Compare · ModelsLive · 2 picked · head to head
Kimi K2.7 Code vs Qwen3.5 397B A17B
Side by side · benchmarks, pricing, and signals you can act on.
Winner summary
Kimi K2.7 Code wins on 3/3 benchmarks
Kimi K2.7 Code wins 3 of 3 shared benchmarks. Leads in speed.
Category leads
speed·Kimi K2.7 Code
Hype vs Reality
Attention vs performance
Kimi K2.7 Code
#42 by perf·no signal
Qwen3.5 397B A17B
#5 by perf·no signal
Best value
Qwen3.5 397B A17B
1.6x better value than Kimi K2.7 Code
Kimi K2.7 Code
34.3 pts/$
$1.84/M
Qwen3.5 397B A17B
55.3 pts/$
$1.42/M
Vendor risk
Who is behind the model
moonshotai
private · undisclosed
Alibaba (Qwen)
$293.0B·Tier 1
Head to head
3 benchmarks · 2 models
Kimi K2.7 CodeQwen3.5 397B A17B
Artificial Analysis · Agentic Index
Kimi K2.7 Code 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?"
Kimi K2.7 Code
29.6
Qwen3.5 397B A17B
19.9
Artificial Analysis · Coding Index
Kimi K2.7 Code leads by +12.5
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.
Kimi K2.7 Code
60.8
Qwen3.5 397B A17B
48.2
Artificial Analysis · Quality Index
Kimi K2.7 Code leads by +8.3
Kimi K2.7 Code
42.0
Qwen3.5 397B A17B
33.7
Full benchmark table
| Benchmark | Kimi K2.7 Code | Qwen3.5 397B A17B |
|---|---|---|
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?" | 29.6 | 19.9 |
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. | 60.8 | 48.2 |
Artificial Analysis · Quality Index | 42.0 | 33.7 |
Pricing · per 1M tokens · projected $/mo at 10M tokens
| Model | Input | Output | Context | Projected $/mo |
|---|---|---|---|---|
| $0.61 | $3.07 | 262K tokens (~131 books) | $12.26 | |
| $0.39 | $2.45 | 256K tokens (~128 books) | $9.01 |
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