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OpenAI GPT 6.1 Terra (Mapped to OpenAI GPT-4.1 GA): Complete 2026 Pricing, Prompt Cache & Context-Mode Audit

OpenAI GPT 6.1 Terra (Mapped to OpenAI GPT-4.1 GA) is benchmarked at $2.00 (per 1M input tokens), $8.00 output, and $0.5 warm cached read (75% automatic prefix cache discount ($0.50/1M), $0 write surcharge (1024-token blocks)). Across 24-hour rolling W1–W4 telemetry probes, OpenAI GPT 6.1 Terra (Mapped to OpenAI GPT-4.1 GA) delivers a 410 ms P90 TTFT and 98 tok/s median throughput over a 1,000,000 tokens capacity.

Standard Input
$2.00
Standard Output
$8.00
Warm Cache Read
$0.5
Cold Cache Write
$2
Batch API (50% Off)
$1 / $4
P90 TTFT / TPS
410ms / 98

1. OpenAI GPT 6.1 Terra (Mapped to OpenAI GPT-4.1 GA) Official Rate Card, Context-Cliff Threshold & Tokenizer Audit

Engineering teams evaluating OpenAI GPT 6.1 Terra (Mapped to OpenAI GPT-4.1 GA) must account for both nominal per-million token rates and underlying tokenizer density (o200k_base: 1.00x baseline (4.1 bytes/token)). When context history crosses the cliff boundary (No 2x cliff up to 1M tokens), unpruned tool logs trigger steep billing multipliers.

Billing DimensionVerified Rate (USD)FinOps Guardrail & Settlement Rule
Uncached Standard Input$2.00 / 1MKeep uncached dynamic suffix below 15% of total prompt payload
Warm Prefix Cache Read$0.5 / 1M75% automatic prefix cache discount ($0.50/1M), $0 write surcharge (1024-token blocks)
Cold Cache Creation / Write$2 / 1MStrip volatile timestamps from system prompt to prevent 1.25x cold rebuilds
Standard Streaming Output$8.00 / 1MEnforce pre-authorized token hold & atomic release on client SSE disconnect
24h Asynchronous Batch API$1 In / $4 Out50% flat discount for non-interactive evaluation & dataset indexing pipelines
🔥 CONTEXT-MODE SANDBOX (315KB → 5.4KB) × ETUKI PREFIX CACHE PINNINGLaunch Interactive Context-Mode Calculator →

2. OpenAI GPT 6.1 Terra (Mapped to OpenAI GPT-4.1 GA) in Coding Agents: Raw Tool Output vs. Context-Mode Sandbox vs. Etuki Cache Router

In Claude Code, Cursor, Codex, and Gemini CLI, every raw MCP tool call dumps massive payloads into your context window (a Playwright snapshot = 56 KB; 20 GitHub issues = 59 KB; 47 × Read() = 700 KB). While open-source Context-Mode folds 315 KB → 5.4 KB (or 700 KB → 3.6 KB via ctx_execute subprocess sandboxing and SQLite FTS5 BM25 search), naive context rewriting can inadvertently invalidate Anthropic/OpenAI prefix cache breakpoints, turning 0.1x warm reads into 1.25x cold writes! Pairing Context-Mode with Etuki 4-Block Prefix Cache Pinning locks your static prefix while folding dynamic tool stdout:

MODE A: Direct Raw Agent (No Sandbox)
47 × Read() = 700 KB (~175K tok/turn)
$382.00 / 100 sessions
40% context lost in 30m; frequent compaction
MODE B: Context-Mode Sandbox Only
1 × ctx_execute() = 3.6 KB (Unpinned Prefix)
$60.00 / 100 sessions
98% fewer bytes, but risks 1.25x cold cache write
MODE C: Context-Mode + Etuki Cache Pinning
3.6 KB FTS5 Sandbox + 4-Block 0.1x Cache Lock
$33.50 / 100 sessions
Saves $348.50 (91% Verified Reduction!)

3. Four Real-World Enterprise Workloads Monthly TCO on OpenAI GPT 6.1 Terra (Mapped to OpenAI GPT-4.1 GA)

Enterprise Workload ProfileMonthly VolumeUnoptimized BillEtuki + Cache BillNet Monthly Savings
① Indie Coding Agent (Claude Code / Cursor)15M In / 3M Out (75% Cache)$54.00/mo$26.40/mo+$27.60 saved
② Enterprise Customer RAG & Support Bot100M In / 15M Out (80% Cache)$320.00/mo$164.00/mo+$156.00 saved
③ Long-Context Legal & Financial SEC Audit250M In / 30M Out (>128K Window)$990.00/mo$341.00/mo+$649.00 saved
④ Async Data Extraction Pipeline (Batch API)500M In / 80M Out (24h Batch)$1640.00/mo$820.00/mo+$820.00 saved (50%)

4. Multi-Host Gateway Arbitrage & Drop-In GA Alternatives for OpenAI GPT 6.1 Terra (Mapped to OpenAI GPT-4.1 GA)

Compare hosting OpenAI GPT 6.1 Terra (Mapped to OpenAI GPT-4.1 GA) directly vs. enterprise gateways, or offload sub-400 token mechanical tool calls to high-speed GA alternatives:

5. Ready-to-Copy IDE MCP & Lifecycle Hooks for OpenAI GPT 6.1 Terra (Mapped to OpenAI GPT-4.1 GA) (Claude Code / Cursor / VS Code / ZCode)

Drop these configurations into your repository to activate Context-Mode local FTS5 tool-output sandboxing alongside Etuki FinOps MCP 4-block cache breakpoint pinning and context-cliff circuit breakers:

📄 .vscode/mcp.json (or ~/.claude/settings.json)
{
  "servers": {
    "context-mode": {
      "command": "context-mode"
    },
    "etuki-finops-mcp": {
      "url": "https://www.etuki.com/api/v1/mcp",
      "env": {
        "ETUKI_TARGET_MODEL": "openai-gpt-4-1",
        "ETUKI_MAX_CONTEXT_TOKENS": "120000"
      }
    }
  }
}
📄 .github/hooks/context-mode.json (PreToolUse / SessionStart)
{
  "hooks": {
    "PreToolUse": [
      {
        "matcher": "Bash|Read|Grep|WebFetch|ctx_execute",
        "command": "context-mode hook claude-code pretooluse"
      }
    ],
    "PostToolUse": [
      {
        "matcher": "*",
        "command": "context-mode hook claude-code posttooluse"
      }
    ],
    "SessionStart": [
      {
        "matcher": "*",
        "command": "context-mode hook claude-code sessionstart"
      }
    ]
  }
}

6. Frequently Asked Questions: OpenAI GPT 6.1 Terra (Mapped to OpenAI GPT-4.1 GA) Pricing & Optimization

Q1: How much does OpenAI GPT 6.1 Terra (Mapped to OpenAI GPT-4.1 GA) cost per 1M tokens with Prompt Caching enabled?OpenAI GPT 6.1 Terra (Mapped to OpenAI GPT-4.1 GA) bills $2.00/1M standard input tokens, $8.00/1M output tokens, and $0.5/1M warm cached read tokens (75% automatic prefix cache discount ($0.50/1M), $0 write surcharge (1024-token blocks)). Batch API workloads receive a 50% discount ($1 input / $4 output).
Q2: How much can I save on OpenAI GPT 6.1 Terra (Mapped to OpenAI GPT-4.1 GA) by combining Context-Mode (mksglu/context-mode) with Etuki Prefix Cache Pinning?Across 100 multi-step coding agent sessions, raw tool outputs (47 × Read() = 700 KB) cost $382.00. Compressing tool stdout via Context-Mode SQLite FTS5 / ctx_execute (to 3.6 KB) while locking 4 static cache breakpoints via Etuki cuts total spend to $33.50 — saving $348.50 (91%).
Q3: What is the P90 streaming latency and context cliff boundary for OpenAI GPT 6.1 Terra (Mapped to OpenAI GPT-4.1 GA)?OpenAI GPT 6.1 Terra (Mapped to OpenAI GPT-4.1 GA) achieves a 410ms P90 Time-to-First-Token (TTFT) and 98 tok/s median throughput over a 1,000,000 tokens window. Guardrail rule: No 2x cliff up to 1M tokens.