Compare
Kimi K2.6 (free) vs Qwen3 VL 235B A22B Instruct
This page is context-first: how much text each model can take in one request. Full specs adds capabilities and limits; the pricing matrix below is only about $/million tokens from hosts that list both models.
Model
Kimi K2.6 (free)
Context window
262K
262,144 tokens · ~197K words
Model
Qwen3 VL 235B A22B Instruct
Context window
262K
262,144 tokens · ~197K words
Context window · side by side
Bar length is relative to the larger of the two windows (100% = max of this pair). This is not pricing.
Same context window size for both models.
Kimi K2.6 (free) and Qwen3 VL 235B A22B Instruct have identical context windows (262K tokens).
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | Kimi K2.6 (free) | Qwen3 VL 235B A22B Instruct |
|---|---|---|
| Context window | 262,144 tokens (262K) | 262,144 tokens (262K) |
| Max output tokens | N/A | N/A |
| Speed tier | Balanced | Balanced |
| Vision | Yes | Yes |
| Function calling | Yes | Yes |
| Extended thinking | Yes | No |
| Prompt caching | No | Yes |
| Batch API | No | No |
| Release date | Apr 2026 | Sep 2025 |
Frequently asked questions
Powered by Mem0
Use a smaller model.
Get better results.
Mem0 gives your AI long-term memory so you stop re-sending context on every call. That means you can use a smaller, faster, cheaper model — and still get better answers.
Example: a multi-turn chat session
80% less to send — works with any model