Model comparison
DeepSeek V4 Pro vs Qwen3.6-27B
Head-to-head evidence from 11 shared benchmark results across 4 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V4 Pro #46 (Supported); Qwen3.6-27B #93 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V4 Pro and Qwen3.6-27B share 11 comparable benchmark results. 4 of 8 categories are comparable. 12 results are unique to DeepSeek V4 Pro; 43 to Qwen3.6-27B.
Updated July 23, 2026- Shared results
- 11
- DeepSeek V4 Pro only
- 12
- Qwen3.6-27B only
- 43
- Comparable categories
- 4 / 8
Pick DeepSeek V4 Pro if you want the stronger benchmark profile. Qwen3.6-27B only becomes the better choice if mathematics is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 11 shared benchmark results across 4 evidence categories; 4 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 53.82. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
DeepSeek V4 Pro is also the more expensive model on tokens at $0.43 input / $0.87 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen3.6-27B. That is roughly Infinityx on output cost alone. Qwen3.6-27B is the reasoning model in the pair, while DeepSeek V4 Pro 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. DeepSeek V4 Pro gives you the larger context window at 1M, compared with 262K for Qwen3.6-27B.
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 | Qwen3.6-27B |
|---|---|---|---|
| Math | DeepSeek V4 Pro31.7 | Margin→ 57.5 | Qwen3.6-27B89.2 |
| Coding | DeepSeek V4 Pro65.3 | Margin→ 12.2 | Qwen3.6-27B77.5 |
| Knowledge | DeepSeek V4 Pro41.3 | Margin→ 12.0 | Qwen3.6-27B53.3 |
| Agentic | DeepSeek V4 Pro59.1 | Margin→ 0.2 | Qwen3.6-27B59.3 |
| Multimodal | DeepSeek V4 ProNot measured | MarginNo overlap | Qwen3.6-27B76.7 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
HMMT Feb 2026
MathA 31.7%B 84.3%Winner: Qwen3.6-27BΔ 52.6HMMT Feb 2026: DeepSeek V4 Pro scored 31.7%; Qwen3.6-27B scored 84.3%. Qwen3.6-27B wins this benchmark. - Source ↗
HLE
KnowledgeA 7.7%B 24%Winner: Qwen3.6-27BΔ 16.3HLE: DeepSeek V4 Pro scored 7.7%; Qwen3.6-27B scored 24%. Qwen3.6-27B wins this benchmark. - Source ↗
GPQA
KnowledgeA 72.9%B 87.8%Winner: Qwen3.6-27BΔ 14.9GPQA: DeepSeek V4 Pro scored 72.9%; Qwen3.6-27B scored 87.8%. Qwen3.6-27B wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 73.6%B 77.2%Winner: Qwen3.6-27BΔ 3.6SWE-bench Verified: DeepSeek V4 Pro scored 73.6%; Qwen3.6-27B scored 77.2%. Qwen3.6-27B wins this benchmark. - Source ↗
MMLU-Pro
KnowledgeA 82.9%B 86.2%Winner: Qwen3.6-27BΔ 3.3MMLU-Pro: DeepSeek V4 Pro scored 82.9%; Qwen3.6-27B scored 86.2%. Qwen3.6-27B wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V4 Pro | Qwen3.6-27B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Pro$0.435 input / $0.87 output | Qwen3.6-27B$0 input / $0 output | Qwen3.6-27B has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V4 ProNot available | Qwen3.6-27BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 ProNot available | Qwen3.6-27BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Pro1M | Qwen3.6-27B262K | DeepSeek V4 Pro lists the larger context window. |
Benchmark Deep Dive
AgenticQwen3.6-27B wins13 benchmarks
| Benchmark | DeepSeek V4 Pro | Qwen3.6-27B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 59.1% | 59.3% | Qwen3.6-27B leads |
| MCP AtlasSource | 69.4% | — | Not comparable |
| ToolathlonSource | 46.3% | — | Not comparable |
| Claw-EvalSource | 59.8% | 72.4% | Qwen3.6-27B leads |
| Gert LabsSource | 50.28% | 54.84% | Qwen3.6-27B leads |
| ResearchClawBenchSource | 17.1% | — | Not comparable |
| QwenClawBenchSource | — | 53.4% | Not comparable |
| QwenWebBenchSource | — | 1487 | Not comparable |
| AndroidWorldSource | — | 70.3% | Not comparable |
| AA Agentic IndexSource | — | 27.0% | Not comparable |
| τ²-bench resultsSource | — | 94.2% | Not comparable |
| GDPval-AASource | — | 32.0% | Not comparable |
| GDPval-AASource | — | 1140 | Not comparable |
CodingQwen3.6-27B wins8 benchmarks
| Benchmark | DeepSeek V4 Pro | Qwen3.6-27B | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 73.6% | 77.2% | Qwen3.6-27B leads |
| SWE-bench ProSource | 52.1% | 53.5% | Qwen3.6-27B leads |
| SWE MultilingualSource | 69.8% | 71.3% | Qwen3.6-27B leads |
| Terminal-Bench 2.0Source | 59.1% | 59.3% | Qwen3.6-27B leads |
| LiveCodeBenchSource | — | 83.9% | Not comparable |
| NL2RepoSource | — | 36.2% | Not comparable |
| AA Coding IndexSource | — | 53.7% | Not comparable |
| AA-SciCodeSource | — | 39.8% | Not comparable |
Reasoning4 benchmarks
KnowledgeQwen3.6-27B wins15 benchmarks
| Benchmark | DeepSeek V4 Pro | Qwen3.6-27B | Result |
|---|---|---|---|
| MMLU-ProSource | 82.9% | 86.2% | Qwen3.6-27B leads |
| SimpleQASource | 45% | — | Not comparable |
| Chinese-SimpleQASource | 75.8% | — | Not comparable |
| GPQASource | 72.9% | 87.8% | Qwen3.6-27B leads |
| GPQA-DSource | 72.9% | — | Not comparable |
| HLESource | 7.7% | 24% | Qwen3.6-27B leads |
| MMLU-ReduxSource | — | 93.5% | Not comparable |
| SuperGPQASource | — | 66% | Not comparable |
| C-EvalSource | — | 91.4% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 37.0% | Not comparable |
| AA-GPQA DiamondSource | — | 84.2% | Not comparable |
| AA-HLESource | — | 21.6% | Not comparable |
| AA-Omniscience IndexSource | — | -19.8% | Not comparable |
| AA-Omniscience AccuracySource | — | 19.2% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 48.3% | Not comparable |
MathQwen3.6-27B wins8 benchmarks
| Benchmark | DeepSeek V4 Pro | Qwen3.6-27B | Result |
|---|---|---|---|
| HMMT Feb 2026Source | 31.7% | 84.3% | Qwen3.6-27B leads |
| IMOAnswerBenchSource | 35.3% | — | Not comparable |
| ApexSource | 0.4% | — | Not comparable |
| Apex ShortlistSource | 9.2% | — | Not comparable |
| HMMT Feb 2025Source | — | 93.8% | Not comparable |
| HMMT Nov 2025Source | — | 90.7% | Not comparable |
| MMAnswerBenchSource | — | 80.8% | Not comparable |
| AIME26Source | — | 94.1% | Not comparable |
Multimodal17 benchmarks
| Benchmark | DeepSeek V4 Pro | Qwen3.6-27B | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1264 | — | Not comparable |
| MMMUSource | — | 82.9% | Not comparable |
| MMMU-ProSource | — | 75.8% | Not comparable |
| RealWorldQASource | — | 84.1% | Not comparable |
| DynaMathSource | — | 85.6% | Not comparable |
| MStarSource | — | 81.4% | Not comparable |
| SimpleVQASource | — | 56.1% | Not comparable |
| CharXivSource | — | 78.4% | Not comparable |
| CC-OCRSource | — | 81.2% | Not comparable |
| CountBenchSource | — | 97.8% | Not comparable |
| RefCOCO (avg)Source | — | 92.5% | Not comparable |
| ERQASource | — | 62.5% | Not comparable |
| Video-MME (with subtitle)Source | — | 87.7% | Not comparable |
| VideoMMMUSource | — | 84.4% | Not comparable |
| MLVU (M-Avg)Source | — | 86.6% | Not comparable |
| V*Source | — | 94.7% | Not comparable |
| AA-MMMU-ProSource | — | 74.6% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | DeepSeek V4 Pro | Qwen3.6-27B | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 67.6% | Not comparable |
Frequently Asked Questions (5)
Which is better, DeepSeek V4 Pro or Qwen3.6-27B?
DeepSeek V4 Pro is ahead on BenchLM's BenchAlign leaderboard, 60.66 to 53.82. The biggest single separator in this matchup is HMMT Feb 2026, where the scores are 31.7% and 84.3%.
Which is better for knowledge tasks, DeepSeek V4 Pro or Qwen3.6-27B?
Qwen3.6-27B has the edge for knowledge tasks in this comparison, averaging 53.3 versus 41.3. Inside this category, HLE is the benchmark that creates the most daylight between them.
Which is better for coding, DeepSeek V4 Pro or Qwen3.6-27B?
Qwen3.6-27B has the edge for coding in this comparison, averaging 77.5 versus 65.3. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Which is better for math, DeepSeek V4 Pro or Qwen3.6-27B?
Qwen3.6-27B has the edge for math in this comparison, averaging 89.2 versus 31.7. Inside this category, HMMT Feb 2026 is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, DeepSeek V4 Pro or Qwen3.6-27B?
Qwen3.6-27B has the edge for agentic tasks in this comparison, averaging 59.3 versus 59.1. Inside this category, Claw-Eval is the benchmark that creates the most daylight between them.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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