Model comparison
DeepSeek V3 vs Qwen3.6-27B
Head-to-head evidence from 19 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V3 #147 (Supported); Qwen3.6-27B #93 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V3 and Qwen3.6-27B share 19 comparable benchmark results. 3 of 8 categories are comparable. 3 results are unique to DeepSeek V3; 35 to Qwen3.6-27B.
Updated July 21, 2026- Shared results
- 19
- DeepSeek V3 only
- 3
- Qwen3.6-27B only
- 35
- Comparable categories
- 3 / 8
Pick Qwen3.6-27B if you want the stronger benchmark profile. DeepSeek V3 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 19 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
Qwen3.6-27B is clearly ahead on the BenchAlign aggregate, 53.82 to 44.97. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.6-27B's sharpest advantage is in mathematics, where it averages 89.2 against 1.7. The single biggest benchmark swing on the page is LiveCodeBench, 37.6% to 83.9%. DeepSeek V3 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
DeepSeek V3 is also the more expensive model on tokens at $0.27 input / $1.10 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 V3 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. Qwen3.6-27B gives you the larger context window at 262K, compared with 128K for DeepSeek V3.
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 V3 | Δ | Qwen3.6-27B |
|---|---|---|---|
| Math | DeepSeek V31.7 | Margin→ 87.5 | Qwen3.6-27B89.2 |
| Coding | DeepSeek V338.9 | Margin→ 38.6 | Qwen3.6-27B77.5 |
| Knowledge | DeepSeek V372.7 | Margin← 19.4 | Qwen3.6-27B53.3 |
| Agentic | DeepSeek V3Not measured | MarginNo overlap | Qwen3.6-27B59.3 |
| Multimodal | DeepSeek V3Not measured | MarginNo overlap | Qwen3.6-27B76.7 |
| Inst. Following | DeepSeek V386.1 | MarginNo overlap | Qwen3.6-27BNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
LiveCodeBench
CodingA 37.6%B 83.9%Winner: Qwen3.6-27BΔ 46.3LiveCodeBench: DeepSeek V3 scored 37.6%; Qwen3.6-27B scored 83.9%. Qwen3.6-27B wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 42%B 77.2%Winner: Qwen3.6-27BΔ 35.2SWE-bench Verified: DeepSeek V3 scored 42%; Qwen3.6-27B scored 77.2%. Qwen3.6-27B wins this benchmark. - Source ↗
GPQA
KnowledgeA 59.1%B 87.8%Winner: Qwen3.6-27BΔ 28.7GPQA: DeepSeek V3 scored 59.1%; Qwen3.6-27B scored 87.8%. Qwen3.6-27B wins this benchmark. - Source ↗
MMLU-Pro
KnowledgeA 75.9%B 86.2%Winner: Qwen3.6-27BΔ 10.3MMLU-Pro: DeepSeek V3 scored 75.9%; 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 V3 | Qwen3.6-27B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V3$0.27 input / $1.1 output | Qwen3.6-27B$0 input / $0 output | Qwen3.6-27B has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V3Not available | Qwen3.6-27BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V3Not available | Qwen3.6-27BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V3128K | Qwen3.6-27B262K | Qwen3.6-27B lists the larger context window. |
Benchmark Deep Dive
Agentic10 benchmarks
| Benchmark | DeepSeek V3 | Qwen3.6-27B | Result |
|---|---|---|---|
| AA Agentic IndexSource | 1.6% | 27.0% | Qwen3.6-27B leads |
| τ²-bench resultsSource | 22.8% | 94.2% | Qwen3.6-27B leads |
| GDPval-AASource | 0.0% | 32.0% | Qwen3.6-27B leads |
| GDPval-AASource | 217 | 1140 | Qwen3.6-27B leads |
| Terminal-Bench 2.0Source | — | 59.3% | Not comparable |
| Claw-EvalSource | — | 72.4% | Not comparable |
| QwenClawBenchSource | — | 53.4% | Not comparable |
| QwenWebBenchSource | — | 1487 | Not comparable |
| AndroidWorldSource | — | 70.3% | Not comparable |
| Gert LabsSource | — | 54.84% | Not comparable |
CodingQwen3.6-27B wins8 benchmarks
| Benchmark | DeepSeek V3 | Qwen3.6-27B | Result |
|---|---|---|---|
| LiveCodeBenchSource | 37.6% | 83.9% | Qwen3.6-27B leads |
| SWE-bench VerifiedSource | 42% | 77.2% | Qwen3.6-27B leads |
| AA Coding IndexSource | 23.0% | 53.7% | Qwen3.6-27B leads |
| AA-SciCodeSource | 35.4% | 39.8% | Qwen3.6-27B leads |
| SWE MultilingualSource | — | 71.3% | Not comparable |
| SWE-bench ProSource | — | 53.5% | Not comparable |
| Terminal-Bench 2.0Source | — | 59.3% | Not comparable |
| NL2RepoSource | — | 36.2% | Not comparable |
Reasoning2 benchmarks
KnowledgeDeepSeek V3 wins12 benchmarks
| Benchmark | DeepSeek V3 | Qwen3.6-27B | Result |
|---|---|---|---|
| GPQASource | 59.1% | 87.8% | Qwen3.6-27B leads |
| MMLU-ProSource | 75.9% | 86.2% | Qwen3.6-27B leads |
| Artificial Analysis Intelligence IndexSource | 14.2% | 37.0% | Qwen3.6-27B leads |
| AA-GPQA DiamondSource | 55.7% | 84.2% | Qwen3.6-27B leads |
| AA-HLESource | 3.6% | 21.6% | Qwen3.6-27B leads |
| AA-Omniscience IndexSource | -41.3% | -19.8% | Qwen3.6-27B leads |
| AA-Omniscience AccuracySource | 25.4% | 19.2% | DeepSeek V3 leads |
| AA-Omniscience Hallucination RateSource | 89.4% | 48.3% | Qwen3.6-27B leads |
| MMLU-ReduxSource | — | 93.5% | Not comparable |
| SuperGPQASource | — | 66% | Not comparable |
| C-EvalSource | — | 91.4% | Not comparable |
| HLESource | — | 24% | Not comparable |
MathQwen3.6-27B wins6 benchmarks
Multimodal17 benchmarks
| Benchmark | DeepSeek V3 | Qwen3.6-27B | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1150 | — | 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 |
Frequently Asked Questions (4)
Which is better, DeepSeek V3 or Qwen3.6-27B?
Qwen3.6-27B is ahead on BenchLM's BenchAlign leaderboard, 53.82 to 44.97. The biggest single separator in this matchup is LiveCodeBench, where the scores are 37.6% and 83.9%.
Which is better for knowledge tasks, DeepSeek V3 or Qwen3.6-27B?
DeepSeek V3 has the edge for knowledge tasks in this comparison, averaging 72.7 versus 53.3. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.
Which is better for coding, DeepSeek V3 or Qwen3.6-27B?
Qwen3.6-27B has the edge for coding in this comparison, averaging 77.5 versus 38.9. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
Which is better for math, DeepSeek V3 or Qwen3.6-27B?
Qwen3.6-27B has the edge for math in this comparison, averaging 89.2 versus 1.7. DeepSeek V3 stays close enough that the answer can still flip depending on your workload.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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