Model comparison
Claude Sonnet 5 vs Ling 2.6 Flash
Head-to-head evidence from 13 shared benchmark results across 4 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude Sonnet 5 #29 (Estimated); Ling 2.6 Flash #154 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Sonnet 5 and Ling 2.6 Flash share 13 comparable benchmark results. 2 of 8 categories are comparable. 23 results are unique to Claude Sonnet 5; 5 to Ling 2.6 Flash.
Updated July 23, 2026- Shared results
- 13
- Claude Sonnet 5 only
- 23
- Ling 2.6 Flash only
- 5
- Comparable categories
- 2 / 8
Pick Claude Sonnet 5 if you want the stronger benchmark profile. Ling 2.6 Flash only becomes the better choice if knowledge is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 13 shared benchmark results across 4 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
Claude Sonnet 5 is clearly ahead on the BenchAlign aggregate, 65.32 to 43.87. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Sonnet 5's sharpest advantage is in coding, where it averages 76.7 against 27. Ling 2.6 Flash does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Claude Sonnet 5 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. Claude Sonnet 5 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 | Claude Sonnet 5 | Δ | Ling 2.6 Flash |
|---|---|---|---|
| Coding | Claude Sonnet 576.7 | Margin← 49.7 | Ling 2.6 Flash27.0 |
| Knowledge | Claude Sonnet 557.4 | Margin→ 1.6 | Ling 2.6 Flash59.0 |
| Agentic | Claude Sonnet 581.9 | MarginNo overlap | Ling 2.6 FlashNot measured |
| Multimodal | Claude Sonnet 588.3 | MarginNo overlap | Ling 2.6 FlashNot measured |
| Inst. Following | Claude Sonnet 5Not measured | MarginNo overlap | Ling 2.6 Flash57.0 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Sonnet 5 | Ling 2.6 Flash | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Sonnet 5$2 input / $10 output | Ling 2.6 FlashNot available | A complete price comparison is not available. |
| Generation speedtokens per second | Claude Sonnet 5Not available | Ling 2.6 Flash209.5 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Sonnet 5Not available | Ling 2.6 Flash1.07 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Sonnet 51M | Ling 2.6 Flash262K | Claude Sonnet 5 lists the larger context window. |
Benchmark Deep Dive
Agentic14 benchmarks
| Benchmark | Claude Sonnet 5 | Ling 2.6 Flash | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 80.4% | — | Not comparable |
| BrowseCompSource | 84.7% | — | Not comparable |
| HLE w/ toolsSource | 57.4% | — | Not comparable |
| OSWorld-VerifiedSource | 81.2% | — | Not comparable |
| GDPval-AASource | 1607 | 545 | Claude Sonnet 5 leads |
| AA Agentic IndexSource | 46.7% | 2.3% | Claude Sonnet 5 leads |
| GDPval-AASource | 55.4% | 2.2% | Claude Sonnet 5 leads |
| AA BriefcaseSource | 1388 | — | Not comparable |
| AA AutomationBenchSource | 39.2% | — | Not comparable |
| AA EnterpriseOps-GymSource | 44.7% | — | Not comparable |
| AA Harvey LABSource | 90.1% | — | Not comparable |
| AA Tau3 BankingSource | 28.2% | — | Not comparable |
| aaTerminalBench21Source | 80.5% | — | Not comparable |
| τ²-bench resultsSource | — | 86% | Not comparable |
CodingClaude Sonnet 5 wins10 benchmarks
| Benchmark | Claude Sonnet 5 | Ling 2.6 Flash | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 85.2% | — | Not comparable |
| SWE-bench ProSource | 63.2% | — | Not comparable |
| SWE MultilingualSource | 78.3% | — | Not comparable |
| SWE MultimodalSource | 28.1% | — | Not comparable |
| Terminal-Bench 2.0Source | 80.4% | — | Not comparable |
| FrontierCode 1.1 MainSource | 42.7% | — | Not comparable |
| cursorBench32Source | 61.5% | — | Not comparable |
| AA Coding IndexSource | 71.5% | 25.3% | Claude Sonnet 5 leads |
| AA-SciCodeSource | 53.6% | 27.1% | Claude Sonnet 5 leads |
| SciCodeSource | — | 27% | Not comparable |
Reasoning2 benchmarks
KnowledgeLing 2.6 Flash wins9 benchmarks
| Benchmark | Claude Sonnet 5 | Ling 2.6 Flash | Result |
|---|---|---|---|
| HLESource | 57.4% | — | Not comparable |
| HLE w/o toolsSource | 43.2% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 53.4% | 14.1% | Claude Sonnet 5 leads |
| AA-GPQA DiamondSource | 91.1% | 59.3% | Claude Sonnet 5 leads |
| AA-HLESource | 39.6% | 6.2% | Claude Sonnet 5 leads |
| AA-Omniscience IndexSource | 15.3% | -65.7% | Claude Sonnet 5 leads |
| AA-Omniscience AccuracySource | 38.3% | 15.4% | Claude Sonnet 5 leads |
| AA-Omniscience Hallucination RateSource | 37.3% | 95.8% | Claude Sonnet 5 leads |
| GPQASource | — | 59% | Not comparable |
Multimodal4 benchmarks
Frequently Asked Questions (3)
Which is better, Claude Sonnet 5 or Ling 2.6 Flash?
Claude Sonnet 5 is ahead on BenchLM's BenchAlign leaderboard, 65.32 to 43.87.
Which is better for knowledge tasks, Claude Sonnet 5 or Ling 2.6 Flash?
Ling 2.6 Flash has the edge for knowledge tasks in this comparison, averaging 59 versus 57.4. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.
Which is better for coding, Claude Sonnet 5 or Ling 2.6 Flash?
Claude Sonnet 5 has the edge for coding in this comparison, averaging 76.7 versus 27. Inside this category, AA Coding Index is the benchmark that creates the most daylight between them.
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