Model comparison
Ling 2.6 Flash vs Qwen3.7 Plus
Head-to-head evidence from 18 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Ling 2.6 Flash #154 (Estimated); Qwen3.7 Plus #21 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Ling 2.6 Flash and Qwen3.7 Plus share 18 comparable benchmark results. 3 of 8 categories are comparable. 0 results are unique to Ling 2.6 Flash; 51 to Qwen3.7 Plus.
Updated July 23, 2026- Shared results
- 18
- Ling 2.6 Flash only
- 0
- Qwen3.7 Plus only
- 51
- Comparable categories
- 3 / 8
Pick Qwen3.7 Plus 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 18 shared benchmark results across 5 evidence categories; 3 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Qwen3.7 Plus is clearly ahead on the BenchAlign aggregate, 67.22 to 43.87. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.7 Plus's sharpest advantage is in coding, where it averages 75.6 against 27. The single biggest benchmark swing on the page is GPQA, 59% to 90.3%.
Qwen3.7 Plus 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. Qwen3.7 Plus 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 | Ling 2.6 Flash | Δ | Qwen3.7 Plus |
|---|---|---|---|
| Coding | Ling 2.6 Flash27.0 | Margin→ 48.6 | Qwen3.7 Plus75.6 |
| Inst. Following | Ling 2.6 Flash57.0 | Margin→ 27.5 | Qwen3.7 Plus84.5 |
| Knowledge | Ling 2.6 Flash59.0 | Margin→ 1.1 | Qwen3.7 Plus60.1 |
| Agentic | Ling 2.6 FlashNot measured | MarginNo overlap | Qwen3.7 Plus71.7 |
| Reasoning | Ling 2.6 FlashNot measured | MarginNo overlap | Qwen3.7 Plus91.7 |
| Math | Ling 2.6 FlashNot measured | MarginNo overlap | Qwen3.7 Plus92.9 |
| Multilingual | Ling 2.6 FlashNot measured | MarginNo overlap | Qwen3.7 Plus85.4 |
| Multimodal | Ling 2.6 FlashNot measured | MarginNo overlap | Qwen3.7 Plus81.5 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
GPQA
KnowledgeA 59%B 90.3%Winner: Qwen3.7 PlusΔ 31.3GPQA: Ling 2.6 Flash scored 59%; Qwen3.7 Plus scored 90.3%. Qwen3.7 Plus wins this benchmark. - Source ↗
SciCode
CodingA 27%B 51.3%Winner: Qwen3.7 PlusΔ 24.3SciCode: Ling 2.6 Flash scored 27%; Qwen3.7 Plus scored 51.3%. Qwen3.7 Plus wins this benchmark. - Source ↗
IFBench
Inst. FollowingA 57%B 79.1%Winner: Qwen3.7 PlusΔ 22.1IFBench: Ling 2.6 Flash scored 57%; Qwen3.7 Plus scored 79.1%. Qwen3.7 Plus wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Ling 2.6 Flash | Qwen3.7 Plus | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Ling 2.6 FlashNot available | Qwen3.7 PlusNot available | A complete price comparison is not available. |
| Generation speedtokens per second | Ling 2.6 Flash209.5 tok/s | Qwen3.7 PlusNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Ling 2.6 Flash1.07 s | Qwen3.7 PlusNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Ling 2.6 Flash262K | Qwen3.7 Plus1M | Qwen3.7 Plus lists the larger context window. |
Benchmark Deep Dive
Agentic16 benchmarks
| Benchmark | Ling 2.6 Flash | Qwen3.7 Plus | Result |
|---|---|---|---|
| τ²-bench resultsSource | 86% | 93% | Qwen3.7 Plus leads |
| GDPval-AASource | 2.2% | 21.8% | Qwen3.7 Plus leads |
| GDPval-AASource | 545 | 936 | Qwen3.7 Plus leads |
| AA Agentic IndexSource | 2.3% | 20.8% | Qwen3.7 Plus leads |
| Terminal-Bench 2.0Source | — | 70.3% | Not comparable |
| QwenClawBenchSource | — | 61.8% | Not comparable |
| QwenWebBenchSource | — | 1536 | Not comparable |
| Claw-EvalSource | — | 62.7% | Not comparable |
| BFCL v4Source | — | 72.9% | Not comparable |
| MCP AtlasSource | — | 73.2% | Not comparable |
| VITA-BenchSource | — | 45.6% | Not comparable |
| DeepPlanningSource | — | 62.3% | Not comparable |
| OSWorld-VerifiedSource | — | 73.3% | Not comparable |
| AndroidWorldSource | — | 81.0% | Not comparable |
| APEX-Agents-AASource | — | 22.4% | Not comparable |
| OSWorld 2.0Source | — | 2.8% | Not comparable |
CodingQwen3.7 Plus wins9 benchmarks
| Benchmark | Ling 2.6 Flash | Qwen3.7 Plus | Result |
|---|---|---|---|
| SciCodeSource | 27% | 51.3% | Qwen3.7 Plus leads |
| AA Coding IndexSource | 25.3% | 55.9% | Qwen3.7 Plus leads |
| AA-SciCodeSource | 27.1% | 45.5% | Qwen3.7 Plus leads |
| Terminal-Bench 2.0Source | — | 70.3% | Not comparable |
| SWE-bench VerifiedSource | — | 77.7% | Not comparable |
| SWE-bench ProSource | — | 57.6% | Not comparable |
| SWE MultilingualSource | — | 75.8% | Not comparable |
| NL2RepoSource | — | 41.1% | Not comparable |
| LiveCodeBenchSource | — | 89.6% | Not comparable |
Reasoning3 benchmarks
KnowledgeQwen3.7 Plus wins13 benchmarks
| Benchmark | Ling 2.6 Flash | Qwen3.7 Plus | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 14.1% | 39.0% | Qwen3.7 Plus leads |
| GPQASource | 59% | 90.3% | Qwen3.7 Plus leads |
| AA-GPQA DiamondSource | 59.3% | 90.0% | Qwen3.7 Plus leads |
| AA-HLESource | 6.2% | 33.4% | Qwen3.7 Plus leads |
| AA-Omniscience IndexSource | -65.7% | 2.4% | Qwen3.7 Plus leads |
| AA-Omniscience AccuracySource | 15.4% | 22.2% | Qwen3.7 Plus leads |
| AA-Omniscience Hallucination RateSource | 95.8% | 25.5% | Qwen3.7 Plus leads |
| GPQA-DSource | — | 90.3% | Not comparable |
| HLESource | — | 34.7% | Not comparable |
| MMLU-ProSource | — | 88.5% | Not comparable |
| MMLU-ReduxSource | — | 94.5% | Not comparable |
| SuperGPQASource | — | 71.4% | Not comparable |
| MMMLUSource | — | 89.0% | Not comparable |
Math3 benchmarks
Multilingual5 benchmarks
Multimodal17 benchmarks
| Benchmark | Ling 2.6 Flash | Qwen3.7 Plus | Result |
|---|---|---|---|
| MMMU-ProSource | — | 79% | Not comparable |
| MathVisionSource | — | 90.3% | Not comparable |
| CharXivSource | — | 85.9% | Not comparable |
| ERQASource | — | 69.8% | Not comparable |
| MedXpertQA (MM)Source | — | 71.0% | Not comparable |
| ScreenSpot ProSource | — | 79.0% | Not comparable |
| SimpleVQASource | — | 81.7% | Not comparable |
| MMSearch-PlusSource | — | 41.4% | Not comparable |
| RealWorldQASource | — | 86.9% | Not comparable |
| OmniDocBench 1.5Source | — | 91.4% | Not comparable |
| OCRBench V2Source | — | 70.7% | Not comparable |
| ODINW13Source | — | 51.1% | Not comparable |
| Video-MME (with subtitle)Source | — | 88.0% | Not comparable |
| VideoMMMUSource | — | 85.4% | Not comparable |
| MLVU (M-Avg)Source | — | 87.4% | Not comparable |
| AA-MMMU-ProSource | — | 80.5% | Not comparable |
| Design Arena WebsiteSource | — | 1288 | Not comparable |
Frequently Asked Questions (4)
Which is better, Ling 2.6 Flash or Qwen3.7 Plus?
Qwen3.7 Plus is ahead on BenchLM's BenchAlign leaderboard, 67.22 to 43.87. The biggest single separator in this matchup is GPQA, where the scores are 59% and 90.3%.
Which is better for knowledge tasks, Ling 2.6 Flash or Qwen3.7 Plus?
Qwen3.7 Plus has the edge for knowledge tasks in this comparison, averaging 60.1 versus 59. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.
Which is better for coding, Ling 2.6 Flash or Qwen3.7 Plus?
Qwen3.7 Plus has the edge for coding in this comparison, averaging 75.6 versus 27. Inside this category, AA Coding Index is the benchmark that creates the most daylight between them.
Which is better for instruction following, Ling 2.6 Flash or Qwen3.7 Plus?
Qwen3.7 Plus has the edge for instruction following in this comparison, averaging 84.5 versus 57. Inside this category, IFBench is the benchmark that creates the most daylight between them.
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