Model comparison
MiniMax M3 vs ZAYA1-74B-Preview
Head-to-head evidence from 1 shared benchmark result across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.
Verified leaderboard positions: MiniMax M3 #18; ZAYA1-74B-Preview unranked
BenchAlign evidence: MiniMax M3 supported; ZAYA1-74B-Preview not scored. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. MiniMax M3 and ZAYA1-74B-Preview share 1 comparable benchmark result. 2 of 8 categories are comparable. 44 results are unique to MiniMax M3; 6 to ZAYA1-74B-Preview.
Updated July 16, 2026- Shared results
- 1
- MiniMax M3 only
- 44
- ZAYA1-74B-Preview only
- 6
- Comparable categories
- 2 / 8
Pick MiniMax M3 if you want the stronger benchmark profile. ZAYA1-74B-Preview only becomes the better choice if you want the cheaper token bill 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; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
MiniMax M3 is clearly ahead on the provisional aggregate, 70 to 55. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
MiniMax M3's sharpest advantage is in coding, where it averages 72.2 against 53.2. The single biggest benchmark swing on the page is SWE-bench Verified, 80.5% to 53.2%.
MiniMax M3 is also the more expensive model on tokens at $0.30 input / $1.20 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for ZAYA1-74B-Preview. That is roughly Infinityx on output cost alone. ZAYA1-74B-Preview is the reasoning model in the pair, while MiniMax M3 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. MiniMax M3 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 | MiniMax M3 | Δ | ZAYA1-74B-Preview |
|---|---|---|---|
| Coding | MiniMax M372.2 | Margin← 19.0 | ZAYA1-74B-Preview53.2 |
| Math | MiniMax M385.7 | Margin← 9.3 | ZAYA1-74B-Preview76.4 |
| Agentic | MiniMax M372.3 | MarginNo overlap | ZAYA1-74B-PreviewNot measured |
| Knowledge | MiniMax M3Not measured | MarginNo overlap | ZAYA1-74B-Preview66.1 |
| Multimodal | MiniMax M364.9 | MarginNo overlap | ZAYA1-74B-PreviewNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
SWE-bench Verified
CodingA 80.5%B 53.2%Winner: MiniMax M3Δ 27.3SWE-bench Verified: MiniMax M3 scored 80.5%; ZAYA1-74B-Preview scored 53.2%. MiniMax M3 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | MiniMax M3 | ZAYA1-74B-Preview | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | MiniMax M3$0.3 input / $1.2 output | ZAYA1-74B-Preview$0 input / $0 output | ZAYA1-74B-Preview has the lower combined listed price. |
| Generation speedtokens per second | MiniMax M3Not available | ZAYA1-74B-PreviewNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | MiniMax M3Not available | ZAYA1-74B-PreviewNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | MiniMax M31M | ZAYA1-74B-Preview256K | MiniMax M3 lists the larger context window. |
Benchmark Deep Dive
Agentic17 benchmarks
| Benchmark | MiniMax M3 | ZAYA1-74B-Preview | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 66% | — | Not comparable |
| BrowseCompSource | 83.5% | — | Not comparable |
| OSWorld-VerifiedSource | 70.1% | — | Not comparable |
| MCP AtlasSource | 74.2% | — | Not comparable |
| Claw-EvalSource | 74.5% | — | Not comparable |
| AA Agentic IndexSource | 35.4% | — | Not comparable |
| τ²-bench resultsSource | 88.9% | — | Not comparable |
| GDPval-AASource | 44.7% | — | Not comparable |
| GDPval-AASource | 1395 | — | Not comparable |
| GDPval rubricsSource | 74.7% | — | Not comparable |
| BankerToolBenchSource | 76.1% | — | Not comparable |
| ResearchClawBenchSource | 19.8% | — | Not comparable |
| OSWorld 2.0Source | 4.6% | — | Not comparable |
| AA BriefcaseSource | 1110 | — | Not comparable |
| AA EnterpriseOps-GymSource | 32.1% | — | Not comparable |
| AA Harvey LABSource | 6.7% | — | Not comparable |
| τ²-bench AirlineSource | — | 56.1% | Not comparable |
CodingMiniMax M3 wins12 benchmarks
| Benchmark | MiniMax M3 | ZAYA1-74B-Preview | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 80.5% | 53.2% | MiniMax M3 leads |
| SWE-bench ProSource | 59% | — | Not comparable |
| Terminal-Bench 2.0Source | 66.0% | — | Not comparable |
| NL2RepoSource | 42.1% | — | Not comparable |
| AA Coding IndexSource | 58.6% | — | Not comparable |
| Terminal-Bench HardSource | 42.4% | — | Not comparable |
| AA-SciCodeSource | 45.4% | — | Not comparable |
| VIBE V2Source | 50.1% | — | Not comparable |
| SVG-BenchSource | 63.7% | — | Not comparable |
| KernelBench HardSource | 28.8% | — | Not comparable |
| AA Terminal-Bench 2.1Source | 65.2% | — | Not comparable |
| LiveCodeBench v6Source | — | 65.7% | Not comparable |
Reasoning2 benchmarks
Knowledge10 benchmarks
| Benchmark | MiniMax M3 | ZAYA1-74B-Preview | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 44.4% | — | Not comparable |
| AA-GPQA DiamondSource | 92.9% | — | Not comparable |
| AA-HLESource | 37.1% | — | Not comparable |
| AA-Omniscience IndexSource | 1.4% | — | Not comparable |
| AA-Omniscience AccuracySource | 15.0% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 16.1% | — | Not comparable |
| AA Openness IndexSource | 33.3% | — | Not comparable |
| MMLU-ProSource | — | 68.1% | Not comparable |
| GPQASource | — | 57.3% | Not comparable |
| GPQA-DSource | — | 57.3% | Not comparable |
MathMiniMax M3 wins2 benchmarks
Multimodal7 benchmarks
| Benchmark | MiniMax M3 | ZAYA1-74B-Preview | Result |
|---|---|---|---|
| OfficeQA ProSource | 45.1% | — | Not comparable |
| OmniDocBench 1.5Source | 91.6% | — | Not comparable |
| MMMU-ProSource | 78.1% | — | Not comparable |
| VideoMMMUSource | 84.6% | — | Not comparable |
| Video-MME (with subtitle)Source | 85.4% | — | Not comparable |
| Design Arena WebsiteSource | 1294 | — | Not comparable |
| AA-MMMU-ProSource | 78.6% | — | Not comparable |
Inst. Following1 benchmarks
| Benchmark | MiniMax M3 | ZAYA1-74B-Preview | Result |
|---|---|---|---|
| AA-IFBenchSource | 82.9% | — | Not comparable |
Frequently Asked Questions (3)
Which is better, MiniMax M3 or ZAYA1-74B-Preview?
MiniMax M3 is ahead on BenchLM's provisional leaderboard, 70 to 55. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 80.5% and 53.2%.
Which is better for coding, MiniMax M3 or ZAYA1-74B-Preview?
MiniMax M3 has the edge for coding in this comparison, averaging 72.2 versus 53.2. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Which is better for math, MiniMax M3 or ZAYA1-74B-Preview?
MiniMax M3 has the edge for math in this comparison, averaging 85.7 versus 76.4. ZAYA1-74B-Preview stays close enough that the answer can still flip depending on your workload.
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