DeepSeek-V4.1-Flash-1017
DeepSeek-V4.1-Flash-1017 is a minor update to DeepSeek-V4.1-Flash, delivering substantial improvements across reasoning, coding, agentic tasks, and visual benchmarks. Alongside these gains, the model…
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DeepSeek-V4.1-Flash-1017 is a minor update to DeepSeek-V4.1-Flash, delivering substantial improvements across reasoning, coding, agentic tasks, and visual benchmarks. Alongside these gains, the model…
OpenRouter lists a 1,048,576-token context and up to 943,718 output tokens for this open-weight model aimed at agentic coding.
120B/12B-active Mamba-2 hybrid with a vision encoder; native speculative decoding and switchable thinking.
Qwen Image 2.1 Pro is an image generation and editing model from Qwen, the higher-quality tier of the Qwen Image 2.1 series. Choose it over Qwen Image 2.1 Turbo when...
Qwen Image 2.1 Turbo is the fast, lower-cost tier of the Qwen Image 2.1 series from Qwen, for image generation and editing where throughput and price matter more than peak...
Nano Banana 2.1 (Gemini Nano Banana 2.1) is Google's image generation and editing model on the Flash tier, succeeding Nano Banana 2 and Nano Banana Pro. It improves product recontextualization,...
FLUX.3 Image is Black Forest Labs' flagship image generation and editing model. It handles text-to-image and multi-reference editing with up to 10 input images, and renders at fixed resolution tiers...
Long decode can use the unified 1M-token budget for output; reads video, audio and PDFs, with implicit-only caching.
Requires Responses API for tools; offers Ultrafast inference with US or EU data residency.
Tuned for quick iteration on scoped fixes and documents; Anthropic favors Opus 5.5 for open-ended work needing sustained judgment.
Always-on adaptive thinking defaults to medium effort; built for sustained work across large codebases and professional documents.
Can turn reasoning off for high-volume requests; Chat Completions tool calls require reasoning_effort=none.
MiMo-V2.6-Pro is the flagship foundation model developed by Xiaomi. Built at a scale of over 1T parameters, it is designed to push the ceiling of capability for the most demanding...
600B total and 27B active parameters; accepts images and video, with FP8 and BF16 weights for deployment.
Causal encoder-decoder activates 8B parameters for input and 16B for output, reducing the compute needed for long inputs.
General-purpose GPT Image 2.5 tier with transparent output, custom dimensions and five explicit quality levels.
Trades longer generation time for intricate detail; supports transparent backgrounds and quality levels through max.
MAI-Image-2.6 Flash is the lower-latency, lower-cost member of the MAI-Image-2.6 family from Microsoft AI, built for latency-sensitive, high-throughput production image generation and editing at comparable…
Accepts mid-turn steering and async tool calls, so agents can take new instructions while other tools are still running.