тепловизионное обследование дома в нижнем новгороде
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тепловизионное обследование дома в нижнем новгороде, Qwen/Qwen3-235B-A22B-GPTQ-Int4 · Hugging Face, Qwen3 235B A22B: Pricing, Context Window, Benchmarks, and More, Qwen3 Technical Report - arXiv.org, Qwen3-235B-A22B-GPTQ-Int4 · Models, Qwen3 235B and 30B MoE Quant Benchmarking Roundup · GitHub, LLM Benchmarks Leaderboard: DeepSeek, Qwen, Llama, and more | Lambda, Qwen 3 Benchmarks, Comparisons, Model Specifications, and More.
The default max_position_embeddings in config.json is set to 40,960. This allocation includes reserving 32,768 tokens for outputs and 8,192 tokens for typical prompts, which is sufficient for most scenarios involving short text processing. If the average context length does not exceed 32,768 tokens, we do not recommend enabling YaRN in this scenario, as it may potentially degrade model performance., By default, Qwen3 has thinking capabilities enabled, similar to QwQ-32B. This means the model will use its reasoning abilities to enhance the quality of generated responses., It achieves competitive results in benchmark evaluations of coding, math, general capabilities, and more, compared to other top-tier models. Compare Qwen3 235B A22B to other models by quality (GPQA score) vs cost. Higher scores and lower costs represent better value..
From the results in Table 3, the Qwen3-235B-A22B-Base model attains the highest performance scores across most of the evaluated benchmarks. We further compare Qwen3-235B-A22B-Base with other baselines separately for the detailed analysis., By default, Qwen3 has thinking capabilities enabled, similar to QwQ-32B. This means the model will use its reasoning abilities to enhance the quality of generated responses., GPQA Diamond Set: A subset of 198 high-objectivity, challenging multiple-choice questions designed for advanced testing. Difficulty aligns with college-level or higher expertise in biology, physics, and chemistry., Discover the latest performance benchmarks leaderboard for top large language models. Compare Llama, Qwen, DeepSeek, and others on key metrics like LiveCodeBench, MMLU Pro, and GPQA to find the best model for your needs., Below, despite being the second-smallest model, Qwen3-235B outranks all models on all benchmarks, excepting DeepSeek v3 on the INCLUDE Multilingual tasks benchmark., Initial benchmark results indicate that Qwen3-235B-A22B meets or outperforms leading systems such as DeepSeek-R1, OpenAI’s O1 and o3-mini, Grok-3 and Google DeepMind’s Gemini-2.5 Pro across coding, mathematics and general-reasoning tasks..