deepseek-ai

Text Generation

DeepSeek V4 Pro 0813 is the official release of V4 Pro, and the point at which the series flagship became a production agent rather than a preview. It keeps the architecture that defines the series — 1.6 trillion total parameters with 49 billion active per token, a one-million-token context window, and a hybrid attention stack built to make that window practical — and rebuilds the agentic behaviour on top of it. Long-horizon software engineering, terminal automation, security workflows, and tool orchestration all improve substantially over the preview, in several cases by a factor of several. Reasoning effort is a per-request setting with three levels, and the checkpoint ships with a speculative decoding module for faster generation. Released under the MIT license.

google

Text Generation

Gemini 3.7 Flash is Google's most capable Flash-tier model, built for coding and agentic work rather than for chat alone. It is natively multimodal in the widest sense available: text, images, video, audio, and PDFs all go in directly, against a one-million-token context window, with no separate extraction step in front of it. Thinking depth is a request-level setting with three levels, letting the same model serve a latency-critical pipeline and a long multi-step agent run. Google reports large gains over the previous Flash generation on issue resolution, production-ready code generation, complex document processing, and real-world business automation. On DEVUP AI it is the natural choice when your input is not plain text and your workflow has more than one step.

deepseek-ai

Text Generation

DeepSeek V4 Flash 0731 is the official release of V4 Flash, and it is the checkpoint where the series became genuinely agentic. Built on the same efficiency-first Mixture-of-Experts design — 284B total parameters with only 13B active per token and a one-million-token context window — it adds a substantially rebuilt agentic capability that lifts long-horizon coding, terminal automation, and tool-use scores far above the preview, in several cases past the much larger V4 Pro preview despite activating a fraction of its parameters. Reasoning effort is a per-request setting with three levels, and the checkpoint ships with a speculative decoding module for faster generation. Released under the MIT license, it is the model to reach for on DEVUP AI when an agent has to finish a long job, not just start one.

stepfun-ai

Text Generation

Step 3.7 Flash is an open-source multimodal reasoning model by StepFun with 198B total parameters (11B active) using Mixture of Experts. It accepts text and image inputs and features a 256K context window, selectable reasoning effort, tool calling, and agentic capabilities for coding and search workflows, scoring 80.9% on GPQA Diamond and 56.3% on SWE-bench Pro.

zai-org

Text Generation

GLM-5.2 is Z-AI's latest flagship model for long-horizon tasks. It marks a substantial leap in long-horizon task capability over its predecessor GLM-5.1 and, for the first time, delivers that capability on a **solid 1M-token context**.

moonshotai

Text Generation

Kimi K2.7 Code is a coding-focused agentic model built upon Kimi K2.6. With substantial improvements on real-world long-horizon coding tasks, it strengthens end-to-end task completion across complex software engineering workflows while improving token efficiency, reducing thinking-token usage by approximately 30% compared with Kimi K2.6.

Qwen

text-to-speech

● Qwen3-TTS-VoiceDesign is a voice design variant of Qwen3-TTS by Alibaba's Qwen team. Instead of selecting from preset voices, you describe the voice you want in natural language — and the model generates speech in that voice. Key capabilities: - Natural language voice control — describe any voice with free text (e.g. "a deep male voice with a calm, authoritative presence", "a young cheerful female with a warm and friendly tone") - 10 languages — English, Chinese, Japanese, Korean, German, French, Russian, Spanish, Italian, Portuguese - Streaming support — real-time PCM streaming - Multiple output formats — WAV, MP3, FLAC, PCM Built on the same 1.7B parameter architecture as Qwen3-TTS, using discrete multi-codebook language modeling and a custom 12Hz acoustic tokenizer for high-quality end-to-end speech synthesis.

Qwen

Text Generation

Qwen3.5-397B-A17B is Alibaba's most capable Qwen3.5 model, a Mixture-of-Experts architecture with 397B total parameters and 17B activated per token. It features a 262K token context window (extensible to 1M with YaRN), thinking/reasoning mode, tool calling with MCP integration, and support for 201 languages. Sets state-of-the-art results on reasoning, coding, math, and multimodal benchmarks.

Qwen

Text Generation

The latest flagship reasoning model in the Qwen3 family. Further enhanced by multiple innovations like adaptive tool-use and advanced test-time scaling techniques

Qwen

text-to-speech

Qwen3-TTS is an advanced text-to-speech model by Alibaba's Qwen team, delivering stable, expressive, and low-latency speech generation across 10 languages. Key capabilities: - 9 preset voices — Vivian, Serena, Uncle_Fu, Dylan, Eric, Ryan, Aiden, Ono_Anna, Sohee — covering diverse genders, ages, and accents - Voice cloning — clone any voice from a short (~3s) audio sample via the voice_id parameter - Instruction control — adjust tone, emotion, and speaking style with natural language (e.g. "speak slowly and calmly", "excited tone") - 10 languages — English, Chinese, Japanese, Korean, German, French, Russian, Spanish, Italian, Portuguese - Streaming support — real-time PCM streaming with ~97ms first-byte latency - Multiple output formats — WAV, MP3, FLAC, PCM Built on a 1.7B parameter architecture using discrete multi-codebook language modeling for end-to-end speech synthesis without cascading errors. Uses a custom 12Hz acoustic tokenizer that preserves paralinguistic information and environmental audio details.

Qwen

Text Generation

Qwen3.6-35B-A3B is Alibaba's latest flagship Mixture-of-Experts model, with 35B total parameters and only 3B activated per token (256 experts, 8 routed + 1 shared). Built on direct feedback from the community, Qwen3.6 prioritizes stability and real-world utility, offering developers a more intuitive, responsive, and genuinely productive coding experience.

nvidia

Text Generation

NVIDIA Nemotron 3 Super is a hybrid Mixture-of-Experts (MoE) model engineered for highest compute efficiency and accuracy in multi-agent applications and specialized agentic systems. It is optimized to run many collaborating agents per application on a single GPU, delivering high accuracy for reasoning, tool use, and instruction following.