模型

浏览来自所有提供商的 13 个标准化 LLM 模型

显示第 1–13 项,共 13 个模型

Gemini 3.5 Flash-Lite

美国

Google's fastest and most cost-effective Gemini 3.5-class model, delivering around 350 output tokens per second per the Artificial Analysis Index. Designed for low-latency and high-throughput agentic workflows such as agentic search and document processing, with configurable thinking levels, built-in computer use, and full multimodal support across a 1M-token context window.

上下文
1.0M
发布日期
2026年7月

MiniMax M3

中国

MiniMax's frontier open-weight model with 1M-token context window, native multimodality (text, image, video), and strong coding capabilities. Built on MiniMax Sparse Attention (MSA) architecture, achieving 59% on SWE-Bench Pro with significantly improved efficiency at long context.

上下文
1.0M
发布日期
2026年6月

Solar Pro 3

韩国

Upstage's powerful Mixture-of-Experts language model with 102B total parameters and 12B active parameters per forward pass. Optimized for Korean with strong English and Japanese support. Excels at complex reasoning, structured output generation, and agentic workflows.

上下文
128K
发布日期
2026年5月

Gemini 3.5 Flash

美国

Google DeepMind's balanced Gemini 3.5 model that pairs Pro-line reasoning quality with Flash-line latency and cost. Natively multimodal across text, image, audio, and video with a 1M-token context window, configurable thinking levels, and streaming function calling, tuned for high-throughput production workloads.

上下文
1.0M
发布日期
2026年5月

Gemini 3 Flash

美国

Google's balanced model combining Gemini 3 Pro's reasoning capabilities with the Flash line's latency, efficiency, and cost. Features configurable thinking levels, multimodal function responses, and streaming function calling for complex agentic workflows.

上下文
1.0M
发布日期
2026年5月

Gemini 3.1 Flash-Lite

美国

Google's most cost-efficient Gemini model optimized for high-volume, low-latency use cases. Delivers 2.5x faster time to first token versus Gemini 2.5 Flash with full multimodal support. Ideal for agentic tasks, data extraction, translation, and classification.

上下文
1.0M
发布日期
2026年5月

Laguna M.1

美国

Poolside AI's flagship agentic coding model with 225B total parameters and 23B active (MoE). Trained from scratch in-house on 30T tokens across 6,144 NVIDIA Hopper GPUs. Optimized for complex multi-step software engineering tasks including codebase exploration, file editing, test running, and iterative debugging.

上下文
128K
发布日期
2026年4月

GLM-5.1

中国

Zhipu AI's latest bilingual model with strong Chinese and English capabilities. Features improved reasoning, coding, and tool use with competitive performance on academic benchmarks.

上下文
131K
发布日期
2026年3月

MiniMax M2.7

中国

MiniMax's latest large language model with strong multilingual and multimodal capabilities. Competitive pricing with high-quality text generation and improved reasoning performance.

上下文
200K
发布日期
2026年3月

Kimi K2.6

中国

Moonshot AI's latest model with ultra-long context window support, strong reasoning capabilities, and excellent performance on complex multi-step tasks. Known for reliable long-document understanding.

上下文
1.0M
发布日期
2026年3月

Mistral Medium 3.5

法国

Mistral AI's balanced model offering strong multilingual performance with excellent price-performance ratio. Optimized for production workloads requiring reliable quality across European and global languages.

上下文
128K
发布日期
2026年2月

Grok 4.1 Fast

美国

xAI's fast and cost-effective model with 2M token context window. Offers both reasoning and non-reasoning modes at significantly lower pricing than flagship models.

上下文
2.0M
发布日期
2025年11月

Gemini 2.5 Flash

美国

Google's cost-effective model optimized for high throughput tasks. Balances speed and intelligence with strong multimodal capabilities and 1M token context window.

上下文
1.0M
发布日期
2025年6月