Model comparison
Celeris-1 vs GPT-5.6 Terra
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Celeris-1 unranked (Not scored); GPT-5.6 Terra #11 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Celeris-1 and GPT-5.6 Terra share 0 comparable benchmark results. 1 of 8 categories are comparable. 1 result is unique to Celeris-1; 45 to GPT-5.6 Terra.
Updated July 24, 2026- Shared results
- 0
- Celeris-1 only
- 1
- GPT-5.6 Terra only
- 45
- Comparable categories
- 1 / 8
Treat this as a split decision. Celeris-1 makes more sense if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model; GPT-5.6 Terra is the better fit if knowledge is the priority or you need the larger 1M context window.
Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Celeris-1 and GPT-5.6 Terra finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.
GPT-5.6 Terra is also the more expensive model on tokens at $2.50 input / $15.00 output per 1M tokens, versus $2.00 input / $6.00 output per 1M tokens for Celeris-1. That is roughly 2.5x on output cost alone. GPT-5.6 Terra is the reasoning model in the pair, while Celeris-1 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. GPT-5.6 Terra gives you the larger context window at 1M, compared with 8K for Celeris-1.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Celeris-1 | GPT-5.6 Terra | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Celeris-1$2 input / $6 output | GPT-5.6 Terra$2.5 input / $15 output | Celeris-1 has the lower combined listed price. |
| Generation speedtokens per second | Celeris-1Not available | GPT-5.6 TerraNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Celeris-1Not available | GPT-5.6 TerraNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Celeris-18K | GPT-5.6 Terra1M | GPT-5.6 Terra lists the larger context window. |
Benchmark Deep Dive
Agentic17 benchmarks
| Benchmark | Celeris-1 | GPT-5.6 Terra | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | — | 87.4% | Not comparable |
| BrowseCompSource | — | 87.5% | Not comparable |
| OSWorld 2.0Source | — | 50.2% | Not comparable |
| CyberGymSource | — | 81.8% | Not comparable |
| ExploitGymSource | — | 23.2% | Not comparable |
| ToolathlonSource | — | 53.1% | Not comparable |
| AA Agentic IndexSource | — | 47.4% | Not comparable |
| τ²-bench resultsSource | — | 86.3% | Not comparable |
| GDPval-AASource | — | 54.1% | Not comparable |
| GDPval-AASource | — | 1581 | Not comparable |
| AA Harvey LABSource | — | 85.2% | Not comparable |
| AA ITBenchSource | — | 51.0% | Not comparable |
| AA Tau3 BankingSource | — | 31.8% | Not comparable |
| AA AutomationBenchSource | — | 45.6% | Not comparable |
| terminalBenchHardSource | — | 57.6% | Not comparable |
| aaTerminalBench21Source | — | 88% | Not comparable |
| APEX-Agents-AASource | — | 38.9% | Not comparable |
Coding7 benchmarks
| Benchmark | Celeris-1 | GPT-5.6 Terra | Result |
|---|---|---|---|
| SWE-bench ProSource | — | 63.4% | Not comparable |
| Terminal-Bench 2.0Source | — | 87.4% | Not comparable |
| deepSweSource | — | 69.6% | Not comparable |
| FrontierCode 1.1 ExtendedSource | — | 55.8% | Not comparable |
| cursorBench32Source | — | 64.9% | Not comparable |
| AA Coding IndexSource | — | 76.7% | Not comparable |
| AA-SciCodeSource | — | 53.9% | Not comparable |
Reasoning4 benchmarks
KnowledgeGPT-5.6 Terra wins11 benchmarks
| Benchmark | Celeris-1 | GPT-5.6 Terra | Result |
|---|---|---|---|
| MMLU-ProSource | 75.9% | — | Not comparable |
| GPQASource | — | 92.9% | Not comparable |
| GPQA-DSource | — | 92.9% | Not comparable |
| HealthBench ProfessionalSource | — | 57.7% | Not comparable |
| HealthBench HardSource | — | 32.7% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 55.0% | Not comparable |
| AA-GPQA DiamondSource | — | 92.5% | Not comparable |
| AA-HLESource | — | 41.8% | Not comparable |
| AA-Omniscience IndexSource | — | -0.2% | Not comparable |
| AA-Omniscience AccuracySource | — | 45.9% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 85.2% | Not comparable |
Math3 benchmarks
Multimodal3 benchmarks
Inst. Following1 benchmarks
| Benchmark | Celeris-1 | GPT-5.6 Terra | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 71.2% | Not comparable |
Frequently Asked Questions (2)
Which is better, Celeris-1 or GPT-5.6 Terra?
Celeris-1 and GPT-5.6 Terra are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.
Which is better for knowledge tasks, Celeris-1 or GPT-5.6 Terra?
GPT-5.6 Terra has the edge for knowledge tasks in this comparison, averaging 92.9 versus 75.9. Celeris-1 stays close enough that the answer can still flip depending on your workload.
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