GPT-5.4: Entrée du catalogue
Confirmé6 liens de référence
Original en anglais

OpenAI
| Modèle | Liens de référence | Prix entrée/sortie |
|---|---|---|
gpt-5.4batch · long context | openai Route API indisponible | $2,50 (Entrée > 272 000 jetons) / $11,25 (Entrée > 272 000 jetons) |
gpt-5.4batch · short context | openai Route API indisponible | $1,25 (Entrée ≤ 272 000 jetons) / $7,50 (Entrée ≤ 272 000 jetons) |
gpt-5.4fast · short context | openai Route API indisponible | $5,00 (Entrée ≤ 272 000 jetons) / $30,00 (Entrée ≤ 272 000 jetons) |
gpt-5.4flex · long context | openai Route API indisponible | $2,50 (Entrée > 272 000 jetons) / $11,25 (Entrée > 272 000 jetons) |
gpt-5.4flex · short context | openai Route API indisponible | $1,25 (Entrée ≤ 272 000 jetons) / $7,50 (Entrée ≤ 272 000 jetons) |
gpt-5.4standard · long context | openai Route API indisponible | $5,00 (Entrée > 272 000 jetons) / $22,50 (Entrée > 272 000 jetons) |
gpt-5.4standard · short context | openai Route API indisponible | $2,50 (Entrée ≤ 272 000 jetons) / $15,00 (Entrée ≤ 272 000 jetons) |
GPT‑5.4 was tested with a longer, updated blocklist
GPT‑5.4 could not
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' | 'gpt-4.1-nano' | 'gpt-4.1-2025-04-14' | 'gpt-4.1-mini-
ope fallback migration metadata // to the owning provider, since other providers may still support the same model slug. let (target_model, current_name, target_name) = match (model_provider_id, model) { (OPENAI_PROVIDER_ID, "gpt-5.4") => ("gpt-6-sol", "GPT-5.4", "GPT-6 Sol"), (AMAZON_BEDROCK_PROVIDER_ID, "openai.gpt-5.4") => ( "openai.gpt-6-sol", "GPT-5.4 on Amazon Bedrock", "GPT-6 Sol on Amazon Bedrock", ), (OPENAI_PROVIDER_ID, "gpt-5.4-mini") => ("gpt-6-luna", "GPT-5.4 Mini", "GPT-6 Luna"), _ => return None, }; let availability = if model == "openai.gpt-5.4" { "no longer offered in Codex" } else { "no longer available" }; Some(ModelUpgrade { id: target_model.to_string(), migration_config_key: model.to_string(), model_link: None,
eturn isinstance(model, str) and model.startswith("computer-use-preview") @classmethod def _is_ga_computer_model(cls, model: str | ChatModel | None) -> bool: return isinstance(model, str) and ( model.startswith("gpt-5.4") or model.startswith("gpt-5.5") ) @classmethod def resolve_computer_tool_model( cls, *, request_model: str | ChatModel | None, tools: Sequence[Tool] | None, ) -> str | ChatModel | None: if not cls._has_computer_tool(tools): return None return request_model @classmethod def _should_use_preview_computer_tool( cls, *, model: str | ChatModel | None, tool_choice: Literal["auto", "required", "none"] | str | MCPToolChoice | None, ) -> bool: # Choose the computer tool wire shape from the effective request m
root.join(".mcp.json"), r#"{"mcpServers":{"repository-server":{"command":"repository-server"}}}"#, )?; std::fs::write(&global_config, "model = \"gpt-5.4\"\n")?; let home_dir = codex_home.path().display().to_string(); let mut mcp = TestAppServer::builder() .with_codex_home(codex_home.path()) .without_auto_env() .with_env_overrides(&[("HOME", Some(home_dir.as_str()))]) .build_initialized_with_timeout(DEFAULT_TIMEOUT) .awa
Cette référence dans le code ne confirme pas un identifiant de modèle utilisé.
, ) .expect("in-memory metrics client") } #[test] fn extension_metrics_preserve_session_metadata_tags() { let metrics = test_metrics_client(); let session_telemetry = SessionTelemetry::new( ThreadId::new(), "gpt-5.4", "gpt-5.4", /*account_id*/ None, /*account_email*/ None, Some(TelemetryAuthMode::Chatgpt), "test_originator".to_string(), /*log_user_prompts*/ false, "tty".to_string(), SessionSource::Cli, ) .with_metrics_service_name("test_service") .with_metrics(metrics.clone()); let extension_metrics = super::extension_metrics::from_session_telemetry(session_telemetry); extension_metrics.histogram( "codex.test.extension", /*value*/ 7, &[ ("component", "skills"), ("app.version", "extension-version"), ("
Cette référence dans le code ne confirme pas un identifiant de modèle utilisé.
, history[:], False) def _strip_orphaned_assistant_ids( items: list[TResponseInputItem], ) -> list[TResponseInputItem]: """Remove ``id`` from assistant messages when their paired reasoning items are missing. Some models (e.g. gpt-5.4) return compacted output that retains assistant message IDs even after stripping the reasoning items those IDs reference. Sending these orphaned IDs back to ``responses.create`` causes a 400 error because the API expects the paired reasoning item for each assistant message ID. This function detects and removes those orphaned IDs so the compacted history can be used safely. """ if not items: return items has_reasoning = any( isinstance(item, dict) and item.get("type") == "reasoning" for item in items ) if has_reasoning: return items cleaned: list[TResponseInputIt
Cette référence dans le code ne confirme pas un identifiant de modèle utilisé.
-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-n
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 Set([ 'codex-mini-latest',
GPT‑5.4 Thinking also has improved context window management that supports its ability to think for longer
Introducing GPT-5.4 in Codex GPT-5.4 is now available in Codex as OpenAI's most capable and efficient frontier model for professional work
GPT‑5.4 Thinking also has improved context window management that supports its ability to think for longer
#44930 Embed friendly instructions in bundled GPT-5.4 and GPT-5.5
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-5.4 est un modèle de OpenAI, sorti le 2026-03-05. La fenêtre de contexte est de 1 050 000 jetons. La sortie est limitée à 128 000 jetons.
La fenêtre de contexte est de 1 050 000 jetons. La sortie est limitée à 128 000 jetons.
Le 2026-03-05.