Model comparison
GPT-5.6 Sol vs Ling 2.6 Flash
Head-to-head evidence from 16 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.6 Sol #3 (Supported); Ling 2.6 Flash #154 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.6 Sol and Ling 2.6 Flash share 16 comparable benchmark results. 2 of 8 categories are comparable. 30 results are unique to GPT-5.6 Sol; 2 to Ling 2.6 Flash.
Updated July 23, 2026- Shared results
- 16
- GPT-5.6 Sol only
- 30
- Ling 2.6 Flash only
- 2
- Comparable categories
- 2 / 8
Pick GPT-5.6 Sol if you want the stronger benchmark profile. Ling 2.6 Flash only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 16 shared benchmark results across 5 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 Sol is clearly ahead on the BenchAlign aggregate, 81.96 to 43.87. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.6 Sol's sharpest advantage is in coding, where it averages 64.6 against 27. The single biggest benchmark swing on the page is GPQA, 94.6% to 59%.
GPT-5.6 Sol is the reasoning model in the pair, while Ling 2.6 Flash 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. GPT-5.6 Sol gives you the larger context window at 1M, compared with 262K for Ling 2.6 Flash.
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 Sol | Δ | Ling 2.6 Flash |
|---|---|---|---|
| Coding | GPT-5.6 Sol64.6 | Margin← 37.6 | Ling 2.6 Flash27.0 |
| Knowledge | GPT-5.6 Sol94.6 | Margin← 35.6 | Ling 2.6 Flash59.0 |
| Agentic | GPT-5.6 Sol92.0 | MarginNo overlap | Ling 2.6 FlashNot measured |
| Math | GPT-5.6 Sol87.5 | MarginNo overlap | Ling 2.6 FlashNot measured |
| Multimodal | GPT-5.6 Sol83.0 | MarginNo overlap | Ling 2.6 FlashNot measured |
| Inst. Following | GPT-5.6 SolNot measured | MarginNo overlap | Ling 2.6 Flash57.0 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
GPQA
KnowledgeA 94.6%B 59%Winner: GPT-5.6 SolΔ 35.6GPQA: GPT-5.6 Sol scored 94.6%; Ling 2.6 Flash scored 59%. GPT-5.6 Sol wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.6 Sol | Ling 2.6 Flash | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.6 Sol$5 input / $30 output | Ling 2.6 FlashNot available | A complete price comparison is not available. |
| Generation speedtokens per second | GPT-5.6 SolNot available | Ling 2.6 Flash209.5 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.6 SolNot available | Ling 2.6 Flash1.07 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.6 Sol1M | Ling 2.6 Flash262K | GPT-5.6 Sol lists the larger context window. |
Benchmark Deep Dive
Agentic17 benchmarks
| Benchmark | GPT-5.6 Sol | Ling 2.6 Flash | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 91.9% | — | Not comparable |
| BrowseCompSource | 92.2% | — | Not comparable |
| OSWorld 2.0Source | 62.6% | — | Not comparable |
| CyberGymSource | 84.5% | — | Not comparable |
| ExploitGymSource | 33.7% | — | Not comparable |
| ToolathlonSource | 58% | — | Not comparable |
| AA Agentic IndexSource | 54.0% | 2.3% | GPT-5.6 Sol leads |
| τ²-bench resultsSource | 85.1% | 86% | Ling 2.6 Flash leads |
| GDPval-AASource | 61.8% | 2.2% | GPT-5.6 Sol leads |
| GDPval-AASource | 1736 | 545 | GPT-5.6 Sol leads |
| AA BriefcaseSource | 1501 | — | Not comparable |
| AA ITBenchSource | 56.2% | — | Not comparable |
| AA Tau3 BankingSource | 33.0% | — | Not comparable |
| AA AutomationBenchSource | 51.2% | — | Not comparable |
| AA Harvey LABSource | 87.2% | — | Not comparable |
| terminalBenchHardSource | 65.9% | — | Not comparable |
| aaTerminalBench21Source | 88% | — | Not comparable |
CodingGPT-5.6 Sol wins9 benchmarks
| Benchmark | GPT-5.6 Sol | Ling 2.6 Flash | Result |
|---|---|---|---|
| SWE-bench ProSource | 64.6% | — | Not comparable |
| Terminal-Bench 2.0Source | 91.9% | — | Not comparable |
| deepSweSource | 72.7% | — | Not comparable |
| FrontierCode 1.1 ExtendedSource | 60.6% | — | Not comparable |
| cursorBench32Source | 67.2% | — | Not comparable |
| VulcanBench v3Source | 87.0% | — | Not comparable |
| AA Coding IndexSource | 77.4% | 25.3% | GPT-5.6 Sol leads |
| AA-SciCodeSource | 56.1% | 27.1% | GPT-5.6 Sol leads |
| SciCodeSource | — | 27% | Not comparable |
Reasoning4 benchmarks
KnowledgeGPT-5.6 Sol wins10 benchmarks
| Benchmark | GPT-5.6 Sol | Ling 2.6 Flash | Result |
|---|---|---|---|
| GPQASource | 94.6% | 59% | GPT-5.6 Sol leads |
| GPQA-DSource | 94.6% | — | Not comparable |
| HealthBench ProfessionalSource | 60.5% | — | Not comparable |
| HealthBench HardSource | 33.1% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 58.9% | 14.1% | GPT-5.6 Sol leads |
| AA-GPQA DiamondSource | 94.1% | 59.3% | GPT-5.6 Sol leads |
| AA-HLESource | 47.2% | 6.2% | GPT-5.6 Sol leads |
| AA-Omniscience IndexSource | 21.7% | -65.7% | GPT-5.6 Sol leads |
| AA-Omniscience AccuracySource | 58.5% | 15.4% | GPT-5.6 Sol leads |
| AA-Omniscience Hallucination RateSource | 88.8% | 95.8% | GPT-5.6 Sol leads |
Math3 benchmarks
Multimodal3 benchmarks
Frequently Asked Questions (3)
Which is better, GPT-5.6 Sol or Ling 2.6 Flash?
GPT-5.6 Sol is ahead on BenchLM's BenchAlign leaderboard, 81.96 to 43.87. The biggest single separator in this matchup is GPQA, where the scores are 94.6% and 59%.
Which is better for knowledge tasks, GPT-5.6 Sol or Ling 2.6 Flash?
GPT-5.6 Sol has the edge for knowledge tasks in this comparison, averaging 94.6 versus 59. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.
Which is better for coding, GPT-5.6 Sol or Ling 2.6 Flash?
GPT-5.6 Sol has the edge for coding in this comparison, averaging 64.6 versus 27. Inside this category, AA Coding Index is the benchmark that creates the most daylight between them.
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