Model comparison
DeepSeek V4 Flash vs Qwen3.5-27B
Head-to-head evidence from 5 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V4 Flash #61 (Estimated); Qwen3.5-27B #45 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V4 Flash and Qwen3.5-27B share 5 comparable benchmark results. 3 of 8 categories are comparable. 17 results are unique to DeepSeek V4 Flash; 23 to Qwen3.5-27B.
Updated July 23, 2026- Shared results
- 5
- DeepSeek V4 Flash only
- 17
- Qwen3.5-27B only
- 23
- Comparable categories
- 3 / 8
Pick Qwen3.5-27B if you want the stronger benchmark profile. DeepSeek V4 Flash only becomes the better choice if you need the larger 1M context window or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 5 shared benchmark results across 3 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
Qwen3.5-27B has the cleaner BenchAlign overall profile here, landing at 60.7 versus 58.88. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Qwen3.5-27B's sharpest advantage is in knowledge, where it averages 82.7 against 38.8. The single biggest benchmark swing on the page is GPQA, 71.2% to 85.5%.
DeepSeek V4 Flash is also the more expensive model on tokens at $0.14 input / $0.28 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen3.5-27B. That is roughly Infinityx on output cost alone. Qwen3.5-27B is the reasoning model in the pair, while DeepSeek V4 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. DeepSeek V4 Flash gives you the larger context window at 1M, compared with 262K for Qwen3.5-27B.
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 Flash | Δ | Qwen3.5-27B |
|---|---|---|---|
| Knowledge | DeepSeek V4 Flash38.8 | Margin→ 43.9 | Qwen3.5-27B82.7 |
| Agentic | DeepSeek V4 Flash49.1 | Margin→ 2.9 | Qwen3.5-27B52.0 |
| Coding | DeepSeek V4 Flash64.2 | Margin→ 0.7 | Qwen3.5-27B64.9 |
| Reasoning | DeepSeek V4 FlashNot measured | MarginNo overlap | Qwen3.5-27B60.6 |
| Math | DeepSeek V4 Flash40.8 | MarginNo overlap | Qwen3.5-27BNot measured |
| Multilingual | DeepSeek V4 FlashNot measured | MarginNo overlap | Qwen3.5-27B82.2 |
| Inst. Following | DeepSeek V4 FlashNot measured | MarginNo overlap | Qwen3.5-27B95.0 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
GPQA
KnowledgeA 71.2%B 85.5%Winner: Qwen3.5-27BΔ 14.3GPQA: DeepSeek V4 Flash scored 71.2%; Qwen3.5-27B scored 85.5%. Qwen3.5-27B wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 49.1%B 41.6%Winner: DeepSeek V4 FlashΔ 7.5Terminal-Bench 2.0: DeepSeek V4 Flash scored 49.1%; Qwen3.5-27B scored 41.6%. DeepSeek V4 Flash wins this benchmark. - Source ↗
MMLU-Pro
KnowledgeA 83%B 86.1%Winner: Qwen3.5-27BΔ 3.1MMLU-Pro: DeepSeek V4 Flash scored 83%; Qwen3.5-27B scored 86.1%. Qwen3.5-27B wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 73.7%B 72.4%Winner: DeepSeek V4 FlashΔ 1.3SWE-bench Verified: DeepSeek V4 Flash scored 73.7%; Qwen3.5-27B scored 72.4%. DeepSeek V4 Flash wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V4 Flash | Qwen3.5-27B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Flash$0.14 input / $0.28 output | Qwen3.5-27B$0 input / $0 output | Qwen3.5-27B has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V4 FlashNot available | Qwen3.5-27BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 FlashNot available | Qwen3.5-27BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Flash1M | Qwen3.5-27B262K | DeepSeek V4 Flash lists the larger context window. |
Benchmark Deep Dive
AgenticQwen3.5-27B wins8 benchmarks
| Benchmark | DeepSeek V4 Flash | Qwen3.5-27B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 49.1% | 41.6% | DeepSeek V4 Flash leads |
| MCP AtlasSource | 64% | — | Not comparable |
| ToolathlonSource | 40.7% | — | Not comparable |
| Claw-EvalSource | 57.8% | — | Not comparable |
| Gert LabsSource | 54.35% | 39.41% | DeepSeek V4 Flash leads |
| BrowseCompSource | — | 61% | Not comparable |
| OSWorld-VerifiedSource | — | 56.2% | Not comparable |
| τ²-bench resultsSource | — | 93.9% | Not comparable |
CodingQwen3.5-27B wins6 benchmarks
| Benchmark | DeepSeek V4 Flash | Qwen3.5-27B | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 73.7% | 72.4% | DeepSeek V4 Flash leads |
| SWE-bench ProSource | 49.1% | — | Not comparable |
| SWE MultilingualSource | 69.7% | — | Not comparable |
| Terminal-Bench 2.0Source | 49.1% | — | Not comparable |
| SWE-RebenchSource | — | 58.9% | Not comparable |
| AA-SciCodeSource | — | 39.5% | Not comparable |
Reasoning5 benchmarks
KnowledgeQwen3.5-27B wins13 benchmarks
| Benchmark | DeepSeek V4 Flash | Qwen3.5-27B | Result |
|---|---|---|---|
| MMLU-ProSource | 83% | 86.1% | Qwen3.5-27B leads |
| SimpleQASource | 23.1% | — | Not comparable |
| Chinese-SimpleQASource | 71.5% | — | Not comparable |
| GPQASource | 71.2% | 85.5% | Qwen3.5-27B leads |
| GPQA-DSource | 71.2% | — | Not comparable |
| HLESource | 8.1% | — | Not comparable |
| SuperGPQASource | — | 65.6% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 33.8% | Not comparable |
| AA-GPQA DiamondSource | — | 85.8% | Not comparable |
| AA-HLESource | — | 22.2% | Not comparable |
| AA-Omniscience IndexSource | — | -42.0% | Not comparable |
| AA-Omniscience AccuracySource | — | 21.0% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 79.7% | Not comparable |
Math4 benchmarks
Multilingual1 benchmarks
| Benchmark | DeepSeek V4 Flash | Qwen3.5-27B | Result |
|---|---|---|---|
| MMLU-ProXSource | — | 82.2% | Not comparable |
Multimodal6 benchmarks
Frequently Asked Questions (4)
Which is better, DeepSeek V4 Flash or Qwen3.5-27B?
Qwen3.5-27B is ahead on BenchLM's BenchAlign leaderboard, 60.7 to 58.88. The biggest single separator in this matchup is GPQA, where the scores are 71.2% and 85.5%.
Which is better for knowledge tasks, DeepSeek V4 Flash or Qwen3.5-27B?
Qwen3.5-27B has the edge for knowledge tasks in this comparison, averaging 82.7 versus 38.8. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Which is better for coding, DeepSeek V4 Flash or Qwen3.5-27B?
Qwen3.5-27B has the edge for coding in this comparison, averaging 64.9 versus 64.2. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, DeepSeek V4 Flash or Qwen3.5-27B?
Qwen3.5-27B has the edge for agentic tasks in this comparison, averaging 52 versus 49.1. Inside this category, Gert Labs is the benchmark that creates the most daylight between them.
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