GPT-5.6 Terra
Proprietary CommercialDeveloped by OpenAI · Released 2025-01-01
What are the token costs and operational benchmarks for GPT-5.6 Terra?
Architectural Overview
Frontier foundation model developed by OpenAI featuring Balanced Production Workhorse MoE architecture.
Optimal Production Use Cases
Mainstream production enterprise workflows, high-throughput developer copilots, and structured data synthesis.
Interactive Monthly Token Economics & ROI Forecaster
Model your expected production workload across prompt (input) and completion (output) tokens.
Estimated Monthly Spend
$1.5/1M in · $6/1M out
$0.18/1M in · $0.72/1M out
Head-to-Head Comparisons Involving GPT-5.6 Terra
GPT-5.6 Terra vs Claude 3.5 Haiku
Claude 3.5 Haiku is 46.7% cheaper for input tokens ($0.80 vs. $1.50 per 1M tokens) and $4.00 vs. $6.00 for output tokens (1.9x cost difference). In terms of operational performance, Claude 3.5 Haiku delivers faster response latency with 140ms TTFT (70ms faster than GPT-5.6 Terra). GPT-5.6 Terra leads coding benchmarks at 65.4% SWE-bench vs. 40.6% for Claude 3.5 Haiku.
GPT-5.6 Terra vs Claude 3.5 Sonnet
GPT-5.6 Terra is 50.0% cheaper for input tokens ($1.50 vs. $3.00 per 1M tokens) and $6.00 vs. $15.00 for output tokens (2.0x cost difference). In terms of operational performance, GPT-5.6 Terra delivers faster response latency with 210ms TTFT (110ms faster than Claude 3.5 Sonnet). GPT-5.6 Terra leads coding benchmarks at 65.4% SWE-bench vs. 63.7% for Claude 3.5 Sonnet.
GPT-5.6 Terra vs Claude 3.7 Sonnet
GPT-5.6 Terra is 50.0% cheaper for input tokens ($1.50 vs. $3.00 per 1M tokens) and $6.00 vs. $15.00 for output tokens (2.0x cost difference). In terms of operational performance, GPT-5.6 Terra delivers faster response latency with 210ms TTFT (440ms faster than Claude 3.7 Sonnet). Claude 3.7 Sonnet leads coding benchmarks at 70.3% SWE-bench vs. 65.4% for GPT-5.6 Terra.
GPT-5.6 Terra vs Claude Opus 5
GPT-5.6 Terra is 70.0% cheaper for input tokens ($1.50 vs. $5.00 per 1M tokens) and $6.00 vs. $25.00 for output tokens (3.3x cost difference). In terms of operational performance, GPT-5.6 Terra delivers faster response latency with 210ms TTFT (130ms faster than Claude Opus 5). Claude Opus 5 leads coding benchmarks at 82.4% SWE-bench vs. 65.4% for GPT-5.6 Terra.
GPT-5.6 Terra vs Codestral 25.01
Codestral 25.01 is 80.0% cheaper for input tokens ($0.30 vs. $1.50 per 1M tokens) and $0.90 vs. $6.00 for output tokens (5.0x cost difference). In terms of operational performance, Codestral 25.01 delivers faster response latency with 150ms TTFT (60ms faster than GPT-5.6 Terra). GPT-5.6 Terra leads coding benchmarks at 65.4% SWE-bench vs. 44.2% for Codestral 25.01.
GPT-5.6 Terra vs Composer 2.5
GPT-5.6 Terra is 16.7% cheaper for input tokens ($1.50 vs. $1.80 per 1M tokens) and $6.00 vs. $7.20 for output tokens (1.2x cost difference). In terms of operational performance, Composer 2.5 delivers faster response latency with 180ms TTFT (30ms faster than GPT-5.6 Terra). Composer 2.5 leads coding benchmarks at 74.6% SWE-bench vs. 65.4% for GPT-5.6 Terra.
GPT-5.6 Terra vs DeepSeek-R1
DeepSeek-R1 is 63.3% cheaper for input tokens ($0.55 vs. $1.50 per 1M tokens) and $2.19 vs. $6.00 for output tokens (2.7x cost difference). In terms of operational performance, GPT-5.6 Terra delivers faster response latency with 210ms TTFT (1590ms faster than DeepSeek-R1). GPT-5.6 Terra leads coding benchmarks at 65.4% SWE-bench vs. 49.2% for DeepSeek-R1.
GPT-5.6 Terra vs DeepSeek-V3
DeepSeek-V3 is 90.7% cheaper for input tokens ($0.14 vs. $1.50 per 1M tokens) and $0.28 vs. $6.00 for output tokens (10.7x cost difference). In terms of operational performance, GPT-5.6 Terra delivers faster response latency with 210ms TTFT (130ms faster than DeepSeek-V3). GPT-5.6 Terra leads coding benchmarks at 65.4% SWE-bench vs. 42.0% for DeepSeek-V3.
GPT-5.6 Terra vs DeepSeek-V4 Flash
DeepSeek-V4 Flash is 90.7% cheaper for input tokens ($0.14 vs. $1.50 per 1M tokens) and $0.56 vs. $6.00 for output tokens (10.7x cost difference). In terms of operational performance, DeepSeek-V4 Flash delivers faster response latency with 150ms TTFT (60ms faster than GPT-5.6 Terra). GPT-5.6 Terra leads coding benchmarks at 65.4% SWE-bench vs. 62.4% for DeepSeek-V4 Flash.
GPT-5.6 Terra vs Fable 5
GPT-5.6 Terra is 25.0% cheaper for input tokens ($1.50 vs. $2.00 per 1M tokens) and $6.00 vs. $8.00 for output tokens (1.3x cost difference). In terms of operational performance, GPT-5.6 Terra delivers faster response latency with 210ms TTFT (30ms faster than Fable 5). GPT-5.6 Terra leads coding benchmarks at 65.4% SWE-bench vs. 58.0% for Fable 5.
GPT-5.6 Terra vs Gemini 2.0 Flash
Gemini 2.0 Flash is 93.3% cheaper for input tokens ($0.10 vs. $1.50 per 1M tokens) and $0.40 vs. $6.00 for output tokens (15.0x cost difference). In terms of operational performance, GPT-5.6 Terra delivers faster response latency with 210ms TTFT (170ms faster than Gemini 2.0 Flash). GPT-5.6 Terra leads coding benchmarks at 65.4% SWE-bench vs. 48.0% for Gemini 2.0 Flash.
GPT-5.6 Terra vs Gemini 3.7 Flash
Gemini 3.7 Flash is 94.7% cheaper for input tokens ($0.08 vs. $1.50 per 1M tokens) and $0.32 vs. $6.00 for output tokens (18.8x cost difference). In terms of operational performance, Gemini 3.7 Flash delivers faster response latency with 75ms TTFT (135ms faster than GPT-5.6 Terra). Gemini 3.7 Flash leads coding benchmarks at 68.2% SWE-bench vs. 65.4% for GPT-5.6 Terra.
GPT-5.6 Terra vs GLM 5.3 Flash
GLM 5.3 Flash is 90.0% cheaper for input tokens ($0.15 vs. $1.50 per 1M tokens) and $0.50 vs. $6.00 for output tokens (10.0x cost difference). In terms of operational performance, GLM 5.3 Flash delivers faster response latency with 130ms TTFT (80ms faster than GPT-5.6 Terra). GPT-5.6 Terra leads coding benchmarks at 65.4% SWE-bench vs. 54.2% for GLM 5.3 Flash.
GPT-5.6 Terra vs OpenAI GPT-4o
GPT-5.6 Terra is 40.0% cheaper for input tokens ($1.50 vs. $2.50 per 1M tokens) and $6.00 vs. $10.00 for output tokens (1.7x cost difference). In terms of operational performance, GPT-5.6 Terra delivers faster response latency with 210ms TTFT (70ms faster than OpenAI GPT-4o). GPT-5.6 Terra leads coding benchmarks at 65.4% SWE-bench vs. 38.8% for OpenAI GPT-4o.
GPT-5.6 Terra vs GPT-5.6 Luna
GPT-5.6 Luna is 88.0% cheaper for input tokens ($0.18 vs. $1.50 per 1M tokens) and $0.72 vs. $6.00 for output tokens (8.3x cost difference). In terms of operational performance, GPT-5.6 Luna delivers faster response latency with 90ms TTFT (120ms faster than GPT-5.6 Terra). GPT-5.6 Terra leads coding benchmarks at 65.4% SWE-bench vs. 48.5% for GPT-5.6 Luna.
GPT-5.6 Terra vs GPT-5.6 Sol
GPT-5.6 Terra is 81.2% cheaper for input tokens ($1.50 vs. $8.00 per 1M tokens) and $6.00 vs. $32.00 for output tokens (5.3x cost difference). In terms of operational performance, GPT-5.6 Terra delivers faster response latency with 210ms TTFT (210ms faster than GPT-5.6 Sol). GPT-5.6 Sol leads coding benchmarks at 79.5% SWE-bench vs. 65.4% for GPT-5.6 Terra.
GPT-5.6 Terra vs Grok 3
GPT-5.6 Terra is 50.0% cheaper for input tokens ($1.50 vs. $3.00 per 1M tokens) and $6.00 vs. $15.00 for output tokens (2.0x cost difference). In terms of operational performance, GPT-5.6 Terra delivers faster response latency with 210ms TTFT (640ms faster than Grok 3). GPT-5.6 Terra leads coding benchmarks at 65.4% SWE-bench vs. 58.5% for Grok 3.
GPT-5.6 Terra vs xAI Grok 4.6
GPT-5.6 Terra is 25.0% cheaper for input tokens ($1.50 vs. $2.00 per 1M tokens) and $6.00 vs. $6.00 for output tokens (1.3x cost difference). In terms of operational performance, GPT-5.6 Terra delivers faster response latency with 210ms TTFT (70ms faster than xAI Grok 4.6). xAI Grok 4.6 leads coding benchmarks at 76.8% SWE-bench vs. 65.4% for GPT-5.6 Terra.
GPT-5.6 Terra vs Llama 3.3 70B Instruct
Llama 3.3 70B Instruct is 88.0% cheaper for input tokens ($0.18 vs. $1.50 per 1M tokens) and $0.40 vs. $6.00 for output tokens (8.3x cost difference). In terms of operational performance, GPT-5.6 Terra delivers faster response latency with 210ms TTFT (210ms faster than Llama 3.3 70B Instruct). GPT-5.6 Terra leads coding benchmarks at 65.4% SWE-bench vs. 38.8% for Llama 3.3 70B Instruct.
GPT-5.6 Terra vs Mistral Large 2
GPT-5.6 Terra is 25.0% cheaper for input tokens ($1.50 vs. $2.00 per 1M tokens) and $6.00 vs. $6.00 for output tokens (1.3x cost difference). In terms of operational performance, GPT-5.6 Terra delivers faster response latency with 210ms TTFT (340ms faster than Mistral Large 2). GPT-5.6 Terra leads coding benchmarks at 65.4% SWE-bench vs. 39.0% for Mistral Large 2.
GPT-5.6 Terra vs OpenAI o1
GPT-5.6 Terra is 90.0% cheaper for input tokens ($1.50 vs. $15.00 per 1M tokens) and $6.00 vs. $60.00 for output tokens (10.0x cost difference). In terms of operational performance, GPT-5.6 Terra delivers faster response latency with 210ms TTFT (640ms faster than OpenAI o1). GPT-5.6 Terra leads coding benchmarks at 65.4% SWE-bench vs. 48.9% for OpenAI o1.
GPT-5.6 Terra vs o3-mini
o3-mini is 26.7% cheaper for input tokens ($1.10 vs. $1.50 per 1M tokens) and $4.40 vs. $6.00 for output tokens (1.4x cost difference). In terms of operational performance, GPT-5.6 Terra delivers faster response latency with 210ms TTFT (990ms faster than o3-mini). GPT-5.6 Terra leads coding benchmarks at 65.4% SWE-bench vs. 49.3% for o3-mini.
GPT-5.6 Terra vs Microsoft Phi-4 (14B)
Microsoft Phi-4 (14B) is 92.0% cheaper for input tokens ($0.12 vs. $1.50 per 1M tokens) and $0.36 vs. $6.00 for output tokens (12.5x cost difference). In terms of operational performance, Microsoft Phi-4 (14B) delivers faster response latency with 110ms TTFT (100ms faster than GPT-5.6 Terra). GPT-5.6 Terra leads coding benchmarks at 65.4% SWE-bench vs. 42.1% for Microsoft Phi-4 (14B).
GPT-5.6 Terra vs Qwen 2.5 72B Instruct
Qwen 2.5 72B Instruct is 76.7% cheaper for input tokens ($0.35 vs. $1.50 per 1M tokens) and $0.40 vs. $6.00 for output tokens (4.3x cost difference). In terms of operational performance, GPT-5.6 Terra delivers faster response latency with 210ms TTFT (210ms faster than Qwen 2.5 72B Instruct). GPT-5.6 Terra leads coding benchmarks at 65.4% SWE-bench vs. 44.0% for Qwen 2.5 72B Instruct.
GPT-5.6 Terra vs Qwen 2.5 Max
Qwen 2.5 Max is 81.3% cheaper for input tokens ($0.28 vs. $1.50 per 1M tokens) and $0.84 vs. $6.00 for output tokens (5.4x cost difference). In terms of operational performance, GPT-5.6 Terra delivers faster response latency with 210ms TTFT (270ms faster than Qwen 2.5 Max). GPT-5.6 Terra leads coding benchmarks at 65.4% SWE-bench vs. 44.2% for Qwen 2.5 Max.
GPT-5.6 Terra vs Qwen 3.8 Flash Next
Qwen 3.8 Flash Next is 92.0% cheaper for input tokens ($0.12 vs. $1.50 per 1M tokens) and $0.48 vs. $6.00 for output tokens (12.5x cost difference). In terms of operational performance, Qwen 3.8 Flash Next delivers faster response latency with 120ms TTFT (90ms faster than GPT-5.6 Terra). GPT-5.6 Terra leads coding benchmarks at 65.4% SWE-bench vs. 56.8% for Qwen 3.8 Flash Next.
Frequently Asked Questions & Query Fan-Out
How much does GPT-5.6 Terra cost per 1M tokens?
GPT-5.6 Terra costs $1.50 per million prompt (input) tokens and $6.00 per million completion (output) tokens.
What is the context window for GPT-5.6 Terra?
GPT-5.6 Terra supports a maximum context window of 262,144 tokens, with a maximum single-generation output of 32,768 tokens.
What are the primary use cases for GPT-5.6 Terra?
Mainstream production enterprise workflows, high-throughput developer copilots, and structured data synthesis.