AI models
Compare text, image, video, decision and robotics models. Read capability and license guides, check API access, and estimate running costs with a calculator.
Models found: 37
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DeepSeek-V4.1-Flash
DeepSeek-V4.1-Flash reads text and images and responds in text, with a 1M-token context window and open weights. Start with hosted deepseek-flash or a compatible client, then compare the whole task’s token and tool bill with the memory, runtime and hardware needed to self-host an exact checkpoint.
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Qwen3.8-27B
Qwen3.8-27B is a dense open-weight model for text, image and video understanding, with text output and an Apache 2.0 license. It offers a simpler local starting point than the much larger Flash-Next. A quantized download can fit a desktop GPU, while the conversation cache and runtime still need extra space. Choose the format and context together, then measure the time to a correct answer on your own task.
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Gemma 4 12B it
Gemma 4 12B is Google’s dense instruction-tuned model for text output from text and supported visual or audio inputs. Its approximately 11.95B parameters are available under Apache 2.0. Google’s QAT Q4_0 GGUF offers a smaller local download; the memory used while running also depends on context, cache settings and the runtime.
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Qwen3.8-Flash-Next
Qwen3.8-Flash-Next brings a large mixture-of-experts model to local coding and visual tasks. Its 125B main model activates about 6B parameters per token, with another 51B in n-gram embeddings and 4B for multi-token prediction. On a PC, Strata can divide that workload between GPU memory, system RAM, the CPU and SSD lookup. The useful choice is which format completes your tasks within your memory and waiting-time budget.
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Claude Opus 5.5
Claude Opus 5.5 is being used for long-running coding agents and, more visibly this week, code-drawn animations and product videos. It accepts text and images and returns text; a browser or rendering tool turns the code into moving images. Its Claude API rates are $4 per million input tokens and $20 per million output tokens, twice Sonnet 5.5’s. The choice depends on the accepted result, the revisions needed, and the total task cost.
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Claude Sonnet 5.5
Claude Sonnet 5.5 is being used for routine coding, bug fixes, documents, and code-drawn animation. Its standard Claude API rates are $2 per million input tokens and $10 per million output tokens, half Opus 5.5’s uncached rates. Early creator reports show that a cheaper model can also build visual work, but the useful measure is the time, tool calls, and revisions needed for an accepted result.
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GPT-6.1 Sol
GPT-6.1 Sol is OpenAI’s model for complex coding, research and computer use. Its standard short-context API rates are $2 per million input tokens and $10 per million output tokens. Compare it with GPT-6 Astra on task cost, reasoning effort and time to a usable result. The reports below cover repository repairs, visual builds and the tradeoffs users found.
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Gemini 4 Argon
Gemini 4 Argon is Google’s model for long software-engineering, enterprise and research tasks. Since October 13, developers can use its paid API and subscribers can access it through supported Google products. Introductory API input/output rates are $2/$10 per million tokens through November 30, then $4/$20 from December 1. Independent evaluations show strong task results alongside substantial output-token use, which makes the full task bill worth comparing.
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Ling 3 Flash
Ling-3.0-flash is inclusionAI’s open-weight text model with 124B total parameters, 5.1B active per token and a 256K context window. Its low hosted token prices make it worth trying for coding and tool use. Community results point to a practical starting place: a bounded task with an external completion check. Local deployment is a separate choice, with quantized weights around 70GB in several reported setups.
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Kolibri 1
Kolibri 1 is Aleph Alpha’s Apache-2.0 text model for German and English. Its mixture-of-experts architecture has 78.1B total parameters and about 3.46B active per token. Consider it for document questions, drafting and extraction on infrastructure you control. The official FP8 weights occupy about 78GB, so the first deployment decision is GPU capacity; the next is how much reasoning time each accepted task needs.
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Reflection Beam
Reflection Beam 1.0 is a text model for coding, reasoning and agents. Its released Apache 2.0 checkpoints contain 501.3B total parameters, with 23.4B active per token, in BF16, FP8 and NVFP4 formats. Choose the hosted Reflection API for a first task or size a deployment around the full checkpoint and your intended context length.
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Ling 3.1 Flash
Ling 3.1 Flash is inclusionAI’s text model for reasoning, coding and tool-driven work. Start with a bounded code or research task through Vercel AI Gateway, OpenRouter or OpenCode Zen. Vercel’s free offer runs through October 13, 2026: its regular model ID starts billing afterward, while its separate -free ID stops serving. For a trial with no automatic switch to paid inference, choose that -free ID and compare the accepted result with a paid alternative before moving ongoing work.
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Mistral Large 4
Mistral Large 4, nicknamed “Le Chonk,” is a multimodal model for document questions, structured extraction and tool-driven work. The practical starting point is its public-preview API: launch pricing is $0.68 per million input tokens and $2.09 per million output tokens. Its 1.05 trillion total parameters make self-hosting a separate infrastructure decision, even though each token activates a much smaller part of the model.
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Claude Haiku 5.5
Claude Haiku 5.5 is Anthropic’s fast hosted model for routing, extraction and coding subagents. Its low starting price makes frequent calls practical, but agent benchmarks show why effort, context length and the number of attempts belong in the budget. It accepts text and images, supports a one-million-token context, and generates up to 128K tokens per standard request.
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MAI-Code-1.1-Flash
MAI-Code-1.1-Flash is Microsoft’s coding model for repository questions, refactoring and tool-driven development, including image-to-code work. The cloud model is available in GitHub Copilot. Microsoft’s October update also introduces a local build, with a much larger device-memory budget than its lightweight coding category might suggest.
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GPT-6 Luna
GPT-6 Luna is OpenAI’s efficient general-purpose model for focused, high-volume work: document extraction, summaries, grounded replies and bounded coding steps. Standard API rates start at $0.10 per million input tokens and $0.50 per million output tokens. Longer prompts, cache writes and repeated agent turns change what it costs to finish a task.
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Step 5 Preview
Step 5 Preview is StepFun’s reasoning and coding model, available through the API and downloadable weights. Its hosted API accepts text, images and video and returns text, with a 1M-token input context and up to 64k output tokens. International and China accounts have separate token prices.
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Claude Mythos 5.1
Claude Mythos 5.1 is the verified-access version of Claude Fable 5.1, with the same underlying model and more permissive safeguards for approved cybersecurity and life-sciences work. It accepts text and images and produces text, with a 1M-token context window and up to 128K output tokens. The Claude API lists $10 per million input tokens and $50 per million output tokens; use it through an approved verification grant.
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Muse Wonder
Muse Wonder is Meta’s hosted model for coding, reasoning and agents that work across many steps. It reads text, images, audio, video and PDFs and returns text. Use muse-wonder-1.0 through Meta Model API at $4 input and $20 output per million tokens, or use it in Muse Code. Muse Wonder Full is a separate subscription variant in Muse Code.
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MiMo V2.6
MiMo V2.6 is Xiaomi’s multimodal Pro and Flash family for coding, research and tool workflows. The September 22 release offers hosted APIs and downloadable checkpoints. Flash starts at $0.14 per million uncached input tokens and $0.28 per million output tokens on the overseas API; Pro’s ordinary overseas input/output rates are $0.435/$0.87 per million tokens; Xiaomi recommends Pro for complex long-running work and Flash for frequent calls. Choose the billing route before comparing a complete task.
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Youtu-Parsing-Omni
Youtu-Parsing-Omni is Tencent’s downloadable 5B model for turning documents, images and audio/video into structured JSON. It fits workflows that need reading order, tables, locations or timestamps as well as recognized content. Its custom license excludes European Union use. Choose the official task recipe and measure the whole pipeline before renting a GPU; Tencent’s published model materials give no hosted API tariff or verified minimum VRAM requirement.
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LFM2.5-24B-A2B
LFM2.5-24B-A2B is Liquid AI’s downloadable reasoning model for text and tool agents. It has 24B total parameters and activates about 2B per token. Use the Liquid API to start without managing weights, or serve the model locally when keeping the agent’s data on your hardware matters. The current API tariff is $0.05 per million input tokens, $0.025 for cached input and $0.70 for output.
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Muse Spark Open
Muse Spark Open is Meta’s open-weight model for coding, multimodal reasoning and tool agents, released October 15, 2026. It has 816B total parameters, 42B active per token and a 1M-token model context. Hosted inference is the practical first step for most users; self-hosting needs substantial GPU or unified memory, with hardware requirements depending on the quantization and runtime.
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Nemotron 3.5
NVIDIA Nemotron 3.5 Super VL is an open-weight vision-language model for coding, tools and document or video understanding. The 120B model activates 12B parameters per token and supports up to 1M context. Bolt is a separate 74B/A9B model with up to 256K context and compact local formats; its 24GB variant name does not describe Super VL’s hardware requirement. The newer text-only Bolt E4B is a separate 8B-total / 4B-effective checkpoint.
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MiniCPM-V 4.7
MiniCPM-V 4.7 is OpenBMB’s open-weight vision-language family for images, documents and video understanding, with text responses. Choose the compact 1B model or the 35B-A3B mixture of experts. The much-publicized phone memory figure belongs to an optimized LES deployment, so choose the model artifact and runner before budgeting a device.
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Elorian Glimpse
Glimpse is Elorian’s research-preview visual reasoning model. It examines images and video, revisits visual evidence and returns answers for tasks such as chart analysis, counting and event understanding. The announced hosted input/output rates are $0.60/$3.00 per million tokens. Start through Elorian’s platform and budget the complete reasoning task.
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Mellum 2.1 Thinking
Mellum 2.1 Thinking is JetBrains’ open-weight text model for coding agents, tool use and reasoning. Its 12B-parameter mixture of experts activates 2.5B parameters per token. Official GGUF files are available for local runners alongside the BF16 checkpoint. Start with a small code task, then choose a quantization and context that leave room for the runtime.
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Underdog Saluki 27B
Underdog Saluki 27B is a compressed Qwen3.8-27B model for local text tasks and tool calling. Its recommended IQ2-mix GGUF download is 7.89GB. That smaller file can make a local trial easier, while context, runtime buffers and optional vision still need extra memory. Start with text, then check the quality and complete task time on your own workload.
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MiniMax M3.1 Flash
MiniMax M3.1 Flash is a multimodal coding and agent model with a one-million-token context window. Use the MiniMax API for your application, MiniMax Code for an existing coding workflow, or the published weights with a compatible serving recipe. Thinking stays enabled, with an effort setting that changes how much reasoning the model performs. For a budget, count the full sequence of model calls, tool results and retries needed to finish the task.
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Mercury 3
Mercury 3 is Inception’s hosted diffusion language model for text applications. It supports a one-million-token context window, tool calling and structured outputs through a chat-completions API. Its launch discount lowers token rates, while the time and cost of an agent task still depend on context, reasoning and external tools.
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Flint
Flint is Recursive’s Apache 2.0 language model for coding agents: investigating repositories, fixing bugs, implementing changes and writing tests. It has 39.8B total parameters with about 2.5B active per token. The official rec engine offers a 4-bit Apple Silicon path with at least 48GB unified memory and about 30GB free disk space; the original BF16 checkpoint is a separate, roughly 79.6GB download.
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Raon-1 mini preview
Raon-1 mini preview is KRAFTON AI’s Apache 2.0 text reasoning and tool-calling model, with Korean conversation among its stated focuses. The card calls it 30B-A4B; its detailed table lists 28.8B total and 4.3B activated parameters. A documented NVFP4 and DFlash2 recipe targets one RTX 5090 32GB at a 32,768-token context. Choose that exact configuration before budgeting hardware.
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Kimi K3.1 Pro
Kimi K3.1 Pro is Moonshot AI’s 3T-class model for coding and longer tool-driven work, with a 1,048,576-token context window. Pro and Pro Highspeed are available through Kimi applications and the API. Highspeed doubles the fresh-input and output rates; both use the same cache-read rate. Full weights are promised by November 4, 2026, so today’s deployment choice is hosted access.
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Nemotron 3.5 Bolt E4B
NVIDIA Nemotron 3.5 Bolt E4B is a downloadable text model for conversational interfaces and tool use. NVIDIA lists 8B total parameters, 4B effective and up to 64K context, with a Q4_K_M GGUF release. The “4GB” label does not include the full download or runtime memory: the main GGUF alone is about 6.18 GB, before cache, buffers and the optional drafter.
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Ornith-1.5-122B
Ornith-1.5-122B is an MIT-licensed reasoning and text-generation model with a Qwen3.5 MoE architecture. It supports tool calls and a native 262,144-token context. Start by choosing a checkpoint format and a serving runtime: the public BF16 weights occupy about 250GB, before runtime memory and request state.
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Ling-3.0-flash-Sante
Ling-3.0-flash-Sante is a text-generation LLM built on Ling-3.0-flash, specialized for healthcare research. Its hybrid MoE architecture has 124B total parameters and activates 5.1B per token. The weights are available under MIT.
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GPT-6.1 Terra
GPT-6.1 Terra is OpenAI’s model for visual reasoning, computer use and everyday writing. It reads text and images and produces text or tool calls. Use it in ChatGPT Work or Codex, or connect the API to an application and an execution environment. Standard API rates start at $1 per million input tokens and $5 per million output tokens; a completed task can include many model turns, screenshots and retries.