Model comparison
Soofi S 30B-A3B vs ZAYA1-74B-Preview
Head-to-head evidence from 3 shared benchmark results across 1 category. Overall scores shown here use BenchLM's provisional ranking lane.
Evidence parity. Soofi S 30B-A3B and ZAYA1-74B-Preview share 3 comparable benchmark results. 1 of 8 categories are comparable. 5 results are unique to Soofi S 30B-A3B; 4 to ZAYA1-74B-Preview.
Updated July 15, 2026- Shared results
- 3
- Soofi S 30B-A3B only
- 5
- ZAYA1-74B-Preview only
- 4
- Comparable categories
- 1 / 8
Pick ZAYA1-74B-Preview if you want the stronger benchmark profile. Soofi S 30B-A3B only becomes the better choice if you need the larger 1M context window or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 3 shared benchmark results 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
ZAYA1-74B-Preview is clearly ahead on the provisional aggregate, 56 to 45. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
ZAYA1-74B-Preview's sharpest advantage is in knowledge, where it averages 66.1 against 49.9. The single biggest benchmark swing on the page is MMLU-Pro, 51.4% to 68.1%.
ZAYA1-74B-Preview is the reasoning model in the pair, while Soofi S 30B-A3B 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. Soofi S 30B-A3B gives you the larger context window at 1M, compared with 256K for ZAYA1-74B-Preview.
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 | Soofi S 30B-A3B | Δ | ZAYA1-74B-Preview |
|---|---|---|---|
| Knowledge | Soofi S 30B-A3B49.9 | Margin→ 16.2 | ZAYA1-74B-Preview66.1 |
| Coding | Soofi S 30B-A3BNot measured | MarginNo overlap | ZAYA1-74B-Preview53.2 |
| Math | Soofi S 30B-A3BNot measured | MarginNo overlap | ZAYA1-74B-Preview76.4 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
MMLU-Pro
KnowledgeA 51.4%B 68.1%Winner: ZAYA1-74B-PreviewΔ 16.7MMLU-Pro: Soofi S 30B-A3B scored 51.4%; ZAYA1-74B-Preview scored 68.1%. ZAYA1-74B-Preview wins this benchmark. - Source ↗
GPQA
KnowledgeA 43.4%B 57.3%Winner: ZAYA1-74B-PreviewΔ 13.9GPQA: Soofi S 30B-A3B scored 43.4%; ZAYA1-74B-Preview scored 57.3%. ZAYA1-74B-Preview wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Soofi S 30B-A3B | ZAYA1-74B-Preview | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Soofi S 30B-A3B$0 input / $0 output | ZAYA1-74B-Preview$0 input / $0 output | Listed prices are equal. |
| Generation speedtokens per second | Soofi S 30B-A3BNot available | ZAYA1-74B-PreviewNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Soofi S 30B-A3BNot available | ZAYA1-74B-PreviewNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Soofi S 30B-A3B1M | ZAYA1-74B-Preview256K | Soofi S 30B-A3B lists the larger context window. |
Benchmark Deep Dive
Agentic1 benchmarks
| Benchmark | Soofi S 30B-A3B | ZAYA1-74B-Preview | Result |
|---|---|---|---|
| τ²-bench AirlineSource | — | 56.1% | Not comparable |
Coding3 benchmarks
Reasoning2 benchmarks
KnowledgeZAYA1-74B-Preview wins4 benchmarks
Frequently Asked Questions (2)
Which is better, Soofi S 30B-A3B or ZAYA1-74B-Preview?
ZAYA1-74B-Preview is ahead on BenchLM's provisional leaderboard, 56 to 45. The biggest single separator in this matchup is MMLU-Pro, where the scores are 51.4% and 68.1%.
Which is better for knowledge tasks, Soofi S 30B-A3B or ZAYA1-74B-Preview?
ZAYA1-74B-Preview has the edge for knowledge tasks in this comparison, averaging 66.1 versus 49.9. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
Related Comparisons
The AI models change fast. We track them for you.
A weekly brief for engineers and researchers covering new models, ranking shifts, and pricing changes.
Free. No spam. Unsubscribe anytime.