GPT-5.6 Terra is a balanced model in OpenAI's GPT-5.6 series, positioned between the flagship Sol tier and the cost-efficient Luna tier. It is suited for everyday coding, reasoning, and agentic tasks where capability and cost need to be balanced, offering strong performance at roughly half the cost of Sol.
Providers
Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick: Balanced (price + speed), Nitro (fastest), or Floor (cheapest).
| $2.00 | $12.00 | $0.20 | 1.79s | 53 tok/s | ||
| $2.00 | $12.00 | $0.20 | 3.15s | 71 tok/s | ||
Not used in Standard routing:Why these endpoints are not used | ||||||
Flex | $1.00 | $6.00 | $0.10 | 2.49s | 78 tok/s | |
| $2.20 | $13.20 | $0.22 | 3.28s | 96 tok/s | ||
| $2.20 | $13.20 | $0.22 | 1.83s | 74 tok/s | ||
| $2.20 | $13.20 | $0.22 | 1.30s | 75 tok/s | ||
Fast | $4.00 | $24.00 | $0.40 | 0.90s | 95 tok/s | |
- Input $2.00 / Output $12.0053 tok/s100.00% uptime
- Input $2.00 / Output $12.0071 tok/s100.00% uptime
- Not used in Standard routing:Why these endpoints are not used
- Input $1.00 / Output $6.0078 tok/s100.00% uptimeFlex
- Input $2.20 / Output $13.2096 tok/s100.00% uptime
- Input $2.20 / Output $13.2074 tok/s100.00% uptime
- Input $2.20 / Output $13.2075 tok/s100.00% uptime
- Input $4.00 / Output $24.0095 tok/s100.00% uptimeFast
Pricing
The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.
Weighted average
GPT-5.6 Terra — Price history
| $0.607 | $12.06 | 84.0% | 13.7% | ||
| $0.887 | $12.02 | 71.8% | 82.6% | ||
Not used in Standard routing:Why these endpoints are not used | |||||
Flex | $0.799 | $6.00 | 31.2% | 1.5% | |
| $0.800 | $13.20 | 76.9% | 1.0% | ||
| $1.102 | $13.20 | 67.8% | 0.6% | ||
Fast | $1.424 | $24.00 | 77.5% | 0.6% | |
| $1.590 | $13.20 | 45.6% | 0.0% | ||
- Effective in $0.607 / Effective out $12.06Token share13.7%
- Effective in $0.887 / Effective out $12.02Token share82.6%
- Not used in Standard routing:Why these endpoints are not used
- Effective in $0.799 / Effective out $6.00FlexToken share1.5%
- Effective in $0.800 / Effective out $13.20Token share1.0%
- Effective in $1.102 / Effective out $13.20Token share0.6%
- Effective in $1.424 / Effective out $24.00FastToken share0.6%
- Effective in $1.590 / Effective out $13.20Token share0.0%
Performance
Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better).
P50, best across providers
P50, best provider
Uptime
Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.
Availability over the last 3 days
Last 72 hoursAvailability over the last 24 hours
When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and provider routing options.
Benchmarks
Scores on standardized evaluations and this model’s own outputs on shared benchmark prompts. Higher percentages are better — and each rank shows where this model lands among the models evaluated on that source.
| Source | Benchmark | Score |
|---|---|---|
| Artificial Analysis | GPT-5.6 Terra (Max) Intelligence Index | 32.3 |
| Artificial Analysis | GPT-5.6 Terra (Max) Coding Index | 76.7 |
| Artificial Analysis | GPT-5.6 Terra (Max) Agentic Index | 43.2 |
| Artificial Analysis | GPT-5.6 Terra (Max) GPQA Diamond | 92.5% |
| Artificial Analysis | GPT-5.6 Terra (Max) HLE | 42.9% |
| Artificial Analysis | GPT-5.6 Terra (Max) IFBench | 71.2% |
| Artificial Analysis | GPT-5.6 Terra (Max) τ²-Bench Telecom | 86.3% |
| Artificial Analysis | GPT-5.6 Terra (Max) AA-LCR | 83.0% |
| Artificial Analysis | GPT-5.6 Terra (Max) τ-Bench Banking | 40.2% |
| Artificial Analysis | GPT-5.6 Terra (Max) GDPval-AA | 48.1% |
| Artificial Analysis | GPT-5.6 Terra (Max) CritPt | 30.0% |
| Artificial Analysis | GPT-5.6 Terra (Max) SciCode | 55.0% |
| Artificial Analysis | GPT-5.6 Terra (Max) Terminal-Bench Hard | 57.6% |
| Artificial Analysis | GPT-5.6 Terra (Max) Terminal-Bench 4.0 | 35.4% |
| Artificial Analysis | GPT-5.6 Terra (Max) Terminal-Bench 2.1 | 88.0% |
| Artificial Analysis | GPT-5.6 Terra (Max) AA-Omniscience Accuracy | 42.3% |
| Artificial Analysis | GPT-5.6 Terra (Max) AA-Omniscience Non-Hallucination Rate | 10.6% |
| Artificial Analysis | GPT-5.6 Terra (Non-reasoning) Coding Index | 52.3 |
| Artificial Analysis | GPT-5.6 Terra (Non-reasoning) Agentic Index | 23.5 |
| Artificial Analysis | GPT-5.6 Terra (Non-reasoning) GPQA Diamond | 74.6% |
| Artificial Analysis | GPT-5.6 Terra (Non-reasoning) HLE | 11.4% |
| Artificial Analysis | GPT-5.6 Terra (Non-reasoning) AA-LCR | 58.7% |
| Artificial Analysis | GPT-5.6 Terra (Non-reasoning) τ-Bench Banking | 15.7% |
| Artificial Analysis | GPT-5.6 Terra (Non-reasoning) GDPval-AA | 30.2% |
| Artificial Analysis | GPT-5.6 Terra (Non-reasoning) CritPt | 2.0% |
| Artificial Analysis | GPT-5.6 Terra (Non-reasoning) SciCode | 45.1% |
| Artificial Analysis | GPT-5.6 Terra (Non-reasoning) Terminal-Bench 4.0 | 0.5% |
| Artificial Analysis | GPT-5.6 Terra (Non-reasoning) Terminal-Bench 2.1 | 56.2% |
| Artificial Analysis | GPT-5.6 Terra (Non-reasoning) AA-Omniscience Accuracy | 32.6% |
| Artificial Analysis | GPT-5.6 Terra (Non-reasoning) AA-Omniscience Non-Hallucination Rate | 4.4% |
| Artificial Analysis | GPT-5.6 Terra (Low) Coding Index | 58.1 |
| Artificial Analysis | GPT-5.6 Terra (Low) Agentic Index | 25.9 |
| Artificial Analysis | GPT-5.6 Terra (Low) GPQA Diamond | 84.3% |
| Artificial Analysis | GPT-5.6 Terra (Low) HLE | 29.2% |
| Artificial Analysis | GPT-5.6 Terra (Low) IFBench | 59.7% |
| Artificial Analysis | GPT-5.6 Terra (Low) τ²-Bench Telecom | 60.5% |
| Artificial Analysis | GPT-5.6 Terra (Low) AA-LCR | 71.3% |
| Artificial Analysis | GPT-5.6 Terra (Low) τ-Bench Banking | 18.8% |
| Artificial Analysis | GPT-5.6 Terra (Low) GDPval-AA | 30.9% |
| Artificial Analysis | GPT-5.6 Terra (Low) CritPt | 9.4% |
| Artificial Analysis | GPT-5.6 Terra (Low) SciCode | 49.9% |
| Artificial Analysis | GPT-5.6 Terra (Low) Terminal-Bench Hard | 43.9% |
| Artificial Analysis | GPT-5.6 Terra (Low) Terminal-Bench 4.0 | 1.5% |
| Artificial Analysis | GPT-5.6 Terra (Low) Terminal-Bench 2.1 | 62.5% |
| Artificial Analysis | GPT-5.6 Terra (Low) AA-Omniscience Accuracy | 39.8% |
| Artificial Analysis | GPT-5.6 Terra (Low) AA-Omniscience Non-Hallucination Rate | 8.7% |
| Artificial Analysis | GPT-5.6 Terra (Xhigh) Coding Index | 70.6 |
| Artificial Analysis | GPT-5.6 Terra (Xhigh) Agentic Index | 41.4 |
| Artificial Analysis | GPT-5.6 Terra (Xhigh) GPQA Diamond | 90.8% |
| Artificial Analysis | GPT-5.6 Terra (Xhigh) HLE | 41.9% |
| Artificial Analysis | GPT-5.6 Terra (Xhigh) IFBench | 66.3% |
| Artificial Analysis | GPT-5.6 Terra (Xhigh) τ²-Bench Telecom | 80.4% |
| Artificial Analysis | GPT-5.6 Terra (Xhigh) AA-LCR | 79.0% |
| Artificial Analysis | GPT-5.6 Terra (Xhigh) τ-Bench Banking | 29.7% |
| Artificial Analysis | GPT-5.6 Terra (Xhigh) GDPval-AA | 47.8% |
| Artificial Analysis | GPT-5.6 Terra (Xhigh) CritPt | 27.1% |
| Artificial Analysis | GPT-5.6 Terra (Xhigh) SciCode | 52.3% |
| Artificial Analysis | GPT-5.6 Terra (Xhigh) Terminal-Bench Hard | 62.9% |
| Artificial Analysis | GPT-5.6 Terra (Xhigh) Terminal-Bench 4.0 | 10.1% |
| Artificial Analysis | GPT-5.6 Terra (Xhigh) Terminal-Bench 2.1 | 80.1% |
| Artificial Analysis | GPT-5.6 Terra (Xhigh) AA-Omniscience Accuracy | 41.3% |
| Artificial Analysis | GPT-5.6 Terra (Xhigh) AA-Omniscience Non-Hallucination Rate | 9.9% |
| Artificial Analysis | GPT-5.6 Terra (High) Coding Index | 67.1 |
| Artificial Analysis | GPT-5.6 Terra (High) Agentic Index | 36.7 |
| Artificial Analysis | GPT-5.6 Terra (High) GPQA Diamond | 89.6% |
| Artificial Analysis | GPT-5.6 Terra (High) HLE | 38.5% |
| Artificial Analysis | GPT-5.6 Terra (High) IFBench | 64.4% |
| Artificial Analysis | GPT-5.6 Terra (High) τ²-Bench Telecom | 78.4% |
| Artificial Analysis | GPT-5.6 Terra (High) AA-LCR | 77.7% |
| Artificial Analysis | GPT-5.6 Terra (High) τ-Bench Banking | 28.7% |
| Artificial Analysis | GPT-5.6 Terra (High) GDPval-AA | 44.4% |
| Artificial Analysis | GPT-5.6 Terra (High) CritPt | 22.9% |
| Artificial Analysis | GPT-5.6 Terra (High) SciCode | 52.4% |
| Artificial Analysis | GPT-5.6 Terra (High) Terminal-Bench Hard | 57.6% |
| Artificial Analysis | GPT-5.6 Terra (High) Terminal-Bench 4.0 | 1.5% |
| Artificial Analysis | GPT-5.6 Terra (High) Terminal-Bench 2.1 | 75.7% |
| Artificial Analysis | GPT-5.6 Terra (High) AA-Omniscience Accuracy | 41.2% |
| Artificial Analysis | GPT-5.6 Terra (High) AA-Omniscience Non-Hallucination Rate | 9.0% |
| Artificial Analysis | GPT-5.6 Terra (Medium) Coding Index | 64.7 |
| Artificial Analysis | GPT-5.6 Terra (Medium) Agentic Index | 30.4 |
| Artificial Analysis | GPT-5.6 Terra (Medium) GPQA Diamond | 87.2% |
| Artificial Analysis | GPT-5.6 Terra (Medium) HLE | 33.3% |
| Artificial Analysis | GPT-5.6 Terra (Medium) IFBench | 62.2% |
| Artificial Analysis | GPT-5.6 Terra (Medium) τ²-Bench Telecom | 72.8% |
| Artificial Analysis | GPT-5.6 Terra (Medium) AA-LCR | 74.0% |
| Artificial Analysis | GPT-5.6 Terra (Medium) τ-Bench Banking | 25.6% |
| Artificial Analysis | GPT-5.6 Terra (Medium) GDPval-AA | 38.7% |
| Artificial Analysis | GPT-5.6 Terra (Medium) CritPt | 17.4% |
| Artificial Analysis | GPT-5.6 Terra (Medium) SciCode | 50.5% |
| Artificial Analysis | GPT-5.6 Terra (Medium) Terminal-Bench 4.0 | 1.0% |
| Artificial Analysis | GPT-5.6 Terra (Medium) Terminal-Bench 2.1 | 72.3% |
| Artificial Analysis | GPT-5.6 Terra (Medium) AA-Omniscience Accuracy | 40.5% |
| Artificial Analysis | GPT-5.6 Terra (Medium) AA-Omniscience Non-Hallucination Rate | 8.7% |
| Vals AI | GPT-5.6 Terra Code Migration | 47.8% |
| Vals AI | GPT-5.6 Terra CorpFin v2 | 65.3% |
| Vals AI | GPT-5.6 Terra CyberBench v1.1 | 72.1% |
| Vals AI | GPT-5.6 Terra EMB | 66.2% |
| Vals AI | GPT-5.6 Terra Finance Agent (v2) | 54.4% |
| Vals AI | GPT-5.6 Terra Financial Coaching Bench | 71.0% |
| Vals AI | GPT-5.6 Terra GPQA Diamond | 90.9% |
| Vals AI | GPT-5.6 Terra Harvey's Legal Agent Benchmark v1 | 0.8% |
| Vals AI | GPT-5.6 Terra IOI | 87.6% |
| Vals AI | GPT-5.6 Terra LiveCodeBench | 85.9% |
| Vals AI | GPT-5.6 Terra LegalBench | 85.1% |
| Vals AI | GPT-5.6 Terra Legal Research Bench | 41.3% |
| Vals AI | GPT-5.6 Terra MedCode | 43.4% |
| Vals AI | GPT-5.6 Terra MedScribe | 82.9% |
| Vals AI | GPT-5.6 Terra MMLU Pro | 86.7% |
| Vals AI | GPT-5.6 Terra MMMU Pro | 86.5% |
| Vals AI | GPT-5.6 Terra MortgageTax | 67.3% |
| Vals AI | GPT-5.6 Terra ProgramBench | 0.5% |
| Vals AI | GPT-5.6 Terra ProofBench v1.1 | 74.0% |
| Vals AI | GPT-5.6 Terra Public Benefits Bench v1.1 | 62.4% |
| Vals AI | GPT-5.6 Terra SAGE | 87.0% |
| Vals AI | GPT-5.6 Terra SkillsBench | 58.9% |
| Vals AI | GPT-5.6 Terra SRE Bench | 9.5% |
| Vals AI | GPT-5.6 Terra SWE-bench | 95.4% |
| Vals AI | GPT-5.6 Terra Tax Agent Bench | 30.0% |
| Vals AI | GPT-5.6 Terra TaxEval v2 | 76.2% |
| Vals AI | GPT-5.6 Terra Terminal-Bench 4.0 | 22.7% |
| Vals AI | GPT-5.6 Terra Terminal-Bench-Science | 10.0% |
| Vals AI | GPT-5.6 Terra Vals Index | 53.1% |
| Vals AI | GPT-5.6 Terra Vals Multimodal Index | 65.1% |
| Vals AI | GPT-5.6 Terra Vibe Code Bench 1-100 | 14.8% |
| Vals AI | GPT-5.6 Terra Vibe Code Bench v1.1 | 74.6% |
Apps
Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.
Activity
Token volume and request traffic to this model over time.
API
Drop-in code to call this model. OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. The only thing that changes between models is the model slug below.
Available through EU in-region routing
OpenAI: GPT-5.6 Terra is available through EU in-region routing. Requests sent to eu.openrouter.ai are decrypted in the EU and routed only to shared provider endpoints in Europe (the EU/EEA, the UK, and Switzerland).
- Providers in Europe
- Azure
- Prices in Europe
- Azure: $2.20/M tokens input, $13.20/M tokens output
- Base URL
https://eu.openrouter.ai/api/v1- Plan
- Requires Business or Enterprise. Self-serve on Business: no contract, no monthly minimum. OpenRouter Business for EU in-region routing
Fails closed: if no shared provider endpoint in Europe is available, the request errors instead of leaving the region. Requests served by your own BYOK key go to your deployment’s region, which you control. In-region routing docs
Documentation
Guides, cookbooks, blog posts, and tools for building with OpenAI: GPT-5.6 Terra on OpenRouter.
Frequently asked questions
GPT-5.6 Terra is a balanced model in OpenAI's GPT-5.6 series, positioned between the flagship Sol tier and the cost-efficient Luna tier. It is suited for everyday coding, reasoning, and agentic tasks where capability and cost need to be balanced, offering strong performance at roughly half the cost of Sol.
The GPT-5.6 Terra documentation on OpenRouter includes the GPT-5.6 Migration Guide cookbook and the GPT 5.6 Discounts & Jevons Paradox blog post. The quickstart covers API keys and your first request, and the API reference lists every parameter.
GPT-5.6 Terra costs $2.00/M input tokens and $12.00/M output tokens, with separate rates for Cache Read at $0.20/M tokens, Cache Write at $2.50/M tokens, and Web Search at $10.00/1K calls.
GPT-5.6 Terra has a 1,050,000 token context window. It supports up to 128,000 completion tokens.
Yes. GPT-5.6 Terra accepts tools and tool_choice for function calling. It also supports structured outputs via a JSON schema in response_format.
Yes. OpenAI caches prompts of 1024 tokens or more automatically, and GPT-5.6 Terra bills a cache write on each cached prompt whether or not the cached prefix is read again. To turn caching off for a request, set prompt_cache_options.mode to "explicit" at the request root and do not mark any content block with prompt_cache_breakpoint. Explicit mode disables OpenAI-managed breakpoints, so a request with none of your own has no cacheable prefix and is billed at the plain input rate. See the prompt caching guide.
GPT-5.6 Terra accepts files such as PDFs, images, and text as input and returns text.
GPT-5.6 Terra is served by 3 providers on OpenRouter: OpenAI, Azure, and Amazon Bedrock. Requests are routed to the best available provider, with automatic failover to the others, and you can pin or exclude providers with provider routing.
GPT-5.6 Terra was released on July 9, 2026. Its knowledge cutoff is February 16, 2026.