Model comparison
DeepSeek V4 Pro vs Ling 2.6 Flash
Head-to-head evidence from 1 shared benchmark result across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V4 Pro #46 (Supported); Ling 2.6 Flash #154 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V4 Pro and Ling 2.6 Flash share 1 comparable benchmark result. 2 of 8 categories are comparable. 22 results are unique to DeepSeek V4 Pro; 17 to Ling 2.6 Flash.
Updated July 23, 2026- Shared results
- 1
- DeepSeek V4 Pro only
- 22
- Ling 2.6 Flash only
- 17
- Comparable categories
- 2 / 8
Pick DeepSeek V4 Pro if you want the stronger benchmark profile. Ling 2.6 Flash only becomes the better choice if knowledge is the priority.
Confidence note. This is a partial-evidence comparison with 1 shared benchmark result across 1 evidence category; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
DeepSeek V4 Pro is clearly ahead on the BenchAlign aggregate, 60.66 to 43.87. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
DeepSeek V4 Pro's sharpest advantage is in coding, where it averages 65.3 against 27. The single biggest benchmark swing on the page is GPQA, 72.9% to 59%. 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.
DeepSeek V4 Pro 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 | DeepSeek V4 Pro | Δ | Ling 2.6 Flash |
|---|---|---|---|
| Coding | DeepSeek V4 Pro65.3 | Margin← 38.3 | Ling 2.6 Flash27.0 |
| Knowledge | DeepSeek V4 Pro41.3 | Margin→ 17.7 | Ling 2.6 Flash59.0 |
| Agentic | DeepSeek V4 Pro59.1 | MarginNo overlap | Ling 2.6 FlashNot measured |
| Math | DeepSeek V4 Pro31.7 | MarginNo overlap | Ling 2.6 FlashNot measured |
| Inst. Following | DeepSeek V4 ProNot 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 72.9%B 59%Winner: DeepSeek V4 ProΔ 13.9GPQA: DeepSeek V4 Pro scored 72.9%; Ling 2.6 Flash scored 59%. DeepSeek V4 Pro wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V4 Pro | Ling 2.6 Flash | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Pro$0.435 input / $0.87 output | Ling 2.6 FlashNot available | A complete price comparison is not available. |
| Generation speedtokens per second | DeepSeek V4 ProNot available | Ling 2.6 Flash209.5 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 ProNot available | Ling 2.6 Flash1.07 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Pro1M | Ling 2.6 Flash262K | DeepSeek V4 Pro lists the larger context window. |
Benchmark Deep Dive
Agentic10 benchmarks
| Benchmark | DeepSeek V4 Pro | Ling 2.6 Flash | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 59.1% | — | Not comparable |
| MCP AtlasSource | 69.4% | — | Not comparable |
| ToolathlonSource | 46.3% | — | Not comparable |
| Claw-EvalSource | 59.8% | — | Not comparable |
| Gert LabsSource | 50.28% | — | Not comparable |
| ResearchClawBenchSource | 17.1% | — | Not comparable |
| τ²-bench resultsSource | — | 86% | Not comparable |
| GDPval-AASource | — | 2.2% | Not comparable |
| GDPval-AASource | — | 545 | Not comparable |
| AA Agentic IndexSource | — | 2.3% | Not comparable |
CodingDeepSeek V4 Pro wins7 benchmarks
| Benchmark | DeepSeek V4 Pro | Ling 2.6 Flash | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 73.6% | — | Not comparable |
| SWE-bench ProSource | 52.1% | — | Not comparable |
| SWE MultilingualSource | 69.8% | — | Not comparable |
| Terminal-Bench 2.0Source | 59.1% | — | Not comparable |
| SciCodeSource | — | 27% | Not comparable |
| AA Coding IndexSource | — | 25.3% | Not comparable |
| AA-SciCodeSource | — | 27.1% | Not comparable |
Reasoning4 benchmarks
KnowledgeLing 2.6 Flash wins12 benchmarks
| Benchmark | DeepSeek V4 Pro | Ling 2.6 Flash | Result |
|---|---|---|---|
| MMLU-ProSource | 82.9% | — | Not comparable |
| SimpleQASource | 45% | — | Not comparable |
| Chinese-SimpleQASource | 75.8% | — | Not comparable |
| GPQASource | 72.9% | 59% | DeepSeek V4 Pro leads |
| GPQA-DSource | 72.9% | — | Not comparable |
| HLESource | 7.7% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 14.1% | Not comparable |
| AA-GPQA DiamondSource | — | 59.3% | Not comparable |
| AA-HLESource | — | 6.2% | Not comparable |
| AA-Omniscience IndexSource | — | -65.7% | Not comparable |
| AA-Omniscience AccuracySource | — | 15.4% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 95.8% | Not comparable |
Math4 benchmarks
Multimodal1 benchmarks
| Benchmark | DeepSeek V4 Pro | Ling 2.6 Flash | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1264 | — | Not comparable |
Frequently Asked Questions (3)
Which is better, DeepSeek V4 Pro or Ling 2.6 Flash?
DeepSeek V4 Pro is ahead on BenchLM's BenchAlign leaderboard, 60.66 to 43.87. The biggest single separator in this matchup is GPQA, where the scores are 72.9% and 59%.
Which is better for knowledge tasks, DeepSeek V4 Pro or Ling 2.6 Flash?
Ling 2.6 Flash has the edge for knowledge tasks in this comparison, averaging 59 versus 41.3. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Which is better for coding, DeepSeek V4 Pro or Ling 2.6 Flash?
DeepSeek V4 Pro has the edge for coding in this comparison, averaging 65.3 versus 27. Ling 2.6 Flash stays close enough that the answer can still flip depending on your workload.
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