Model comparison
Celeris-1 vs Claude Opus 4.7 (Adaptive)
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); Claude Opus 4.7 (Adaptive) #27 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Celeris-1 and Claude Opus 4.7 (Adaptive) share 0 comparable benchmark results. 1 of 8 categories are comparable. 1 result is unique to Celeris-1; 39 to Claude Opus 4.7 (Adaptive).
Updated July 24, 2026- Shared results
- 0
- Celeris-1 only
- 1
- Claude Opus 4.7 (Adaptive) only
- 39
- 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; Claude Opus 4.7 (Adaptive) 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 Claude Opus 4.7 (Adaptive) 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.
Claude Opus 4.7 (Adaptive) is also the more expensive model on tokens at $5.00 input / $25.00 output per 1M tokens, versus $2.00 input / $6.00 output per 1M tokens for Celeris-1. That is roughly 4.2x on output cost alone. Claude Opus 4.7 (Adaptive) 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. Claude Opus 4.7 (Adaptive) 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 | Claude Opus 4.7 (Adaptive) | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Celeris-1$2 input / $6 output | Claude Opus 4.7 (Adaptive)$5 input / $25 output | Celeris-1 has the lower combined listed price. |
| Generation speedtokens per second | Celeris-1Not available | Claude Opus 4.7 (Adaptive)Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Celeris-1Not available | Claude Opus 4.7 (Adaptive)Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Celeris-18K | Claude Opus 4.7 (Adaptive)1M | Claude Opus 4.7 (Adaptive) lists the larger context window. |
Benchmark Deep Dive
Agentic12 benchmarks
| Benchmark | Celeris-1 | Claude Opus 4.7 (Adaptive) | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | — | 69.4% | Not comparable |
| BrowseCompSource | — | 79.3% | Not comparable |
| MCP AtlasSource | — | 77.3% | Not comparable |
| OSWorld-VerifiedSource | — | 78% | Not comparable |
| CyberGymSource | — | 73.1% | Not comparable |
| AA Agentic IndexSource | — | 44.4% | Not comparable |
| τ²-bench resultsSource | — | 88.6% | Not comparable |
| GDPval-AASource | — | 49.8% | Not comparable |
| GDPval-AASource | — | 1495 | Not comparable |
| OSWorld 2.0Source | — | 18.2% | Not comparable |
| JobBenchSource | — | 45.9% | Not comparable |
| AA ITBenchSource | — | 46.7% | Not comparable |
Coding5 benchmarks
Reasoning5 benchmarks
KnowledgeCeleris-1 wins11 benchmarks
| Benchmark | Celeris-1 | Claude Opus 4.7 (Adaptive) | Result |
|---|---|---|---|
| MMLU-ProSource | 75.9% | — | Not comparable |
| GPQASource | — | 94.2% | Not comparable |
| GPQA-DSource | — | 94.2% | Not comparable |
| HLESource | — | 54.7% | Not comparable |
| HLE w/o toolsSource | — | 46.9% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 53.5% | Not comparable |
| AA-GPQA DiamondSource | — | 91.4% | Not comparable |
| AA-HLESource | — | 39.6% | Not comparable |
| AA-Omniscience IndexSource | — | 26.2% | Not comparable |
| AA-Omniscience AccuracySource | — | 45.8% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 36.2% | Not comparable |
Math1 benchmarks
| Benchmark | Celeris-1 | Claude Opus 4.7 (Adaptive) | Result |
|---|---|---|---|
| FrontierMath (legacy)Source | — | 43.8% | Not comparable |
Multimodal5 benchmarks
Inst. Following1 benchmarks
| Benchmark | Celeris-1 | Claude Opus 4.7 (Adaptive) | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 58.6% | Not comparable |
Frequently Asked Questions (2)
Which is better, Celeris-1 or Claude Opus 4.7 (Adaptive)?
Celeris-1 and Claude Opus 4.7 (Adaptive) 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 Claude Opus 4.7 (Adaptive)?
Celeris-1 has the edge for knowledge tasks in this comparison, averaging 75.9 versus 60. Claude Opus 4.7 (Adaptive) stays close enough that the answer can still flip depending on your workload.
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