Compare · ModelsLive · 2 picked · head to head
Step 3.5 Flash vs Qwen3.6 Plus
Side by side · benchmarks, pricing, and signals you can act on.
Winner summary
Qwen3.6 Plus wins on 3/3 benchmarks
Qwen3.6 Plus wins 3 of 3 shared benchmarks. Leads in speed.
Category leads
speed·Qwen3.6 Plus
Hype vs Reality
Attention vs performance
Step 3.5 Flash
#9 by perf·#11 by attention
Qwen3.6 Plus
#14 by perf·no signal
Best value
Step 3.5 Flash
6.2x better value than Qwen3.6 Plus
Step 3.5 Flash
384.5 pts/$
$0.20/M
Qwen3.6 Plus
62.3 pts/$
$1.14/M
Vendor risk
Mixed exposure
One or more vendors flagged
StepFun
$5.0B·Tier 1
Alibaba (Qwen)
$293.0B·Tier 1
Head to head
3 benchmarks · 2 models
Step 3.5 FlashQwen3.6 Plus
Artificial Analysis · Agentic Index
Qwen3.6 Plus leads by +9.7
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?"
Step 3.5 Flash
52.0
Qwen3.6 Plus
61.7
Artificial Analysis · Coding Index
Qwen3.6 Plus leads by +11.2
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.
Step 3.5 Flash
31.6
Qwen3.6 Plus
42.9
Artificial Analysis · Quality Index
Qwen3.6 Plus leads by +12.2
Step 3.5 Flash
37.8
Qwen3.6 Plus
50.0
Full benchmark table
| Benchmark | Step 3.5 Flash | Qwen3.6 Plus |
|---|---|---|
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?" | 52.0 | 61.7 |
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. | 31.6 | 42.9 |
Artificial Analysis · Quality Index | 37.8 | 50.0 |
Pricing · per 1M tokens · projected $/mo at 10M tokens
| Model | Input | Output | Context | Projected $/mo |
|---|---|---|---|---|
| $0.10 | $0.30 | 262K tokens (~131 books) | $1.50 | |
| $0.33 | $1.95 | 1.0M tokens (~500 books) | $7.31 |