Compare · ModelsLive · 2 picked · head to head
DeepSeek V4 Flash vs Qwen3.6 27B
Side by side · benchmarks, pricing, and signals you can act on.
Winner summary
DeepSeek V4 Flash wins on 8/11 benchmarks
DeepSeek V4 Flash wins 8 of 11 shared benchmarks. Leads in speed · coding · language.
Category leads
speed·DeepSeek V4 Flashcoding·DeepSeek V4 Flashreasoning·Qwen3.6 27Blanguage·DeepSeek V4 Flashmath·Qwen3.6 27Bknowledge·DeepSeek V4 Flash
Hype vs Reality
Attention vs performance
DeepSeek V4 Flash
#31 by perf·no signal
Qwen3.6 27B
#36 by perf·no signal
Best value
DeepSeek V4 Flash
10.9x better value than Qwen3.6 27B
DeepSeek V4 Flash
533.3 pts/$
$0.13/M
Qwen3.6 27B
48.9 pts/$
$1.34/M
Vendor risk
Mixed exposure
One or more vendors flagged
DeepSeek
$3.4B·Tier 1
Alibaba (Qwen)
$293.0B·Tier 1
Head to head
11 benchmarks · 2 models
DeepSeek V4 FlashQwen3.6 27B
Artificial Analysis · Agentic Index
DeepSeek V4 Flash leads by +4.0
Artificial Analysis Agentic Index · a composite score measuring how well a model performs in agentic workflows · multi-step tool use, planning, error recovery, and autonomous task completion. Aggregates results from multiple agentic benchmarks including SWE-bench, tool-use tests, and planning evaluations. The canonical single-number metric for "how good is this model as an agent?"
DeepSeek V4 Flash
31.1
Qwen3.6 27B
27.0
Artificial Analysis · Coding Index
DeepSeek V4 Flash leads by +2.5
Artificial Analysis Coding Index · a composite score that aggregates performance across multiple coding benchmarks into a single index. Tracks code generation quality, debugging ability, multi-language competence, and real-world software engineering tasks. Used by Artificial Analysis to rank model coding capability in a normalized, comparable format. Useful for developers choosing between models for coding-heavy workloads.
DeepSeek V4 Flash
56.2
Qwen3.6 27B
53.7
Artificial Analysis · Quality Index
DeepSeek V4 Flash leads by +3.2
DeepSeek V4 Flash
40.3
Qwen3.6 27B
37.0
LiveBench · Agentic Coding
DeepSeek V4 Flash
50.0
Qwen3.6 27B
50.0
LiveBench · Coding
Qwen3.6 27B leads by +2.6
DeepSeek V4 Flash
69.2
Qwen3.6 27B
71.8
LiveBench · Data Analysis
Qwen3.6 27B leads by +2.4
DeepSeek V4 Flash
68.0
Qwen3.6 27B
70.4
LiveBench · If
DeepSeek V4 Flash leads by +9.9
DeepSeek V4 Flash
63.1
Qwen3.6 27B
53.2
LiveBench · Language
DeepSeek V4 Flash leads by +6.8
DeepSeek V4 Flash
70.1
Qwen3.6 27B
63.3
LiveBench · Mathematics
Qwen3.6 27B leads by +0.2
DeepSeek V4 Flash
79.7
Qwen3.6 27B
79.9
LiveBench · Overall
DeepSeek V4 Flash leads by +1.7
DeepSeek V4 Flash
67.3
Qwen3.6 27B
65.6
LiveBench · Reasoning
DeepSeek V4 Flash leads by +0.3
DeepSeek V4 Flash
70.6
Qwen3.6 27B
70.3
Full benchmark table
| Benchmark | DeepSeek V4 Flash | Qwen3.6 27B |
|---|---|---|
Artificial Analysis · Agentic Index Artificial Analysis Agentic Index · a composite score measuring how well a model performs in agentic workflows · multi-step tool use, planning, error recovery, and autonomous task completion. Aggregates results from multiple agentic benchmarks including SWE-bench, tool-use tests, and planning evaluations. The canonical single-number metric for "how good is this model as an agent?" | 31.1 | 27.0 |
Artificial Analysis · Coding Index Artificial Analysis Coding Index · a composite score that aggregates performance across multiple coding benchmarks into a single index. Tracks code generation quality, debugging ability, multi-language competence, and real-world software engineering tasks. Used by Artificial Analysis to rank model coding capability in a normalized, comparable format. Useful for developers choosing between models for coding-heavy workloads. | 56.2 | 53.7 |
Artificial Analysis · Quality Index | 40.3 | 37.0 |
LiveBench · Agentic Coding | 50.0 | 50.0 |
LiveBench · Coding | 69.2 | 71.8 |
LiveBench · Data Analysis | 68.0 | 70.4 |
LiveBench · If | 63.1 | 53.2 |
LiveBench · Language | 70.1 | 63.3 |
LiveBench · Mathematics | 79.7 | 79.9 |
LiveBench · Overall | 67.3 | 65.6 |
LiveBench · Reasoning | 70.6 | 70.3 |
Pricing · per 1M tokens · projected $/mo at 10M tokens
| Model | Input | Output | Context | Projected $/mo |
|---|---|---|---|---|
| $0.08 | $0.17 | 1.0M tokens (~524 books) | $1.05 | |
| $0.28 | $2.40 | 262K tokens (~131 books) | $8.14 |
People also compared