Model comparison
Celeris-1 vs MAI-Thinking-1
Head-to-head evidence from 1 shared benchmark result across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.
Evidence parity. Celeris-1 and MAI-Thinking-1 share 1 comparable benchmark result. 1 of 8 categories are comparable. 0 results are unique to Celeris-1; 12 to MAI-Thinking-1.
Updated July 24, 2026- Shared results
- 1
- Celeris-1 only
- 0
- MAI-Thinking-1 only
- 12
- Comparable categories
- 1 / 8
Treat this as a split decision. Celeris-1 makes more sense if knowledge is the priority or you would rather avoid the extra latency and token burn of a reasoning model; MAI-Thinking-1 is the better fit if you need the larger 256K context window or you want the stronger reasoning-first profile.
Confidence note. This is a partial-evidence comparison with 1 shared benchmark result across 1 evidence category; 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 MAI-Thinking-1 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.
MAI-Thinking-1 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. MAI-Thinking-1 gives you the larger context window at 256K, compared with 8K for Celeris-1.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | Celeris-1 | Δ | MAI-Thinking-1 |
|---|---|---|---|
| Knowledge | Celeris-175.9 | Margin← 3.4 | MAI-Thinking-172.5 |
| Agentic | Celeris-1Not measured | MarginNo overlap | MAI-Thinking-146.0 |
| Coding | Celeris-1Not measured | MarginNo overlap | MAI-Thinking-165.5 |
| Math | Celeris-1Not measured | MarginNo overlap | MAI-Thinking-189.7 |
| Inst. Following | Celeris-1Not measured | MarginNo overlap | MAI-Thinking-185.0 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
MMLU-Pro
KnowledgeA 75.9%B 85%Winner: MAI-Thinking-1Δ 9.1MMLU-Pro: Celeris-1 scored 75.9%; MAI-Thinking-1 scored 85%. MAI-Thinking-1 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Celeris-1 | MAI-Thinking-1 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Celeris-1$2 input / $6 output | MAI-Thinking-1Not available | A complete price comparison is not available. |
| Generation speedtokens per second | Celeris-1Not available | MAI-Thinking-1Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Celeris-1Not available | MAI-Thinking-1Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Celeris-18K | MAI-Thinking-1256K | MAI-Thinking-1 lists the larger context window. |
Benchmark Deep Dive
Agentic1 benchmarks
| Benchmark | Celeris-1 | MAI-Thinking-1 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | — | 46% | Not comparable |
Coding3 benchmarks
Reasoning1 benchmarks
| Benchmark | Celeris-1 | MAI-Thinking-1 | Result |
|---|---|---|---|
| Graphwalks BFS 128KSource | — | 90% | Not comparable |
KnowledgeCeleris-1 wins4 benchmarks
Math3 benchmarks
Inst. Following1 benchmarks
| Benchmark | Celeris-1 | MAI-Thinking-1 | Result |
|---|---|---|---|
| IFBenchSource | — | 85% | Not comparable |
Frequently Asked Questions (2)
Which is better, Celeris-1 or MAI-Thinking-1?
Celeris-1 and MAI-Thinking-1 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 MAI-Thinking-1?
Celeris-1 has the edge for knowledge tasks in this comparison, averaging 75.9 versus 72.5. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
Related Comparisons
Explore More
Choose a model with this week’s evidence
Join 2,000+ readers for ranking moves, pricing changes, and the claims that still need proof.
One email each week. Unsubscribe anytime.