AI Models

Anthropic's default flagship for agentic coding and knowledge work, at $4/$20 per million tokens with a 1M-token context.

ElevenLabs' expressive text-to-speech pair, tied for first on Artificial Analysis's speech arena; v4 Turbo is built for voice agents.

OpenAI's current image models: Flare for everyday generation and editing, Sunburst for precise multi-step edits.

Anthropic's mid-tier model: close to Opus 5.5 on many benchmarks at half the price, $2/$10 per million tokens.

OpenAI's mid-priced workhorse: near-Astra results on coding and computer use at $2/$10 per million tokens.

Google's Flash-tier image model: fourth in blind votes, from about 3.4 cents per 1K image, with up to 14 reference images.

Voyage AI's newest rerankers, with a 32K-token window, instruction following and prices from $0.02 per million tokens.

Anthropic's small, fast model, from $0.10/$0.50 per million tokens, with a 1M-token context and adjustable effort.

Google's expressive text-to-speech, fifth in blind votes at about $16.50 per million characters, with voice design and cloning.

Google's new flagship reasoning model: reads text, images, audio, video and PDFs, with a 1M-token context.

Xiaomi's 1-trillion-parameter open-weight model, top of the open models on Artificial Analysis, at $0.87 per 1M output.

Perplexity's open 27B and 4B decision models, also sold as a $0.02-per-million-token API: text and images in, probabilities out.

Alibaba's Apache 2.0 dense model: 27 billion parameters, image and video input, and coding scores that rival models many times its size.

Voyage AI's top text embedding model, built on mixture-of-experts, sharing one vector space with cheaper Voyage 4 models.

Alibaba's newest video model, top of the current Artificial Analysis video board, with clips up to 30 seconds.

Cartesia's low-latency text-to-speech model for voice agents, in 44 languages.

Cohere's October 2026 reranker in Pro and Fast sizes, with calibrated scores and an option to return only the relevant spans.

ElevenLabs' batch transcription model: 2.2% word error rate on independent tests, $0.22 per hour, with diarization and entity detection.

Google's Apache 2.0 open model family, from phone-sized E2B to a 31B model for one GPU, with image, video and audio input.

Z.ai's open-weight coding and agent model, near-MIT licensed, at $1.40/$4.40 per million tokens on its API.

Moonshot AI's post-trained upgrade to Kimi K3: fourth on Artificial Analysis's index at a third less per token.

A 0.9-billion-parameter document parser that tops the main OCR benchmark, at least on its makers' count.

ByteDance's joint audio-video model with 30-second takes, heavy multimodal referencing and timestamp edits.

Mistral's October 2026 speech family: transcription in 50 languages from $0.0035 a minute, real-time under 500 ms, and voice cloning.

Anthropic's top tier for hard reasoning and long-horizon agent work, priced at $10/$50 per million tokens.

DeepSeek's largest open-weight model: 1.6T parameters, MIT licence, 1M-token context and very low API prices.

Google's open, on-device embedding model that puts text, code, images, audio and video in one space.

Google's first multimodal embedding model: text, images, video, audio and PDFs in one shared vector space.

Google's default video model, built on Gemini, for short clips you refine through conversation.

Z.ai's MIT-licensed 320B mixture-of-experts model with image and video input, a 1M-token context and a $0.15/$0.50 API price.

OpenAI's small, cheap model for high-volume tasks, at $0.10/$0.50 per million tokens with a 1.05M-token context.

OpenAI's full-duplex voice model: it listens while it talks and hands the thinking to a text model you choose, at $0.05 a minute.

Jina AI's small multilingual text embedders and their omni siblings for images, video and audio, sharing one vector space.

Small 0.6B multilingual reranker from Jina AI (now Elastic) that scores a whole candidate list in one pass, with 131K-token context.

Moonshot AI's 2.8-trillion-parameter open-weight model, strong on agent and browsing tasks, with a 1M-token context.

Microsoft's in-house image model, fifth on Artificial Analysis's arena, in preview on Foundry at about $39 per 1,000 images.

Midjourney's eighth-generation image model, now at V8.2 with an instruction editor, sold only as a monthly subscription.

MiniMax's 33B video model with stereo sound: the top open-weights entry, licensed out of the US, EU, UK and South Korea.

Alibaba's open multimodal embedder for text, images, screenshots and video in one vector space, in 2B and 8B sizes.

Cohere's multimodal embedding models for text, images and PDFs, with a 128K-token input and Pro and Fast tiers that share one vector space.

DeepSeek's open MIT-licensed mixture-of-experts model with image input and a 1M-token context, from $0.15 per million input tokens off-peak.

Black Forest Labs' multimodal model for video with audio and images, built on one shared architecture.

Google's dedicated speech-to-text models, with a streaming Live variant, at about half a cent per minute.

OpenAI's flagship reasoning model for the hardest work, at $10/$50 per million tokens with a 1.05M-token context.

Tencent's 770B open-weight flagship (formerly Hunyuan) under plain Apache 2.0, strong at coding with a 1M-token context.

Mistral's document OCR with paragraph bounding boxes, block labels and confidence scores in 170 languages, at $4 per 1,000 pages.

Google's premium image model: four times the price of Nano Banana 2.1, but still the one reviewers trust for realism.

Alibaba's Apache 2.0 embedding and reranking family, from a 0.6B model to an 8B that topped MTEB multilingual in June 2025.

Qwen's preview of the Qwen4 architecture: 6 billion active parameters, strong vendor-reported coding scores and a restrictive licence.

Alibaba's 2.4-trillion-parameter flagship, with open weights and a $2/$6 API that adds image, video and 1M context.

Mistral's open 3B safety classifier that checks text and images against moderation policies you write in plain language.

StepFun's 600B open-weight model with a 1M-token context, as smart as Kimi K3 on Artificial Analysis for half the cost.

vLLM Semantic Router's upgraded 27B decision model: reads an input once, answers up to 255 questions, and locates objects in video.

ByteDance's closed flagship behind the Doubao app: a leader on video and visual understanding, sold mainly through China's Volcano Engine.

Google's cheapest current Gemini text model, very fast once it starts, at $0.30/$2.50 per million tokens and with a free tier.

Google's mid-tier model for agents and documents, reading text, images, audio, video and PDFs with a 1M-token input.

Kuaishou's new video model: 30-second takes, 10 keyframes, 15 references and stereo sound, but no public API yet.

Mistral's small open models in three sizes, each with base, instruct and reasoning versions and image input, under Apache 2.0.

Meta's 30B Apache 2.0 agent model, distilled from Muse Spark and packaged with tested 4-bit builds for one consumer GPU.

Meta's first frontier-priced model: strong on long coding and legal agent work, behind Claude Opus 5.5 on most of Meta's own table.

NVIDIA's open 120B hybrid Mamba MoE that reads images, documents and video, with a 1M-token context and published training recipes.

NVIDIA's 600M-parameter transcription model for 25 European languages: the fastest on Artificial Analysis's board.

ByteDance's flagship image model, built for editable design work: up to 20 layers, coordinate edits and text in 14 languages.

Baidu's rework of DeepSeek-OCR that reads dozens of pages in a single pass without running out of memory.

vLLM Semantic Router's open 27B decision model with video input and stock vLLM serving, already overtaken by its own d3-turbo.

Deepgram's speech-to-text model: second-fastest on Artificial Analysis's test and cheap per minute, but well off the accuracy leaders.

Black Forest Labs' 5.6B open image model with FLUX 3's 4K output, editing and bounding boxes, free to use commercially under $5M revenue.

OpenAI's restricted cybersecurity model for vetted researchers: it writes exploits and tests defences that its standard models refuse.

OpenAI's larger open-weight reasoning model: Apache 2.0, 5.1B active parameters, and small enough for a single 80GB GPU.

OpenAI's restricted life-sciences model for approved research organisations: drug discovery, genomics and protein work.

IBM's Apache 2.0 family of 3B, 8B and 30B dense reasoning models for agents and coding, released in August 2026.

Ideogram's 9.3B design model, strong on in-image text; its downloadable weights are non-commercial, so paid work goes through the API.

Ant Group's 560B open-weight model: fast at over 200 tokens a second, MIT-licensed, with a 1M-token context.

OpenBMB's 2.5B on-device model: tool calls and code fixes like a 4B model, with its checkpoints and training data published.

Meta's closed agent and coding model: a 1M-token context at $1.25/$4.25, now the budget tier beneath Muse Wonder.

Meta's 816B open-weight Muse Spark: a 1M-token agent model you can self-host, under a licence with strings attached.

Alibaba's 7B open image generator and editor tops the open-weights board and outputs transparency, but is licensed for research only.

Mistral's fast fill-in-the-middle model for code autocomplete, still a default in IDE tools; not built for agent work.

Recursive's first model: an open-weight coding model with 40B parameters, 2.5B active, built to run fast on a laptop.

OpenAI's replacement for Whisper: more accurate and cheaper than GPT-4o Transcribe, but without timestamps or speaker labels.

An 82M-parameter Apache 2.0 speech model, mid-table on quality and the cheapest voice on Artificial Analysis's board.

Luma's video model for post-production: 16 keyframes, native HDR and 16-bit EXR, sold per clip through the API and the Luma app.

TwelveLabs' video-first embedding model: video, audio, images, text and PDF pages in one 512-dimension space, billed per token.

MiniMax's open-weight multimodal MoE: 1M-token context, sparse attention, a $0.30/$1.20 API and a licence with strings attached.

Mistral's 1-trillion-parameter flagship, trained and hosted in Europe, in preview at $1.36/$4.18 with weights promised.

Sakana AI's orchestrator: one API that splits each task across a hidden pool of frontier models and merges the answers.

ZeroEntropy's 4B open reranker with calibrated scores, Apache 2.0 since Notion bought the company and its hosted API went dark.

Cohere's 218B mixture-of-experts model for agents and multilingual RAG, with Apache 2.0 weights that fit on two H100s.

OpenAI's Apache 2.0 open-weight reasoning model with 3.6B active parameters, sized to run in 16GB of memory on a laptop or consumer GPU.

SpaceXSI's flagship Grok model for chat, code and agents: $2/$6 per million tokens, a 500K context and very long thinking times.

TypeSafe AI's hosted decision model: typed choices, scores and yes/no probabilities for $0.042 per million input tokens, output free.

Lightricks' 22B open video model with synchronised sound and multishot scenes, up to 4K on its API from $0.09 a second.

Mistral's 128B dense open-weight coding and agent model fits four GPUs, but its licence shuts out firms above $20M a month.

Mixedbread's Apache 2.0 rerankers in 0.5B and 1.5B sizes, with 100+ languages and an 8K-token context, built to self-host.

NVIDIA's late-interaction retrievers that search page images without OCR: accurate, storage-hungry and non-commercial at every size.

Runway's in-house video model: a 2025 leaderboard winner, now outranked, sold inside a suite that also resells its rivals.

Microsoft's MIT-licensed transcriber that takes an hour of audio in one pass and labels who spoke when.

Resemble AI's MIT-licensed voice-cloning models, from a 110M CPU model to 23 languages, with a watermark on every clip.

Cohere's December 2025 reranker in Pro and Fast versions with a 32K-token context, replaced by Rerank 5 on 21 October 2026.

DeepSeek's 3B open document reader reorders a page before reading it, but PaddleOCR-VL and Unlimited-OCR now outscore it.

Baidu's closed flagship, distilled from ERNIE 5.0 at a fraction of the cost: strong at search and maths, hard to buy outside China.

Mistral's Apache 2.0 mixture-of-experts: 119B parameters, image input, switchable reasoning, $0.15/$0.60 per million tokens.

OpenAI's top embedding model, unchanged since January 2024: supported everywhere and cheap, but no longer a retrieval leader.

OpenAI's open-weights speech recognition model, still the default for self-hosted transcription.

A 6B Apache-licensed image model from Alibaba's Tongyi lab that runs in eight steps on a 16GB consumer GPU.

Cloudflare's open 27B decision model that scores typed choices about text and images, served on Workers AI behind a Jev-compatible API.

TII's 7B maths and coding reasoning model with a hybrid Transformer-Mamba design, a 256K context and an attribution licence.

Fastino's sub-billion-parameter zero-shot classifier: pass any labels at call time and get one back on a CPU, no prompt or generation.

A 122B open-weight reasoning and coding model trained by a self-improvement loop that writes its own tasks, under MIT.

Alibaba's Apache-licensed image editor: mid-table on quality, but the cleanest licence among open editors you can ship.

Alibaba's first Qwen3.5 open model: a 397B MoE with 17B active under Apache 2.0, now outpaced by Qwen3.8 and its own hosted twin.

Sakana AI's Japanese-tuned model built on Kimi K2.6, with built-in web search and code execution behind an OpenAI-style API.

China Telecom's Apache 2.0 agent model, notable less for its scores than for being trained entirely on Huawei Ascend chips.

Tencent's 80B open image model with a reasoning step: third among open editors, but it needs an eight-GPU node and skips Europe.

Alibaba's Apache-licensed speech family: voice design from a sentence, cloning from three seconds, and no misuse safeguards.

Hugging Face's fully open 3B model, with switchable reasoning, a 128K context and its whole training recipe published.

The default embedding model of a thousand tutorials, now best kept for tests, prototypes and short English text.

Mistral's 24B Apache 2.0 coding model that runs on one RTX 4090 or a 32GB Mac, with a 256K context and image input.

Apache 2.0 decision model on ModernBERT that answers typed questions in tens of milliseconds, but needs fine-tuning to be accurate.

Microsoft's newest small Phi model: 15B, MIT licensed, reads images and can switch step-by-step reasoning on or off.

Microsoft's 5.6B MIT-licensed model that takes speech, images and text in one network, now 20 months old.

Google's retired-from-the-API video model, still sold as GA on its enterprise cloud for teams that need extension and end-frame control.

Mistral's 123B open coding model from December 2025, now retired from its API and replaced by Mistral Medium 3.5.