Qwen3.6 35B A3B Uncensored
phala/qwen3.6-35b-a3b-uncensored- - 🧠 Mixture-of-experts: 35B total parameters, ~3B active per token
- - 🆕 Community "uncensored" fine-tune of Alibaba's Qwen3.6-35B-A3B base
- - 🔒 Runs in a Trusted Execution Environment with hardware attestation
- - 📏 Native context up to 262,144 tokens
- - 👁️ Catalog lists multimodal input across text, images, and video
- - 🔧 Vendor reports big agentic-coding gain over Qwen3.5-35B-A3B
- - 🌐 Capabilities include web search; served at FP8 quantization
- - 🆕 Adds "Thinking Preservation" to retain reasoning across turns
Alibaba Group is a Chinese multinational technology company founded in 1999 and headquartered in Hangzhou, Zhejiang. Originally built around e-commerce and cloud computing, Alibaba has become one of the most prolific contributors to open-weight AI research, developing the Qwen…
Explore 39 more models by Alibaba Group →Qwen3.6 35B A3B Uncensored is a community-modified variant of Alibaba's Qwen3.6-35B-A3B, a sparse mixture-of-experts model with 35 billion total and roughly 3 billion active parameters. The "uncensored" descriptor refers to a third-party post-training fine-tune that strips the base model's safety refusal mechanisms without altering core capabilities; it is not an official Alibaba release. Venice runs it inside a Trusted Execution Environment with attestation evidence for independent verification, here at FP8 quantization.
Architecturally, the base uses 256 experts routing 8 per token, 40 layers, and a hybrid linear plus full-softmax attention mechanism, supporting native context up to 262,144 tokens. The catalog additionally lists multimodal input across text, images, and video. Compared with its same-family predecessor Qwen 3.5 35B A3B from February 2026, the Qwen3.6 generation adds the "Thinking Preservation" option to retain reasoning context across messages. Per Alibaba's own blog, Qwen3.6-35B-A3B "surpasses its predecessor Qwen3.5-35B-A3B by a wide margin" on agentic coding.
This entry is the uncensored sibling of the standard Qwen 3.6 35B A3B FP8 deployment, sharing the same base weights and TEE delivery but removing refusal behavior. Both maintain Qwen3.6's thinking and non-thinking modes. Note that the catalog configures a 128K-token context window for this deployment, below the architecture's native 262K maximum.
This About section is AI-generated from public sources via VeniceStats + Venice inference, with no human editing. It may contain inaccuracies.
| Seller | Reputation↓ | Routing | Input $/M | Cached $/M | Output $/M | Categories | API |
|---|---|---|---|---|---|---|---|
| Phala 0x88c8…15d6 | 43.88 | gated | $0.30 | $0.30 | $1.50 | chat,confidential,reasoning,multimodal | openai-chat-completions |
"Best price" and the seller table are live AntSeed catalog data (advertised $/1M tokens — or $ per generated image for unit-billed image models — not settled amounts). Reputation = on-chain trust (0-100). "Routing" = the SDK's default buyer routing (what the VPR desktop app ships with): a trust ≥ 60 gate on the effective reputation, then cheapest-first among routable sellers; live failover state (per-peer cooldowns) is buyer-side runtime and not included. Model knowledge (TLDR, provider, About) via the VeniceStats enrichment layer. Advertised catalog, not the model used in any specific purchase. "Usage on AntSeed" counts only settlements whose buyers share the per-model split on-chain (metadata v2/v3, opt-in), so every usage figure is a lower bound.