| Signal | Kimi K2 Thinking | Delta | Qwen3.5 Plus 2026-02-15 |
|---|---|---|---|
Capabilities | 67 | -17 | |
Pricing | 2 | +0 | |
Context window size | 81 | -14 | |
Recency | 100 | -- | |
Output Capacity | 20 | -60 | |
| Overall Result | 1 wins | of 5 | 3 wins |
0
days ranked higher
0
days
30
days ranked higher
Moonshot AI
Alibaba
Qwen3.5 Plus 2026-02-15 saves you $43.00/month
That's $516.00/year compared to Kimi K2 Thinking at your current usage level of 100K calls/month.
| Metric | Kimi K2 Thinking | Qwen3.5 Plus 2026-02-15 | Winner |
|---|---|---|---|
| Overall Score | 73 | 85 | Qwen3.5 Plus 2026-02-15 |
| Rank | #138 | #30 | Qwen3.5 Plus 2026-02-15 |
| Quality Rank | #138 | #30 | Qwen3.5 Plus 2026-02-15 |
| Adoption Rank | #138 | #30 | Qwen3.5 Plus 2026-02-15 |
| Parameters | -- | -- | -- |
| Context Window | 131K | 1000K | Qwen3.5 Plus 2026-02-15 |
| Pricing | $0.47/$2.00/M | $0.26/$1.56/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 83 | Qwen3.5 Plus 2026-02-15 |
| Pricing | 2 | 2 | Kimi K2 Thinking |
| Context window size | 81 | 95 | Qwen3.5 Plus 2026-02-15 |
| Recency | 100 | 100 | Kimi K2 Thinking |
| Output Capacity | 20 | 80 | Qwen3.5 Plus 2026-02-15 |
Our composite score (0–100) combines six weighted signals: benchmark performance (25%), pricing efficiency (25%), context window size (15%), model recency (15%), output capacity (10%), and capability versatility (10%). Here's what the scores mean for these two models:
Scores 73/100 (rank #138), placing it in the top 53% of all 290 models tracked.
Scores 85/100 (rank #30), placing it in the top 90% of all 290 models tracked.
Qwen3.5 Plus 2026-02-15 has a 12-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.
Qwen3.5 Plus 2026-02-15 offers 26% better value per quality point. At 1M tokens/day, you'd spend $27.30/month with Qwen3.5 Plus 2026-02-15 vs $37.05/month with Kimi K2 Thinking - a $9.75 monthly difference.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Higher benchmark score (0/100) indicates stronger performance on coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Faster response time (speed score 0/100) is critical for user-facing chat. Qwen3.5 Plus 2026-02-15 also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (1000K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($1.56/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (85/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
Qwen3.5 Plus 2026-02-15 clearly outperforms Kimi K2 Thinking with a significant 12.400000000000006-point lead. For most general use cases, Qwen3.5 Plus 2026-02-15 is the stronger choice. However, Kimi K2 Thinking may still excel in niche scenarios.
Best for Quality
Kimi K2 Thinking
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen3.5 Plus 2026-02-15
26% lower pricing; better value at scale
Best for Reliability
Kimi K2 Thinking
Higher uptime and faster response speeds
Best for Prototyping
Kimi K2 Thinking
Stronger community support and better developer experience
Best for Production
Kimi K2 Thinking
Wider enterprise adoption and proven at scale
by Moonshot AI
by Alibaba
| Capability | Kimi K2 Thinking | Qwen3.5 Plus 2026-02-15 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Moonshot AI
Alibaba
Qwen3.5 Plus 2026-02-15 saves you $0.9060/month
That's 28% cheaper than Kimi K2 Thinking at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | Kimi K2 Thinking | Qwen3.5 Plus 2026-02-15 |
|---|---|---|
| Context Window | 131K | 1M |
| Max Output Tokens | -- | 65,536 |
| Open Source | Yes | No |
| Created | Nov 6, 2025 | Feb 16, 2026 |
Qwen3.5 Plus 2026-02-15 scores 85/100 (rank #30) compared to Kimi K2 Thinking's 73/100 (rank #138), giving it a 12-point advantage. Qwen3.5 Plus 2026-02-15 is the stronger overall choice, though Kimi K2 Thinking may excel in specific areas like certain benchmarks.
Kimi K2 Thinking is ranked #138 and Qwen3.5 Plus 2026-02-15 is ranked #30 out of 290+ AI models. Rankings use a composite score combining benchmark performance (25%), pricing (25%), context window (15%), recency (15%), output capacity (10%), and versatility (10%). Scores update hourly.
Qwen3.5 Plus 2026-02-15 is cheaper at $1.56/M output tokens vs Kimi K2 Thinking's $2.00/M output tokens - 1.3x more expensive. Input token pricing: Kimi K2 Thinking at $0.47/M vs Qwen3.5 Plus 2026-02-15 at $0.26/M.
Qwen3.5 Plus 2026-02-15 has a larger context window of 1,000,000 tokens compared to Kimi K2 Thinking's 131,072 tokens. A larger context window means the model can process longer documents and conversations.