iFLYTEK released the new generation of Spark Medical Large Model X2, trained on domestic computing power, achieving multiple breakthroughs in the medical vertical field, with performance in various tasks exceeding international leading models, triggering high attention in the industry.
iFLYTEK released the Xinghuo X2 large model, trained on a fully domestic computing power base, achieving self-controlled computing power from the bottom up to the top application. The model enhances general capabilities while focusing on highly specialized fields, aiming to solve real-world problems rather than just pursuing generality.
ByteDance is accelerating its development of the self-designed AI chip SeedChip, planning to mass-produce at least 100,000 units this year, mainly for inference tasks to ensure AI computing power supply. Although the company stated that the relevant reports are inaccurate, its AI procurement budget this year has exceeded 160 billion yuan, with half still used to purchase NVIDIA chips, reflecting the high inference cost pressure faced when advancing large models.
iFLYTEK released the "Spark X2" large model, which is trained using fully domestic computing power and achieves breakthroughs in algorithms and engineering. The model matches international top-level capabilities in core areas such as mathematics, logical reasoning, language comprehension, and intelligent agents. It focuses on industry application needs, driving the development of domestic large models to a new stage.
Provides stable and efficient AI computing power and GPU rental services.
Intelligent computing power available on demand, significantly improving efficiency and competitiveness.
SandboxAQ, which uses AI and advanced computing power to change the world.
Upsonic AI provides powerful computing and management infrastructure that allows developers to seamlessly create AI agents.
Google
$0.49
Input tokens/M
$2.1
Output tokens/M
1k
Context Length
Openai
$7.7
$30.8
200
Alibaba
-
Tencent
$1
$4
32
$1.75
$14
400
Iflytek
$2
$0.8
Baidu
64
Minimax
$1.6
$16
$21
$84
128
cpatonn
Qwen3-VL-32B-Instruct AWQ - INT4 is a 4-bit quantized version based on the Qwen3-VL-32B-Instruct base model. It uses the AWQ quantization method, significantly reducing storage and computing resource requirements while maintaining performance. This is the most powerful vision-language model in the Qwen series, with comprehensive upgrades in text understanding, visual perception, context length, etc.
QCRI
Fanar-1-9B-Instruct is a powerful Arabic-English large language model developed by the Qatar Computing Research Institute (QCRI). It supports Modern Standard Arabic and multiple Arabic dialects, and is aligned with Islamic values and Arab culture.
modularStarEncoder
ModularStarEncoder-300M is an encoder model fine-tuned on the SynthCoNL dataset based on the ModularStarEncoder-1B pre-trained model. It is specifically designed for code-to-code and text-to-code retrieval tasks. This model uses hierarchical self-distillation technology, allowing users to choose different layer versions according to their computing power.
chavinlo
The Alpaca model replicated by the Tatsu team at Stanford University. This is a large language model that performs instruction fine-tuning based on LLaMA-7B. The model was trained on 4 A100 GPUs for 6 hours, with computing power donated by redmond.ai. It does not use LoRA technology and adopts the native fine-tuning method.
A mathematical computing service based on the MCP protocol and the SymPy library, providing powerful symbolic computing capabilities, including basic operations, algebraic operations, calculus, equation solving, matrix operations, etc.
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