Model comparison
GPT-5.6 Luna vs ZAYA1-74B-Preview
Head-to-head evidence from 2 shared benchmark results across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.6 Luna #22 (Estimated); ZAYA1-74B-Preview unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.6 Luna and ZAYA1-74B-Preview share 2 comparable benchmark results. 3 of 8 categories are comparable. 38 results are unique to GPT-5.6 Luna; 5 to ZAYA1-74B-Preview.
Updated July 18, 2026- Shared results
- 2
- GPT-5.6 Luna only
- 38
- ZAYA1-74B-Preview only
- 5
- Comparable categories
- 3 / 8
Treat this as a split decision. GPT-5.6 Luna makes more sense if knowledge is the priority or you need the larger 1M context window; ZAYA1-74B-Preview is the better fit if mathematics is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 2 shared benchmark results across 1 evidence category; 3 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GPT-5.6 Luna and ZAYA1-74B-Preview 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.
GPT-5.6 Luna is also the more expensive model on tokens at $1.00 input / $6.00 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. GPT-5.6 Luna 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 | GPT-5.6 Luna | Δ | ZAYA1-74B-Preview |
|---|---|---|---|
| Knowledge | GPT-5.6 Luna92.3 | Margin← 26.2 | ZAYA1-74B-Preview66.1 |
| Coding | GPT-5.6 Luna62.7 | Margin← 9.5 | ZAYA1-74B-Preview53.2 |
| Math | GPT-5.6 Luna73.6 | Margin→ 2.8 | ZAYA1-74B-Preview76.4 |
| Agentic | GPT-5.6 Luna84.1 | MarginNo overlap | ZAYA1-74B-PreviewNot measured |
| Multimodal | GPT-5.6 Luna78.4 | MarginNo overlap | ZAYA1-74B-PreviewNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
GPQA
KnowledgeA 92.3%B 57.3%Winner: GPT-5.6 LunaΔ 35GPQA: GPT-5.6 Luna scored 92.3%; ZAYA1-74B-Preview scored 57.3%. GPT-5.6 Luna wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.6 Luna | ZAYA1-74B-Preview | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.6 Luna$1 input / $6 output | ZAYA1-74B-Preview$0 input / $0 output | ZAYA1-74B-Preview has the lower combined listed price. |
| Generation speedtokens per second | GPT-5.6 LunaNot available | ZAYA1-74B-PreviewNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.6 LunaNot available | ZAYA1-74B-PreviewNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.6 Luna1M | ZAYA1-74B-Preview256K | GPT-5.6 Luna lists the larger context window. |
Benchmark Deep Dive
Agentic15 benchmarks
| Benchmark | GPT-5.6 Luna | ZAYA1-74B-Preview | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 84.7% | — | Not comparable |
| BrowseCompSource | 83.3% | — | Not comparable |
| OSWorld 2.0Source | 45.6% | — | Not comparable |
| CyberGymSource | 77.9% | — | Not comparable |
| ExploitGymSource | 12.4% | — | Not comparable |
| ToolathlonSource | 53.4% | — | Not comparable |
| AA Agentic IndexSource | 45.6% | — | Not comparable |
| GDPval-AASource | 54.6% | — | Not comparable |
| GDPval-AASource | 1592 | — | Not comparable |
| AA Harvey LABSource | 5.0% | — | Not comparable |
| AA ITBenchSource | 40.3% | — | Not comparable |
| AA Tau3 BankingSource | 27.2% | — | Not comparable |
| AA AutomationBenchSource | 42.2% | — | Not comparable |
| aaTerminalBench21Source | 80.9% | — | Not comparable |
| τ²-bench AirlineSource | — | 56.1% | Not comparable |
CodingGPT-5.6 Luna wins9 benchmarks
| Benchmark | GPT-5.6 Luna | ZAYA1-74B-Preview | Result |
|---|---|---|---|
| SWE-bench ProSource | 62.7% | — | Not comparable |
| Terminal-Bench 2.0Source | 84.7% | — | Not comparable |
| deepSweSource | 67.2% | — | Not comparable |
| FrontierCode 1.1 ExtendedSource | 55.1% | — | Not comparable |
| cursorBench32Source | 61.1% | — | Not comparable |
| AA Coding IndexSource | 71.5% | — | Not comparable |
| AA-SciCodeSource | 52.5% | — | Not comparable |
| LiveCodeBench v6Source | — | 65.7% | Not comparable |
| SWE-bench VerifiedSource | — | 53.2% | Not comparable |
Reasoning3 benchmarks
KnowledgeGPT-5.6 Luna wins11 benchmarks
| Benchmark | GPT-5.6 Luna | ZAYA1-74B-Preview | Result |
|---|---|---|---|
| GPQASource | 92.3% | 57.3% | GPT-5.6 Luna leads |
| GPQA-DSource | 92.3% | 57.3% | GPT-5.6 Luna leads |
| HealthBench ProfessionalSource | 55.7% | — | Not comparable |
| HealthBench HardSource | 32.0% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 51.2% | — | Not comparable |
| AA-GPQA DiamondSource | 91.1% | — | Not comparable |
| AA-HLESource | 37.2% | — | Not comparable |
| AA-Omniscience IndexSource | -11.2% | — | Not comparable |
| AA-Omniscience AccuracySource | 41.5% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 90.1% | — | Not comparable |
| MMLU-ProSource | — | 68.1% | Not comparable |
MathZAYA1-74B-Preview wins4 benchmarks
Frequently Asked Questions (4)
Which is better, GPT-5.6 Luna or ZAYA1-74B-Preview?
GPT-5.6 Luna and ZAYA1-74B-Preview 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, GPT-5.6 Luna or ZAYA1-74B-Preview?
GPT-5.6 Luna has the edge for knowledge tasks in this comparison, averaging 92.3 versus 66.1. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Which is better for coding, GPT-5.6 Luna or ZAYA1-74B-Preview?
GPT-5.6 Luna has the edge for coding in this comparison, averaging 62.7 versus 53.2. ZAYA1-74B-Preview stays close enough that the answer can still flip depending on your workload.
Which is better for math, GPT-5.6 Luna or ZAYA1-74B-Preview?
ZAYA1-74B-Preview has the edge for math in this comparison, averaging 76.4 versus 73.6. GPT-5.6 Luna stays close enough that the answer can still flip depending on your workload.
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