| Signal | Kimi K2 Thinking | Delta | Qwen3 235B A22B |
|---|---|---|---|
Capabilities | 67 | -- | |
Benchmarks | 51 | -4 | |
Pricing | 98 | -1 | |
Context window size | 86 | +5 | |
Recency | 100 | +33 | |
Output Capacity | 90 | +25 | |
| Overall Result | 3 wins | of 6 | 2 wins |
Score History
53.3
current score
Qwen3 235B A22B
right now
54
current score
Moonshot AI
Alibaba
Qwen3 235B A22B saves you $48.50/month
That's $582.00/year compared to Kimi K2 Thinking at your current usage level of 100K calls/month.
| Metric | Kimi K2 Thinking | Qwen3 235B A22B | Winner |
|---|---|---|---|
| Overall Score | 53 | 54 | Qwen3 235B A22B |
| Rank | #155 | #153 | Qwen3 235B A22B |
| Quality Rank | #155 | #153 | Qwen3 235B A22B |
| Adoption Rank | #155 | #153 | Qwen3 235B A22B |
| Parameters | -- | 235B | -- |
| Context Window | 262K | 131K | Kimi K2 Thinking |
| Pricing | $0.60/$2.50/M | $0.45/$1.82/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 67 | Kimi K2 Thinking |
| Benchmarks | 51 | 55 | Qwen3 235B A22B |
| Pricing | 98 | 98 | Qwen3 235B A22B |
| Context window size | 86 | 81 | Kimi K2 Thinking |
| Recency | 100 | 68 | Kimi K2 Thinking |
| Output Capacity | 90 | 65 | Kimi K2 Thinking |
Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.
Scores 53/100 (rank #155), placing it in the top 47% of all 290 models tracked.
Scores 54/100 (rank #153), placing it in the top 48% of all 290 models tracked.
With only a 1-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.
Qwen3 235B A22B offers 27% better value per quality point. At 1M tokens/day, you'd spend $34.13/month with Qwen3 235B A22B vs $46.50/month with Kimi K2 Thinking - a $12.38 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
Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Suitable for user-facing chat with competitive response times. Qwen3 235B A22B also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (262K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($1.82/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (54/100) correlates with better nuance, coherence, and style in long-form content
Kimi K2 Thinking and Qwen3 235B A22B are extremely close in overall performance (only 0.7000000000000028 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Kimi K2 Thinking
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen3 235B A22B
27% 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
| Capability | Kimi K2 Thinking | Qwen3 235B A22B |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Moonshot AI
Alibaba
Qwen3 235B A22B saves you $1.08/month
That's 26% 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 235B A22B |
|---|---|---|
| Context Window | 262K | 131K |
| Max Output Tokens | 262,144 | 8,192 |
| Open Source | Yes | Yes |
| Created | Nov 6, 2025 | Apr 28, 2025 |