AI model comparison
Qwen3 235B A22B Thinking 2507 vs Kimi K2 0711
Pricing, context window, benchmarks, and features compared side by side. Or skip the guesswork and send one prompt to both.
Qwen3-235B-A22B-Thinking-2507 is a high-performance, open-weight Mixture-of-Experts (MoE) language model optimized for complex reasoning tasks.
- Input / 1M
- $0.45
- Output / 1M
- $3.50
- Context
- 128K
Moonshot AI
Kimi K2 0711
Kimi K2 Instruct is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32 billion active per forward pass.
- Input / 1M
- $0.57
- Output / 1M
- $2.30
- Context
- 131K
At a glance
Quick verdict
How the two models stack up on the things people ask about most.
Lower price
Kimi K2 0711
1.2x cheaper for a typical chat
Higher intelligence score
Tie
12.7 vs 12.7 on Artificial Analysis
Larger context window
Kimi K2 0711
131K vs 128K tokens
Newer release
Qwen3 235B A22B Thinking 2507
Released July 25, 2025
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
Qwen3 235B A22B Thinking 250712.7Coding index
Qwen3 235B A22B Thinking 250722.1Agentic index
Qwen3 235B A22B Thinking 25071.3Pricing
Qwen3 235B A22B Thinking 2507 vs Kimi K2 0711 API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | Qwen3 235B A22B Thinking 2507 | |
|---|---|---|
| Input tokensPer 1M tokens | $0.45 | $0.57 |
| Output tokensPer 1M tokens | $3.50 | $2.30 |
| Cached input (read)Per 1M tokens | Not available | Not available |
| Cache writePer 1M tokens | Not available | Not available |
What it costs in practice
Estimated cost per 1,000 requests at standard rates. Coding and long-document figures also show the cost when the input is already cached.
Chat message
2K in, 500 out
Qwen3 235B A22B Thinking 2507$2.65Coding task
30K in, 4K out
Qwen3 235B A22B Thinking 2507$27.50Long document summary
150K in, 2K out
Qwen3 235B A22B Thinking 2507$74.50Specs
Context window and capabilities
How much each model can read, how much it can write, and what it accepts as input.
| Metric | Qwen3 235B A22B Thinking 2507 | |
|---|---|---|
| Context window | 128K tokens | 131K tokens |
| Max output | 16K tokens | 98K tokens |
| Input types | Text | Text |
| Output types | Text | Text |
| Reasoning effort levels | Not available | Not available |
| Default reasoning effort | Not available | Not available |
| Release date | July 25, 2025 | July 11, 2025 |
Features
Supported features
API features available for each model.
| Metric | Qwen3 235B A22B Thinking 2507 | |
|---|---|---|
| Tool calling | Supported | Supported |
| Structured outputs | Not supported | Not supported |
| JSON mode | Not supported | Not supported |
| Reasoning | Supported | Not supported |
| Temperature | Supported | Supported |
| Stop sequences | Supported | Supported |
| Deterministic seed | Not supported | Supported |
| Verbosity control | Not supported | Not supported |
Keep exploring
More on these models
Other head-to-heads, the full model page, and the alternatives list for each model.
Qwen3 235B A22B Thinking 2507View full model details- Qwen3 235B A22B Thinking 2507 vs Gemini 2.5 Flash
- Qwen3 235B A22B Thinking 2507 vs Mistral Medium 3.5
- Qwen3 235B A22B Thinking 2507 vs Nova 2 Lite
- Qwen3 235B A22B Thinking 2507 vs R1 0528
- Qwen3 235B A22B Thinking 2507 vs Command A
- Qwen3 235B A22B Thinking 2507 vs GLM 4.5
- Qwen3 235B A22B Thinking 2507 vs GPT-4.1
- Qwen3 235B A22B Thinking 2507 vs o3 Mini
- Qwen3 235B A22B Thinking 2507 vs Qwen3 235B A22B Instruct 2507
- Qwen3 235B A22B Thinking 2507 vs Qwen3 Coder 480B A35B
- Qwen3 235B A22B Thinking 2507 vs Sonar Reasoning Pro
- Qwen3 235B A22B Thinking 2507 vs o3 Mini High
- Qwen3 235B A22B Thinking 2507 vs Qwen3 VL 235B A22B Instruct
Our take
Kimi K2 0711 is 1.2x cheaper for a typical chat. Kimi K2 0711 has the larger context window (131K vs 128K tokens). The right pick depends on your workload, so the quickest way to settle it is to send the same prompt to both and compare.
FAQ
Frequently asked questions
Is Qwen3 235B A22B Thinking 2507 or Kimi K2 0711 cheaper?
Kimi K2 0711 is cheaper for a typical chat (2K input tokens and 500 output tokens). Kimi K2 0711 costs $0.57 per 1M input tokens and $2.30 per 1M output tokens, while Qwen3 235B A22B Thinking 2507 costs $0.45 per 1M input tokens and $3.50 per 1M output tokens.
Which has a bigger context window, Qwen3 235B A22B Thinking 2507 or Kimi K2 0711?
Kimi K2 0711 supports up to 131K tokens of context, compared with 128K for Qwen3 235B A22B Thinking 2507.
Is Qwen3 235B A22B Thinking 2507 smarter than Kimi K2 0711?
On the Artificial Analysis Intelligence Index, Qwen3 235B A22B Thinking 2507 scores 12.7 and Kimi K2 0711 scores 12.7, putting Qwen3 235B A22B Thinking 2507 ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.
Can I use Qwen3 235B A22B Thinking 2507 and Kimi K2 0711 at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see Qwen3 235B A22B Thinking 2507 and Kimi K2 0711 answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to Qwen3 235B A22B Thinking 2507 and Kimi K2 0711 at the same time. Compare the answers side by side and keep the best one.