Model comparison
GPT-5.6 Luna vs Inkling
Head-to-head evidence from 7 shared benchmark results across 4 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Verified leaderboard positions: GPT-5.6 Luna unranked; Inkling #17
BenchAlign evidence: GPT-5.6 Luna estimated; Inkling not scored. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.6 Luna and Inkling share 7 comparable benchmark results. 5 of 8 categories are comparable. 33 results are unique to GPT-5.6 Luna; 9 to Inkling.
Updated July 15, 2026- Shared results
- 7
- GPT-5.6 Luna only
- 33
- Inkling only
- 9
- Comparable categories
- 5 / 8
Pick GPT-5.6 Luna if you want the stronger benchmark profile. Inkling only becomes the better choice if mathematics is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 7 shared benchmark results across 4 evidence categories; 5 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 is clearly ahead on the provisional aggregate, 82 to 69. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.6 Luna's sharpest advantage is in knowledge, where it averages 92.3 against 51.7. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 84.7% to 63.8%. Inkling does hit back in mathematics, so the answer changes if that is the part of the workload you care about most.
GPT-5.6 Luna is also the more expensive model on tokens at $1.00 input / $6.00 output per 1M tokens, versus $1.87 input / $4.68 output per 1M tokens for Inkling. GPT-5.6 Luna is the reasoning model in the pair, while Inkling 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.
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 | Inkling |
|---|---|---|---|
| Knowledge | GPT-5.6 Luna92.3 | Margin← 40.6 | Inkling51.7 |
| Math | GPT-5.6 Luna73.6 | Margin→ 23.5 | Inkling97.1 |
| Agentic | GPT-5.6 Luna84.1 | Margin← 14.7 | Inkling69.4 |
| Coding | GPT-5.6 Luna62.7 | Margin→ 5.9 | Inkling68.6 |
| Multimodal | GPT-5.6 Luna78.4 | Margin← 1.9 | Inkling76.5 |
| Inst. Following | GPT-5.6 LunaNot measured | MarginNo overlap | Inkling79.8 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 84.7%B 63.8%Winner: GPT-5.6 LunaΔ 20.9Terminal-Bench 2.0: GPT-5.6 Luna scored 84.7%; Inkling scored 63.8%. GPT-5.6 Luna wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 62.7%B 54.3%Winner: GPT-5.6 LunaΔ 8.4SWE-bench Pro: GPT-5.6 Luna scored 62.7%; Inkling scored 54.3%. GPT-5.6 Luna wins this benchmark. - Source ↗
BrowseComp
AgenticA 83.3%B 77.1%Winner: GPT-5.6 LunaΔ 6.2BrowseComp: GPT-5.6 Luna scored 83.3%; Inkling scored 77.1%. GPT-5.6 Luna wins this benchmark. - Source ↗
MMMU-Pro
MultimodalA 78.4%B 73.5%Winner: GPT-5.6 LunaΔ 4.9MMMU-Pro: GPT-5.6 Luna scored 78.4%; Inkling scored 73.5%. GPT-5.6 Luna wins this benchmark. - Source ↗
GPQA
KnowledgeA 92.3%B 87.9%Winner: GPT-5.6 LunaΔ 4.4GPQA: GPT-5.6 Luna scored 92.3%; Inkling scored 87.9%. 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 | Inkling | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.6 Luna$1 input / $6 output | Inkling$1.87 input / $4.68 output | Inkling has the lower combined listed price. |
| Generation speedtokens per second | GPT-5.6 LunaNot available | InklingNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.6 LunaNot available | InklingNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.6 Luna1M | Inkling1M | Listed context windows are equal. |
Benchmark Deep Dive
AgenticGPT-5.6 Luna wins15 benchmarks
| Benchmark | GPT-5.6 Luna | Inkling | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 84.7% | 63.8% | GPT-5.6 Luna leads |
| BrowseCompSource | 83.3% | 77.1% | GPT-5.6 Luna leads |
| 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 |
| MCP AtlasSource | — | 74.1% | Not comparable |
| Design Arena Agentic Web DevSource | — | 1258 | Not comparable |
CodingInkling wins9 benchmarks
| Benchmark | GPT-5.6 Luna | Inkling | Result |
|---|---|---|---|
| SWE-bench ProSource | 62.7% | 54.3% | GPT-5.6 Luna leads |
| Terminal-Bench 2.0Source | 84.7% | 63.8% | GPT-5.6 Luna leads |
| 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 |
| AA Terminal-Bench 2.1Source | 80.9% | — | Not comparable |
| SWE-bench VerifiedSource | — | 77.6% | Not comparable |
Reasoning3 benchmarks
KnowledgeGPT-5.6 Luna wins12 benchmarks
| Benchmark | GPT-5.6 Luna | Inkling | Result |
|---|---|---|---|
| GPQASource | 92.3% | 87.9% | GPT-5.6 Luna leads |
| GPQA-DSource | 92.3% | 87.9% | 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 |
| HLESource | — | 46% | Not comparable |
| HLE w/o toolsSource | — | 30% | Not comparable |
MathInkling wins4 benchmarks
MultimodalGPT-5.6 Luna wins5 benchmarks
Inst. Following1 benchmarks
| Benchmark | GPT-5.6 Luna | Inkling | Result |
|---|---|---|---|
| IFBenchSource | — | 79.8% | Not comparable |
Frequently Asked Questions (6)
Which is better, GPT-5.6 Luna or Inkling?
GPT-5.6 Luna is ahead on BenchLM's provisional leaderboard, 82 to 69. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 84.7% and 63.8%.
Which is better for knowledge tasks, GPT-5.6 Luna or Inkling?
GPT-5.6 Luna has the edge for knowledge tasks in this comparison, averaging 92.3 versus 51.7. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Which is better for coding, GPT-5.6 Luna or Inkling?
Inkling has the edge for coding in this comparison, averaging 68.6 versus 62.7. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Which is better for math, GPT-5.6 Luna or Inkling?
Inkling has the edge for math in this comparison, averaging 97.1 versus 73.6. GPT-5.6 Luna stays close enough that the answer can still flip depending on your workload.
Which is better for agentic tasks, GPT-5.6 Luna or Inkling?
GPT-5.6 Luna has the edge for agentic tasks in this comparison, averaging 84.1 versus 69.4. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Which is better for multimodal and grounded tasks, GPT-5.6 Luna or Inkling?
GPT-5.6 Luna has the edge for multimodal and grounded tasks in this comparison, averaging 78.4 versus 76.5. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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