Model comparison
Holo3-122B-A10B vs MAI-Thinking-1
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Evidence parity. Holo3-122B-A10B and MAI-Thinking-1 share 0 comparable benchmark results. 1 of 8 categories are comparable. 1 result is unique to Holo3-122B-A10B; 13 to MAI-Thinking-1.
Updated July 23, 2026- Shared results
- 0
- Holo3-122B-A10B only
- 1
- MAI-Thinking-1 only
- 13
- Comparable categories
- 1 / 8
Treat this as a split decision. Holo3-122B-A10B makes more sense if agentic 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 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
Holo3-122B-A10B 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 Holo3-122B-A10B 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 64K for Holo3-122B-A10B.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Holo3-122B-A10B | MAI-Thinking-1 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Holo3-122B-A10B$0.4 input / $3 output | MAI-Thinking-1Not available | A complete price comparison is not available. |
| Generation speedtokens per second | Holo3-122B-A10BNot available | MAI-Thinking-1Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Holo3-122B-A10BNot available | MAI-Thinking-1Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Holo3-122B-A10B64K | MAI-Thinking-1256K | MAI-Thinking-1 lists the larger context window. |
Benchmark Deep Dive
AgenticHolo3-122B-A10B wins2 benchmarks
Coding3 benchmarks
Reasoning1 benchmarks
| Benchmark | Holo3-122B-A10B | MAI-Thinking-1 | Result |
|---|---|---|---|
| Graphwalks BFS 128KSource | — | 90% | Not comparable |
Knowledge4 benchmarks
Math3 benchmarks
Inst. Following1 benchmarks
| Benchmark | Holo3-122B-A10B | MAI-Thinking-1 | Result |
|---|---|---|---|
| IFBenchSource | — | 85% | Not comparable |
Frequently Asked Questions (2)
Which is better, Holo3-122B-A10B or MAI-Thinking-1?
Holo3-122B-A10B 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 agentic tasks, Holo3-122B-A10B or MAI-Thinking-1?
Holo3-122B-A10B has the edge for agentic tasks in this comparison, averaging 78.9 versus 46. MAI-Thinking-1 stays close enough that the answer can still flip depending on your workload.
Related Comparisons
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.