Qwen: Qwen3.5 27B RPRMax v1
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Model Card
Qwen3.5 27B RPRMax v1 is a community fine-tune of Qwen3.5 27B distributed through the Infron aggregator. Its name and pricing follow the same pattern as other roleplay-oriented Qwen3.5 27B tunes on the platform (a 262K context window and per-token cost matching the "derestricted" fine-tune family), suggesting a similar orientation toward roleplay or creative-writing use, but no model card or listing description could be found to confirm training details or intended use.
No creator attribution, base-lineage confirmation beyond Qwen3.5 27B, or third-party coverage could be located for this model at the time of writing.
Context is 262K tokens, and no independent benchmark scores have been published for it.
Context Window 262K
tokens
Max Output 262K
tokens
Input Cost $0.31
per million tokens
Output Cost $0.31
per million tokens
Release Date N/A
Code Example
Add AI to your app with the Puter.js AI API, no API keys or setup required.
// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms").then(response => {
document.body.innerHTML = response.message.content;
});
<html>
<body>
<script src="https://js.puter.com/v2/"></script>
<script>
puter.ai.chat("Explain quantum computing in simple terms").then(response => {
document.body.innerHTML = response.message.content;
});
</script>
</body>
</html>
More AI Models From Qwen
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Qwen3.6 27B is a dense 27-billion-parameter multimodal model from Alibaba's Qwen team, purpose-built for agentic coding and repository-level reasoning. It scores 77.2% on SWE-bench Verified and 59.3% on Terminal-Bench 2.0, outperforming the previous-generation Qwen3.5-397B-A17B across all major coding benchmarks despite being far smaller. It natively supports text, image, and video inputs with a 262K-token context window, extendable to 1M tokens. A standout feature is Thinking Preservation, which retains reasoning traces across conversation turns — reducing redundant computation in multi-step agent loops. The model uses a hybrid attention architecture combining Gated DeltaNet with traditional self-attention. Ideal for developers building coding agents, multi-turn tool-use workflows, or frontend generation pipelines.
ChatQwen3.6 Max Preview
Qwen3.6 Max Preview is Alibaba's most capable language model to date — a proprietary flagship that claimed the top score on six major coding benchmarks at its April 20, 2026 release. It leads on SWE-bench Pro, Terminal-Bench 2.0, SkillsBench, QwenClawBench, QwenWebBench, and SciCode. The Artificial Analysis Intelligence Index rates it at 52, well above the median for reasoning models in its price tier. It supports a 256K-token context window and is text-only at launch. As a preview release, Alibaba is still actively iterating on the model. Best suited for teams building coding agents, scientific computing tools, or frontend generation systems that need peak benchmark performance.
ChatQwen3.6 35B A3B
Qwen3.6 35B A3B is a sparse Mixture-of-Experts model with 35 billion total parameters but only 3 billion active per token, making it highly efficient for inference. Developed by Alibaba's Qwen team, it scores 73.4% on SWE-bench Verified and 51.5% on Terminal-Bench 2.0 — significantly outperforming dense models like Gemma 4-31B (52.0% on SWE-bench Verified). It natively handles text, image, and video with a 262K-token context window, extendable to 1M tokens. The model supports Thinking Preservation for stable multi-turn reasoning and includes native tool-calling capabilities. Released under Apache 2.0, it was the first open-weight model in the Qwen3.6 family. A strong choice for developers who want frontier-adjacent coding performance at a fraction of the compute cost of larger models.
Frequently Asked Questions
Qwen3.5 27B RPRMax v1 is no longer available through Puter.js. Explore other AI models for alternatives.
| Price per 1M tokens | |
|---|---|
| Input | $0.31 |
| Output | $0.31 |
Qwen3.5 27B RPRMax v1 supports a context window of 262K tokens. For reference, that is roughly equivalent to 524 pages of text.
Qwen3.5 27B RPRMax v1 can generate up to 262K tokens in a single response.
Yes — the Qwen3.5 27B RPRMax v1 API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.
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