Model comparison
GPT-5.6 Luna vs o3-mini
Head-to-head evidence from 5 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.6 Luna #22 (Estimated); o3-mini #136 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.6 Luna and o3-mini share 5 comparable benchmark results. 2 of 8 categories are comparable. 36 results are unique to GPT-5.6 Luna; 5 to o3-mini.
Updated July 23, 2026- Shared results
- 5
- GPT-5.6 Luna only
- 36
- o3-mini only
- 5
- Comparable categories
- 2 / 8
Pick GPT-5.6 Luna if you want the stronger benchmark profile. o3-mini only becomes the better choice if you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 5 shared benchmark results across 2 evidence categories; 2 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 BenchAlign aggregate, 67.17 to 47.41. 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 77.2. The single biggest benchmark swing on the page is GPQA, 92.3% to 77.2%.
GPT-5.6 Luna is also the more expensive model on tokens at $1.00 input / $6.00 output per 1M tokens, versus $1.10 input / $4.40 output per 1M tokens for o3-mini. GPT-5.6 Luna gives you the larger context window at 1M, compared with 200K for o3-mini.
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 | o3-mini |
|---|---|---|---|
| Knowledge | GPT-5.6 Luna92.3 | Margin← 15.1 | o3-mini77.2 |
| Coding | GPT-5.6 Luna62.7 | Margin← 13.4 | o3-mini49.3 |
| Agentic | GPT-5.6 Luna84.1 | MarginNo overlap | o3-miniNot measured |
| Math | GPT-5.6 Luna73.6 | MarginNo overlap | o3-miniNot measured |
| Multimodal | GPT-5.6 Luna78.4 | MarginNo overlap | o3-miniNot measured |
| Inst. Following | GPT-5.6 LunaNot measured | MarginNo overlap | o3-mini93.9 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
GPQA
KnowledgeA 92.3%B 77.2%Winner: GPT-5.6 LunaΔ 15.1GPQA: GPT-5.6 Luna scored 92.3%; o3-mini scored 77.2%. 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 | o3-mini | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.6 Luna$1 input / $6 output | o3-mini$1.1 input / $4.4 output | o3-mini has the lower combined listed price. |
| Generation speedtokens per second | GPT-5.6 LunaNot available | o3-mini160 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.6 LunaNot available | o3-mini7.12 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.6 Luna1M | o3-mini200K | GPT-5.6 Luna lists the larger context window. |
Benchmark Deep Dive
Agentic16 benchmarks
| Benchmark | GPT-5.6 Luna | o3-mini | 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 | 54.2% | — | Not comparable |
| GDPval-AASource | 1584 | — | Not comparable |
| AA Harvey LABSource | 87.9% | — | 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 |
| APEX-Agents-AASource | 35.8% | — | Not comparable |
| τ²-bench resultsSource | — | 28.7% | Not comparable |
CodingGPT-5.6 Luna wins8 benchmarks
| Benchmark | GPT-5.6 Luna | o3-mini | 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% | 39.9% | GPT-5.6 Luna leads |
| SWE-bench VerifiedSource | — | 49.3% | Not comparable |
Reasoning3 benchmarks
KnowledgeGPT-5.6 Luna wins11 benchmarks
| Benchmark | GPT-5.6 Luna | o3-mini | Result |
|---|---|---|---|
| GPQASource | 92.3% | 77.2% | GPT-5.6 Luna leads |
| GPQA-DSource | 92.3% | — | Not comparable |
| HealthBench ProfessionalSource | 55.7% | — | Not comparable |
| HealthBench HardSource | 32.0% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 51.2% | 19.0% | GPT-5.6 Luna leads |
| AA-GPQA DiamondSource | 91.1% | 74.8% | GPT-5.6 Luna leads |
| AA-HLESource | 37.2% | 8.7% | GPT-5.6 Luna leads |
| AA-Omniscience IndexSource | -11.2% | — | Not comparable |
| AA-Omniscience AccuracySource | 41.5% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 90.1% | — | Not comparable |
| MMLUSource | — | 86.9% | Not comparable |
Math4 benchmarks
Multimodal3 benchmarks
Inst. Following1 benchmarks
| Benchmark | GPT-5.6 Luna | o3-mini | Result |
|---|---|---|---|
| IFEvalSource | — | 93.9% | Not comparable |
Frequently Asked Questions (3)
Which is better, GPT-5.6 Luna or o3-mini?
GPT-5.6 Luna is ahead on BenchLM's BenchAlign leaderboard, 67.17 to 47.41. The biggest single separator in this matchup is GPQA, where the scores are 92.3% and 77.2%.
Which is better for knowledge tasks, GPT-5.6 Luna or o3-mini?
GPT-5.6 Luna has the edge for knowledge tasks in this comparison, averaging 92.3 versus 77.2. Inside this category, Artificial Analysis Intelligence Index is the benchmark that creates the most daylight between them.
Which is better for coding, GPT-5.6 Luna or o3-mini?
GPT-5.6 Luna has the edge for coding in this comparison, averaging 62.7 versus 49.3. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
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