Model comparison
Ling 2.6 Flash vs Qwen3.5 397B (Reasoning)
Head-to-head evidence from 15 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); Qwen3.5 397B (Reasoning) #56 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Ling 2.6 Flash and Qwen3.5 397B (Reasoning) share 15 comparable benchmark results. 0 of 8 categories are comparable. 3 results are unique to Ling 2.6 Flash; 2 to Qwen3.5 397B (Reasoning).
Updated July 21, 2026- Shared results
- 15
- Ling 2.6 Flash only
- 3
- Qwen3.5 397B (Reasoning) only
- 2
- Comparable categories
- 0 / 8
Benchmark data for Ling 2.6 Flash and Qwen3.5 397B (Reasoning) is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 15 shared benchmark results across 5 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
Ling 2.6 Flash has the larger context window at 262K, compared with 128K for Qwen3.5 397B (Reasoning).
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 | Qwen3.5 397B (Reasoning) |
|---|---|---|---|
| Coding | Ling 2.6 Flash27.0 | MarginNo overlap | Qwen3.5 397B (Reasoning)Not measured |
| Knowledge | Ling 2.6 Flash59.0 | MarginNo overlap | Qwen3.5 397B (Reasoning)Not measured |
| Inst. Following | Ling 2.6 Flash57.0 | MarginNo overlap | Qwen3.5 397B (Reasoning)Not measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Ling 2.6 Flash | Qwen3.5 397B (Reasoning) | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Ling 2.6 FlashNot available | Qwen3.5 397B (Reasoning)$0.6 input / $3.6 output | A complete price comparison is not available. |
| Generation speedtokens per second | Ling 2.6 Flash209.5 tok/s | Qwen3.5 397B (Reasoning)Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Ling 2.6 Flash1.07 s | Qwen3.5 397B (Reasoning)Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Ling 2.6 Flash262K | Qwen3.5 397B (Reasoning)128K | Ling 2.6 Flash lists the larger context window. |
Benchmark Deep Dive
Agentic5 benchmarks
| Benchmark | Ling 2.6 Flash | Qwen3.5 397B (Reasoning) | Result |
|---|---|---|---|
| τ²-bench resultsSource | 86% | 95.6% | Qwen3.5 397B (Reasoning) leads |
| GDPval-AASource | 2.2% | 23.1% | Qwen3.5 397B (Reasoning) leads |
| GDPval-AASource | 545 | 962 | Qwen3.5 397B (Reasoning) leads |
| AA Agentic IndexSource | 2.3% | 19.9% | Qwen3.5 397B (Reasoning) leads |
| APEX-Agents-AASource | — | 15.3% | Not comparable |
Coding3 benchmarks
Reasoning2 benchmarks
Knowledge7 benchmarks
| Benchmark | Ling 2.6 Flash | Qwen3.5 397B (Reasoning) | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 14.1% | 33.7% | Qwen3.5 397B (Reasoning) leads |
| GPQASource | 59% | — | Not comparable |
| AA-GPQA DiamondSource | 59.3% | 89.3% | Qwen3.5 397B (Reasoning) leads |
| AA-HLESource | 6.2% | 27.3% | Qwen3.5 397B (Reasoning) leads |
| AA-Omniscience IndexSource | -65.7% | -29.8% | Qwen3.5 397B (Reasoning) leads |
| AA-Omniscience AccuracySource | 15.4% | 31.4% | Qwen3.5 397B (Reasoning) leads |
| AA-Omniscience Hallucination RateSource | 95.8% | 89.1% | Qwen3.5 397B (Reasoning) leads |
Multimodal1 benchmarks
| Benchmark | Ling 2.6 Flash | Qwen3.5 397B (Reasoning) | Result |
|---|---|---|---|
| AA-MMMU-ProSource | — | 77.3% | Not comparable |
Frequently Asked Questions (3)
Can I compare Ling 2.6 Flash and Qwen3.5 397B (Reasoning) on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for Ling 2.6 Flash and Qwen3.5 397B (Reasoning) today?
Ling 2.6 Flash: Pricing unavailable Qwen3.5 397B (Reasoning): $0.60 input / $3.60 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
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