HLE
24.0 score
LLM Leaderboard · Open Weight
Qwen3.6-27B benchmarks, pricing, and LLM comparison.
Compare Qwen3.6-27B vs GPT, Claude, Gemini, DeepSeek, open-weight, and frontier AI models using public benchmark scores, token pricing, context window, and access details.
Rank #28AskClash overall score: 49.1
$0 / $0Input and output token price, when published. Context: 262K.
APIBilling and access path cached for this model row.
Qwen3.6-27B benchmark snapshot
AskClash combines public LLM benchmark cells into a weighted percentile score and penalizes missing coverage so narrow rows do not dominate better-measured models.
Overall49.1
Benchmark cells9
Context262K
CreatorAlibaba
Qwen3.6-27B public benchmark scores
Cached benchmark values can include HLE, GPQA, SWE-bench, SWE-Pro, SWE-Atlas, Terminal-Bench, MCP Atlas, MMMU-Pro, ARC-AGI-2, Tau2, and model-specific coding or agent scores.
GPQA
87.8 score
IFEval
67.6 score
SWE-bench
77.2 score
Terminal-Bench
59.3 score
LiveCodeBench
83.9 score
CharXiv
78.4 score
MMMU-Pro
75.8 score
Tau2
94.2 score
Qwen3.6-27B vs other AI models
Use these comparison links to evaluate Qwen3.6-27B against nearby LLMs by benchmark score, price, context window, and provider.
Related AI and tech coverage
Cached AskClash article matches that can provide release, provider, benchmark, pricing, or market context around this model.
Qwen3.6-27B: Flagship-Level Coding in a 27B Dense Model
Qwen3.6-27B: Flagship-Level Coding in a 27B Dense Model Simon Willison’s Weblog Subscribe Sponsored by: Honeycomb — AI agents behave unpredictably. Get the context you need to debug what actually happened. Read the blog 22nd April 2026 - Link Blog Qwen3.6-27B: Flagship-Level Coding in a 27B Dense Model ( via ) Big claims from Qwen about their latest open weight model: Qwen3.6-27B delivers flagship-level agentic coding performance, surpassing the previous-generation open-source flagship Qwen3.5-3
OpenAI workspace agents 🤝, Google Workspace Intelligence 🌐, Qwen3.6-27B 🤖
OpenAI workspace agents 🤝, Google Workspace Intelligence 🌐, Qwen3.6-27B 🤖 TLDR Newsletters Advertise TLDR TLDR AI 2026-04-23 OpenAI workspace agents 🤝, Google Workspace Intelligence 🌐, Qwen3.6-27B 🤖 Google Cloud Next is underway! (Sponsor) If you're building for the agentic era you need AI-optimized infrastructure to deliver on new requirements. We announced significant expansion of our AI infrastructure portfolio including the eighth generation of our Tensor Processing Units (TPUs) , which for
HuggingFace TRL / RLHF v1.3.0 Release Notes
TRL v1.3 ships training support for the new **Qwen 3.6** family (`Qwen/Qwen3.6-27B`, `Qwen/Qwen3.6-35B-A3B`). Qwen 3.6 reuses the `Qwen3_5Moe*` architecture but ships a slightly different chat template (adds a `preserve_thinking` flag, tweaks tool-arg stringification), so exact-string template matching needed updates across the stack. A new experimental `TPOTrainer` implements [Triple Preference Optimization](https://huggingface.co/papers/2405.16681), which augments DPO with a `reference` (gold)
llama.cpp b8964 Release Notes
- [Windows x64 (CUDA 12)](https://github.com/ggml-org/llama.cpp/releases/download/b8964/llama-b8964-bin-win-cuda-12.4-x64.zip) - [CUDA 12.4 DLLs](https://github.com/ggml-org/llama.cpp/releases/download/b8964/cudart-llama-bin-win-cuda-12.4-x64.zip) DONE state absorbs all tokens including a new start tag, causing any think blocks after the first to run unbudgeted. Observed on unsloth/Qwen3.6-27B-GGUF which interleaves multiple <think> blocks per response.
Last cached leaderboard date: May 25, 2026. This model page is generated from the AskClash LLM Leaderboard cache and linked from the live leaderboard.