Compare · ModelsLive · 2 picked · head to head
Qwen3.7 Max vs DeepSeek V4 Pro
Side by side · benchmarks, pricing, and signals you can act on.
Winner summary
Qwen3.7 Max wins on 7/11 benchmarks
Qwen3.7 Max wins 7 of 11 shared benchmarks. Leads in speed · language · knowledge.
Category leads
speed·Qwen3.7 Maxcoding·DeepSeek V4 Proreasoning·DeepSeek V4 Prolanguage·Qwen3.7 Maxmath·DeepSeek V4 Proknowledge·Qwen3.7 Max
Hype vs Reality
Attention vs performance
Qwen3.7 Max
#28 by perf·no signal
DeepSeek V4 Pro
#13 by perf·no signal
Best value
DeepSeek V4 Pro
4.1x better value than Qwen3.7 Max
Qwen3.7 Max
27.2 pts/$
$2.50/M
DeepSeek V4 Pro
112.8 pts/$
$0.65/M
Vendor risk
Mixed exposure
One or more vendors flagged
Alibaba (Qwen)
$293.0B·Tier 1
DeepSeek
$3.4B·Tier 1
Head to head
11 benchmarks · 2 models
Qwen3.7 MaxDeepSeek V4 Pro
Artificial Analysis · Agentic Index
DeepSeek V4 Pro leads by +5.8
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?"
Qwen3.7 Max
30.6
DeepSeek V4 Pro
36.4
Artificial Analysis · Coding Index
Qwen3.7 Max leads by +6.6
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.
Qwen3.7 Max
66.0
DeepSeek V4 Pro
59.4
Artificial Analysis · Quality Index
Qwen3.7 Max leads by +1.7
Qwen3.7 Max
46.0
DeepSeek V4 Pro
44.3
LiveBench · Agentic Coding
DeepSeek V4 Pro leads by +5.0
Qwen3.7 Max
51.7
DeepSeek V4 Pro
56.7
LiveBench · Coding
Qwen3.7 Max leads by +4.2
Qwen3.7 Max
74.2
DeepSeek V4 Pro
70.0
LiveBench · Data Analysis
DeepSeek V4 Pro leads by +2.8
Qwen3.7 Max
71.8
DeepSeek V4 Pro
74.5
LiveBench · If
Qwen3.7 Max leads by +11.7
Qwen3.7 Max
74.0
DeepSeek V4 Pro
62.4
LiveBench · Language
Qwen3.7 Max leads by +1.6
Qwen3.7 Max
79.7
DeepSeek V4 Pro
78.1
LiveBench · Mathematics
DeepSeek V4 Pro leads by +5.4
Qwen3.7 Max
85.3
DeepSeek V4 Pro
90.7
LiveBench · Overall
Qwen3.7 Max leads by +0.7
Qwen3.7 Max
74.3
DeepSeek V4 Pro
73.6
LiveBench · Reasoning
Qwen3.7 Max leads by +0.7
Qwen3.7 Max
83.3
DeepSeek V4 Pro
82.7
Full benchmark table
| Benchmark | Qwen3.7 Max | DeepSeek V4 Pro |
|---|---|---|
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?" | 30.6 | 36.4 |
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. | 66.0 | 59.4 |
Artificial Analysis · Quality Index | 46.0 | 44.3 |
LiveBench · Agentic Coding | 51.7 | 56.7 |
LiveBench · Coding | 74.2 | 70.0 |
LiveBench · Data Analysis | 71.8 | 74.5 |
LiveBench · If | 74.0 | 62.4 |
LiveBench · Language | 79.7 | 78.1 |
LiveBench · Mathematics | 85.3 | 90.7 |
LiveBench · Overall | 74.3 | 73.6 |
LiveBench · Reasoning | 83.3 | 82.7 |
Pricing · per 1M tokens · projected $/mo at 10M tokens
| Model | Input | Output | Context | Projected $/mo |
|---|---|---|---|---|
| $1.25 | $3.75 | 1.0M tokens (~500 books) | $18.75 | |
| $0.43 | $0.87 | 1.0M tokens (~524 books) | $5.44 |