrada > 272.000 tokens) / $450,00 (Entrada > 272.000 tokens) |
gpt-6-astraultrafast · short context | openai Ruta de API no disponible | $60,00 (Entrada ≤ 272.000 tokens) / $300,00 (Entrada ≤ 272.000 tokens) |
openai/gpt-6-astra-prostandard | openrouter | $10,00 / $50,00 |
openai/gpt-6-astra-pro:batchbatch | openrouter | $5,00 / $25,00 |
- · Uso confirmado · OpenAI · official articles · A model guide for the GPT-6 family
- · Enlaces de referencia · OpenAI · official articles
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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
- · Uso confirmado · OpenAI · official articles · How Jump Trading is scaling quant research with ChatGPT
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Jump Trading uses GPT‑6 Astra to take on longer, more ambiguous research problems
- · Enlaces de referencia · OpenAI · official articles
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Jump Trading uses GPT‑6 Astra to take on longer, more ambiguous research problems
- · Enlaces de referencia · OpenAI · official articles
- · Enlaces de referencia · OpenAI · official articles
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Making longer videos possible with GPT‑6 Astra
- · Uso confirmado · OpenAI · official articles · Asana cuts model costs 76x in browser tests with GPT-6.1 Sol
- · Enlaces de referencia · OpenAI · official articles
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We used some of our most capable and aligned models, including our upcoming GPT‑6 Astra Cyber model and an internal frontier model
- · Uso confirmado · 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
- · Uso confirmado · OpenAI · official articles · Retell uses OpenAI models to help power 100M monthly calls
- · Uso confirmado · OpenAI · official articles · Qodo builds context into AI code review with Codex
- · Uso confirmado · OpenAI · official articles · DevRev delivers autonomous self-service with GPT-6.1 Sol
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DevRev’s sales engineers also use GPT‑6 Astra to create demos for the company’s booths at international conferences
- · Uso confirmado · OpenAI · official articles · Merge builds product and business tools with OpenAI technology
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For its own product development, Merge uses GPT‑6 Astra
- · Enlaces de referencia · OpenAI · official articles
- · Enlaces de referencia · OpenAI · official articles
- · Uso confirmado · OpenAI · official articles · Introducing Astra for Law
- · Enlaces de referencia · OpenAI · official articles
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It will appear in the model picker as “GPT‑6 Astra Law” and in the API as gpt-6-astra-law
- · Enlaces de referencia · OpenAI · official articles
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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
- · Entrada de catálogo · GitHub · openai/openai-node · code
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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
- · Uso confirmado · OpenAI · official articles · Cogent and OpenAI build cyber defense factories for enterprises
- · Entrada de catálogo · GitHub · openai/codex · code
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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
Esta referencia en el código no confirma un identificador de modelo en uso.
- · Entrada de catálogo · GitHub · openai/codex · code
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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
- · Entrada de catálogo · GitHub · openai/openai-agents-python · code
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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
Esta referencia en el código no confirma un identificador de modelo en uso.
- · Entrada de catálogo · GitHub · openai/openai-python · code
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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-
- · Entrada de catálogo · GitHub · openai/openai-agents-js · code
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(): 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
- · Entrada de catálogo · Vertex AI · quotas
- · Publicaciones de Alex · Alex Getman
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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.
- · Publicaciones de Alex · familia · 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
- · Enlaces de referencia · 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
- · Publicaciones de 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.
- · Publicaciones de Alex · Alex Getman
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🚨 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
- · Publicaciones de 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
- · Publicaciones de 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.
- · Publicaciones de 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
- · Publicaciones de Alex · Alex Getman
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🚨 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.
- · Publicaciones de Alex · Alex Getman
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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%.
- · Publicaciones de Alex · Alex Getman
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🚨 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.
- · Publicaciones de 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.
- · Publicaciones de 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.
- · Publicaciones de 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
- · Publicaciones de Alex · Alex Getman
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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.
- · Publicaciones de 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.
- · Publicaciones de Alex · Alex Getman
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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.
- · Publicaciones de Alex · Alex Getman
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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
- · Publicaciones de Alex · Alex Getman
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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.
- · Publicaciones de Alex · Alex Getman
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🚨 Plus users got access to GPT-6 Astra
- · Publicaciones de Alex · Alex Getman
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🚨 GPT-6 Astra is out for Pro users
- · Publicaciones de 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.
- · Publicaciones de Alex · Alex Getman
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🚨 GPT-6 Astra is officially out https://openai.com/index/gpt-6-astra/
- · Publicaciones de Alex · Alex Getman
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🚨 GPT-6 Astra is absolutely crushing everyone on the benchmarks
- · Publicaciones de Alex · Alex Getman
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🚨 GPT-6 Astra has been added to the OpenAI API Launch in less than 24 hours
- · Publicaciones de 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.
El plazo previsto no se cumplió; se conserva como mención temprana, no como predicción acertada.
Señales 1
Especificaciones
GPT-6 Astra es un modelo de OpenAI, lanzado el 2026-09-03. La ventana de contexto es de 1.050.000 tokens. El máximo de salida es de 128.000 tokens. El precio por millón de tokens es de $10,00 para la entrada y $50,00 para la salida.
- Ventana de contexto
- 1.050.000
- Salida máxima
- 128.000
- Entrada
- texto · imagen
- Salida
- texto
- Entrada · USD / 1 millón de tokens
- $10,00
- Salida · USD / 1 millón de tokens
- $50,00
- Entrada en caché · USD / 1 millón de tokens
- $1,00
Preguntas
¿Cuál es la ventana de contexto de GPT-6 Astra?
La ventana de contexto es de 1.050.000 tokens. El máximo de salida es de 128.000 tokens.
¿Cuánto cuesta GPT-6 Astra?
El precio por millón de tokens es de $10,00 para la entrada y $50,00 para la salida. La entrada en caché cuesta $1,00 por millón.
¿Cuándo se lanzó GPT-6 Astra?
El 2026-09-03.