Alex Getmanisyarat awal AI
MS

GPT-5.6 Terra

OpenAI

Dikeluarkan Dikemas kini
Tetingkap konteks
1M
1,050,000 token
Keluaran maksimum
128K
128,000 token
Input / Output
teks, imej → teks

Harga API

USD / 1 juta token

InputOutputInput dalam cache
  • $2.00
openrouter
  • $12.00
openrouter
  • $0.20
openrouter
Kira kos penggunaan anda

Garis masa

  1. · Ketersediaan API · pautan bukti
Harga input / output · USD / 1 juta token
ModelPautan buktiHarga input / output
gpt-5.6-terra
batch · long context
openai
Laluan API tidak tersedia
$2.00 (Input > 272,000 token) / $9.00 (Input > 272,000 token)
gpt-5.6-terra
batch · short context
openai
Laluan API tidak tersedia
$1.00 (Input ≤ 272,000 token) / $6.00 (Input ≤ 272,000 token)
gpt-5.6-terra
fast · long context
openai
Laluan API tidak tersedia
$8.00 (Input > 272,000 token) / $36.00 (Input > 272,000 token)
gpt-5.6-terra
fast · short context
openai
Laluan API tidak tersedia
$4.00 (Input ≤ 272,000 token) / $24.00 (Input ≤ 272,000 token)
gpt-5.6-terra
flex · long context
openai
Laluan API tidak tersedia
$2.00 (Input > 272,000 token) / $9.00 (Input > 272,000 token)
gpt-5.6-terra
flex · short context
openai
Laluan API tidak tersedia
$1.00 (Input ≤ 272,000 token) / $6.00 (Input ≤ 272,000 token)
gpt-5.6-terra
standard · long context
openai
Laluan API tidak tersedia
$4.00 (Input > 272,000 token) / $18.00 (Input > 272,000 token)
gpt-5.6-terra
standard · short context
openai
Laluan API tidak tersedia
$2.00 (Input ≤ 272,000 token) / $12.00 (Input ≤ 272,000 token)
openai/gpt-5.6-terra-pro
standard
openrouter$2.00 / $12.00
openai/gpt-5.6-terra-pro:batch
batch
openrouter$1.00 / $6.00
  1. · Penggunaan disahkan · OpenAI · official articles · Retell uses OpenAI models to help power 100M monthly calls
    Petikan
    After a call, Retell uses GPT‑5.6 Terra to analyze the transcript and extract outcomes and other data
  2. · Penggunaan disahkan · OpenAI · official articles · How we detect frontier model misalignment
  3. · Entri katalog · GitHub · openai/openai-node · code
    Petikan
    ttps://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' | 'gpt-5-chat-latest' | 'gpt-4.1' | 'gp
  4. · Entri katalog · GitHub · openai/codex · code
    Petikan
    cfg = ConfigToml { agents: Some(AgentsToml { enabled: Some(false), max_depth: Some(2), default_subagent_model: Some("gpt-5.6-terra".to_string()), default_subagent_reasoning_effort: Some(ReasoningEffort::High), interrupt_message: Some(false), ..Default::default() }), ..Default::default() }; let config = Config::load_from_base_config_with_overrides( cfg, ConfigOverrides::d

    Rujukan dalam kod ini tidak mengesahkan pengecam model yang digunakan.

  5. · Entri katalog · GitHub · openai/codex · code
    Petikan
    se; use codex_protocol::openai_models::WebSearchToolType; use 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_
  6. · Entri katalog · GitHub · openai/openai-agents-python · code
    Petikan
    "gpt-5.4-pro", "gpt-5.4-pro-2026-03-05", "gpt-5.5", "gpt-5.5-2026-04-23", "gpt-5.5-pro", "gpt-5.5-pro-2026-04-23", "gpt-5.6", "gpt-5.6-sol", "gpt-5.6-terra", "gpt-5.6-luna", "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", ), 1_047_576, ), **_model_context_windows( ( "gpt-5", "gpt-5-2025-08-07", "gpt-5-codex", "gpt-5-mini", "gpt-5-mini-2025-08-07", "gpt-5-nano", "gpt-5-nano-2025-08-07", "gpt-5-pro", "gpt-5-pro-2025-10-06", "gpt-5.1", "gpt-5.1-2025-11-13", "gpt-
  7. · Entri katalog · GitHub · openai/openai-python · code
    Petikan
    gth 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", "gpt-5", "gpt-5-mini",
  8. · Entri katalog · GitHub · openai/openai-agents-js · code
    Petikan
    .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', 'gpt-5.4-nano', ]); const SANDBOX_CONTEXT_WINDOWS_200K = new
  9. · Siaran Alex · Alex Getman
    Petikan
    Jev is out, a new AI model from startup TypeSafe AI It is built for fast decision making inside apps. You give it context and possible actions, and it picks the best option with probability and confidence. TypeSafe says Jev reaches GPT 5.6 Terra level on these tasks, responds in 70 to 500ms, and costs $0.042 per 1M input tokens. Output is free. It can route support tickets, score risk, and check AI agent actions.
  10. · Siaran Alex · Alex Getman
    Petikan
    🚨 Google released Gemini 3.8 Flash • still $0.75 per 1M input tokens • at the same price, it is noticeably stronger than Gemini 3.7 Flash across almost the entire table • especially big gains in autonomous computer use and complex scientific tasks • beats GPT 5.6 Terra, a model in the same class, on almost every benchmark
  11. · Siaran Alex · Alex Getman
    Petikan
    ⚡️ Qwen 3.8 27B beat GPT 5.6 Terra This happened in the AA Agentic Index, a benchmark that tests how well models handle agentic tasks. And you can run Qwen 3.8 27B locally on a single RTX 3090.
  12. · Siaran Alex · Alex Getman
    Petikan
    Very few people know this, but Muse Spark 1.2 might be the best value model on the market right now. Its intelligence is around GPT-5.6 Terra. But if you use Muse Code and agree to code analysis through the Contributor tier, the price drops 10–20x. So you basically get Terra-level intelligence at Luna-level cost.
  13. · Siaran Alex · Alex Getman
    Petikan
    ⚡️ 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.
  14. · Siaran Alex · Alex Getman
    Petikan
    ⚡️ RELEASE: KIMI K3 Moonshot just dropped its new flagship: 2.8T parameters, a 1M-token context window, native vision, and a focus on large projects, coding, games, and 3D. Full weights are expected in the next few days. API: $3 / $15 per million input/output tokens. Pricing-wise, that puts it around Sonnet 5 or GPT-5.6 Terra, while Moonshot’s own benchmarks have it taking shots at Opus 4.8 and Sol. So basically: Opus-class performance at Sonnet pricing. You can already try it for free on the Kimi website or through Kimi Code CLI.
  15. · Siaran Alex · Alex Getman
    Petikan
    Grok 4.5: a new competitor to GPT and Claude Posting this a little late, but I prepared something interesting. Grok 4.5 is temporarily available to test for free in Grok Build and Cursor. The model runs at around 80 tokens per second, supports a context window of up to 500,000 tokens, and costs $2 per million input tokens and $6 per million output tokens. According to Musk, Grok 4.5 was trained from scratch on SpaceXAI’s own foundation and is not built on top of Kimi like Composer. In terms of quality, Grok 4.5 comes close to GPT-5.6 Terra, while its pricing is closer to Luna. Among Anthropic models, it sits between Haiku and Sonnet, making it especially attractive in terms of price-to-pe

Isyarat 2

Spesifikasi

GPT-5.6 Terra ialah model daripada OpenAI, dikeluarkan pada 2026-07-09. Tetingkap konteks ialah 1,050,000 token. Keluaran maksimum ialah 128,000 token. Harganya ialah $2.00 bagi sejuta token input dan $12.00 bagi sejuta token output.

Tetingkap konteks
1,050,000
Keluaran maksimum
128,000
Input
teks · imej
Output
teks
Input · USD / 1 juta token
$2.00
Output · USD / 1 juta token
$12.00
Input dalam cache · USD / 1 juta token
$0.20

Soalan

Apakah tetingkap konteks GPT-5.6 Terra?

Tetingkap konteks ialah 1,050,000 token. Keluaran maksimum ialah 128,000 token.

Berapakah harga GPT-5.6 Terra?

Harganya ialah $2.00 bagi sejuta token input dan $12.00 bagi sejuta token output. Input dalam cache berharga $0.20 bagi sejuta token.

Bilakah GPT-5.6 Terra dikeluarkan?

Pada 2026-07-09.