GPT-5.4: Oppføring i katalog
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Engelsk original

OpenAI
| Modell | Dokumentasjonslenker | Pris for inndata / utdata |
|---|---|---|
gpt-5.4batch · long context | openai API-ruten er ikke tilgjengelig | $2,50 (Inndata > 272 000 tokener) / $11,25 (Inndata > 272 000 tokener) |
gpt-5.4batch · short context | openai API-ruten er ikke tilgjengelig | $1,25 (Inndata ≤ 272 000 tokener) / $7,50 (Inndata ≤ 272 000 tokener) |
gpt-5.4fast · short context | openai API-ruten er ikke tilgjengelig | $5,00 (Inndata ≤ 272 000 tokener) / $30,00 (Inndata ≤ 272 000 tokener) |
gpt-5.4flex · long context | openai API-ruten er ikke tilgjengelig | $2,50 (Inndata > 272 000 tokener) / $11,25 (Inndata > 272 000 tokener) |
gpt-5.4flex · short context | openai API-ruten er ikke tilgjengelig | $1,25 (Inndata ≤ 272 000 tokener) / $7,50 (Inndata ≤ 272 000 tokener) |
gpt-5.4standard · long context | openai API-ruten er ikke tilgjengelig | $5,00 (Inndata > 272 000 tokener) / $22,50 (Inndata > 272 000 tokener) |
gpt-5.4standard · short context | openai API-ruten er ikke tilgjengelig | $2,50 (Inndata ≤ 272 000 tokener) / $15,00 (Inndata ≤ 272 000 tokener) |
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
Denne referansen i koden bekrefter ikke en modellidentifikator i bruk.
, ) .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"), ("
Denne referansen i koden bekrefter ikke en modellidentifikator i bruk.
, 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
Denne referansen i koden bekrefter ikke en modellidentifikator i bruk.
-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 er en modell fra OpenAI, lansert 2026-03-05. Kontekstvinduet er 1 050 000 tokener. Maksimal utdatalengde er 128 000 tokener.
Kontekstvinduet er 1 050 000 tokener. Maksimal utdatalengde er 128 000 tokener.
Den 2026-03-05.