Model comparison
Celeris-1 vs GPT-5.5
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-5.5 #9 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Celeris-1 and GPT-5.5 share 0 comparable benchmark results. 1 of 8 categories are comparable. 1 result is unique to Celeris-1; 58 to GPT-5.5.
Updated July 24, 2026- Shared results
- 0
- Celeris-1 only
- 1
- GPT-5.5 only
- 58
- Comparable categories
- 1 / 8
Treat this as a split decision. Celeris-1 makes more sense if knowledge is the priority or you want the cheaper token bill; GPT-5.5 is the better fit if you need the larger 1M context window or you want the stronger reasoning-first profile.
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-5.5 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-5.5 is also the more expensive model on tokens at $5.00 input / $30.00 output per 1M tokens, versus $2.00 input / $6.00 output per 1M tokens for Celeris-1. That is roughly 5.0x on output cost alone. GPT-5.5 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-5.5 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-5.5 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Celeris-1$2 input / $6 output | GPT-5.5$5 input / $30 output | Celeris-1 has the lower combined listed price. |
| Generation speedtokens per second | Celeris-1Not available | GPT-5.5Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Celeris-1Not available | GPT-5.5Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Celeris-18K | GPT-5.51M | GPT-5.5 lists the larger context window. |
Benchmark Deep Dive
Agentic24 benchmarks
| Benchmark | Celeris-1 | GPT-5.5 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | — | 82% | Not comparable |
| CyberGymSource | — | 81.8% | Not comparable |
| BrowseCompSource | — | 84.4% | Not comparable |
| OSWorld-VerifiedSource | — | 78.7% | Not comparable |
| MCP AtlasSource | — | 75.3% | Not comparable |
| ToolathlonSource | — | 55.6% | Not comparable |
| τ²-bench resultsSource | — | 93.9% | Not comparable |
| AA Agentic IndexSource | — | 44.9% | Not comparable |
| APEX-Agents-AASource | — | 37.7% | Not comparable |
| GDPval-AASource | — | 49.5% | Not comparable |
| GDPval-AASource | — | 1490 | Not comparable |
| Gert LabsSource | — | 72.93% | Not comparable |
| ResearchClawBenchSource | — | 17.0% | Not comparable |
| OSWorld 2.0Source | — | 13.0% | Not comparable |
| JobBenchSource | — | 42.7% | Not comparable |
| ExploitGymSource | — | 13.4% | Not comparable |
| AA BriefcaseSource | — | 1154 | Not comparable |
| AA AutomationBenchSource | — | 42.1% | Not comparable |
| AA EnterpriseOps-GymSource | — | 46.6% | Not comparable |
| AA Harvey LABSource | — | 86.3% | Not comparable |
| AA ITBenchSource | — | 45.8% | Not comparable |
| AA Tau3 BankingSource | — | 31.3% | Not comparable |
| terminalBenchHardSource | — | 60.6% | Not comparable |
| aaTerminalBench21Source | — | 84.3% | Not comparable |
Coding9 benchmarks
| Benchmark | Celeris-1 | GPT-5.5 | Result |
|---|---|---|---|
| SWE-bench ProSource | — | 58.6% | Not comparable |
| Terminal-Bench 2.0Source | — | 82.0% | Not comparable |
| Vibe Code BenchSource | — | 69.85% | Not comparable |
| React Native EvalsSource | — | 84.7% | Not comparable |
| cursorBench31Source | — | 59.2% | Not comparable |
| cursorBench32Source | — | 58.4% | Not comparable |
| AA Coding IndexSource | — | 74.9% | Not comparable |
| AA-SciCodeSource | — | 56.1% | Not comparable |
| FrontierCode 1.1 MainSource | — | 43.0% | Not comparable |
Reasoning6 benchmarks
KnowledgeCeleris-1 wins11 benchmarks
| Benchmark | Celeris-1 | GPT-5.5 | Result |
|---|---|---|---|
| MMLU-ProSource | 75.9% | — | Not comparable |
| GPQASource | — | 93.6% | Not comparable |
| GPQA-DSource | — | 93.6% | Not comparable |
| HLESource | — | 52.2% | Not comparable |
| HLE w/o toolsSource | — | 41.4% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 54.8% | Not comparable |
| AA-GPQA DiamondSource | — | 93.5% | Not comparable |
| AA-HLESource | — | 44.3% | Not comparable |
| AA-Omniscience IndexSource | — | 20.1% | Not comparable |
| AA-Omniscience AccuracySource | — | 56.9% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 85.5% | Not comparable |
Math3 benchmarks
Multimodal5 benchmarks
Inst. Following1 benchmarks
| Benchmark | Celeris-1 | GPT-5.5 | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 75.9% | Not comparable |
Frequently Asked Questions (2)
Which is better, Celeris-1 or GPT-5.5?
Celeris-1 and GPT-5.5 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-5.5?
Celeris-1 has the edge for knowledge tasks in this comparison, averaging 75.9 versus 57.8. GPT-5.5 stays close enough that the answer can still flip depending on your workload.
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