Tokenator AI model catalog

All LLMs available through Tokenator. Pass the model ID in the model field of your request — Tokenator routes the traffic to the matching upstream provider. The chip next to each model is the billing multiplier: how much more (or less) its tokens cost relative to base.

Anthropiconline
Claude Opus 5
claude-opus-5
×1.9

Claude Opus 5 is Anthropic’s flagship model for demanding reasoning, coding, and long-horizon agentic work. It is particularly strong at end-to-end software tasks, code review and bug finding, visual analysis of charts and documents, complex office deliverables, and coordinating parallel subagents. The model maintains strong instruction following and tool use across extended tasks, while remaining effective at lower effort settings for workloads that prioritize latency and token efficiency.

Context 1M tokens
Geminionline
Free Gemini 3.8 Flash
free-gemini-3.8-flash
×1.7

This model is available on a free plan with set usage limits. Gemini 3.8 Flash is the most intelligent model in Google's Flash series, significantly outperforming Gemini 3.7 Flash in programming, agent-based tasks, and complex multi-step reasoning. It combines high performance with improved capabilities for analysis, planning, and execution of complex tasks, while maintaining the efficiency characteristic of the Flash series.

FreeContext 1M tokens
Anthropiconline
Free Claude Opus 5
free-claude-opus-5
×1.9

This model is available on a free plan with set usage limits. Claude Opus 5 is Anthropic's flagship model for complex logical reasoning, programming, and long-term agent management. It is particularly effective in complex software development, code review and error detection, document and diagram analysis, complex office tasks, and coordinating multiple concurrent subagents. Claude Opus 5 reliably follows instructions and uses tools efficiently, even in lengthy, multi-step tasks. It is also well-suited for scenarios where low latency and more efficient token usage are essential.

UnstableFreeContext 1M tokens
Z-AIonline
Free GLM 5.3 Flash
free-glm-5.3-flash
×1.9

This model is available on a free plan with limited usage. GLM-5.3-Flash is a native multimodal model from Z.ai that demonstrates high performance in programming, agent-based tasks, and working with long-term contexts.

FreeContext 1M tokens
Anthropiconline
Claude Sonnet 5
claude-sonnet-5
×1.7

Sonnet 5 is Anthropic's most capable Sonnet-class model, with frontier performance across coding, agents, and professional work.

Context 1M tokens
DeepSeekonline
Deepseek V4.1 Flash
deepseek-v4.1-flash
×1.7

DeepSeek V4.1 Flash is a new high-performance model from DeepSeek that significantly outperforms V4 Pro across key metrics, including task quality, generation speed, cost efficiency, and overall execution time. The model is designed for coding, complex reasoning, agentic workflows, and multi-step tasks, delivering Pro-level capabilities with higher speed and significantly better efficiency.

Context 1.05M tokens
DeepSeekonline
Deepseek V4 Pro
deepseek-v4-pro
×1.8–×2

DeepSeek V4 Pro 0813 is a large-scale mixture-of-experts model from DeepSeek. This is the GA release of DeepSeek V4 Pro.

Context 1.05M tokens
OpenAIonline
GPT-6 Astra
gpt-6-astra
×5–×6

GPT-6 Astra is OpenAI's flagship model for demanding end-to-end work. It is suited for advanced analysis, software engineering, deep research, scientific work, and document creation, with particular strengths in long-horizon agentic tasks that involve computer and browser use.

Context 1M tokens
OpenAIonline
Free GPT-6 Astra
free-gpt-6-astra
×6

This model is available on the free tier with predefined usage limits. GPT-6 Astra is OpenAI's flagship model for demanding end-to-end work. It is suited for advanced analysis, software engineering, deep research, scientific work, and document creation, with particular strengths in long-horizon agentic tasks that involve computer and browser use.

FreeContext 1M tokens
OpenAIonline
GPT-5.6 Sol
gpt-5.6-sol
×1.8–×1.9

GPT-5.6 Sol is the flagship model in OpenAI's GPT-5.6 series. It is suited for complex reasoning, coding, and agentic workflows, and is particularly strong at command-line and multi-step coding tasks and long-horizon problem solving.

Context 1M tokens
Geminionline
Gemini 3.8 Flash
gemini-3.8-flash
×1.4–×1.7

Gemini 3.8 Flash is Google's most intelligent Flash model with significant gains from 3.7 Flash across software engineering, agentic tasks, and multi-step reasoning.

Context 1M tokens
Anthropiconline
Claude Sonnet 4.6
claude-sonnet-4-6
×1.7

Sonnet 4.6 is Anthropic's most capable Sonnet-class model yet, with frontier performance across coding, agents, and professional work.

Context 1M tokens
OpenAIonline
GPT-5.6 Terra
gpt-5.6-terra
×1.7–×1.8

GPT-5.6 Terra is a balanced model in OpenAI's GPT-5.6 series, positioned between the flagship Sol tier and the cost-efficient Luna tier. It is suited for everyday coding, reasoning, and agentic tasks where capability and cost need to be balanced, offering strong performance at roughly half the cost of Sol.

Context 1M tokens
Anthropiconline
Claude Opus 4.8
claude-opus-4-8
×1.8

Claude Opus 4.8 is Anthropic's most capable generally available model in the Opus family. It supports text, image, and file inputs with text output, with reasoning support and a 1M-token context window.

Context 1M tokens
MoonshotAIonline
Kimi K3
kimi-k3
×6–×10

Kimi K3 is a 2.8T parameter open-weight multimodal reasoning model from Moonshot AI. It is suited for complex coding, knowledge work, and long-horizon agentic workflows, and is particularly strong at navigating large repositories, using tools, debugging, and iterating against images, logs, tests, and runtime feedback. Its architecture uses KDA and Attention Residuals for computational efficiency.

Context 1M tokens
Xiaomionline
MiMo-V2.5
mimo-v2.5
×1.6

MiMo-V2.5 is a native omnimodal model by Xiaomi. It delivers Pro-level agentic performance at roughly half the inference cost, while surpassing MiMo-V2-Omni in multimodal perception across image and video understanding tasks. Its 1M context window supports complete documents, extended conversations, and complex task contexts in a single pass, making it ideal for integration with agent frameworks where strong reasoning, rich perception, and cost efficiency all matter.

Context 1M tokens
Z-AIonline
GLM 5.3 Flash
glm-5.3-flash
×1.5–×1.7

GLM-5.3-Flash is a native multimodal model from Z.ai. It is suited for efficient coding and long-horizon agent tasks. Its hybrid sparse and linear attention architecture maintains accurate long-context behavior while reducing compute overhead.

Context 1M tokens
Anthropiconline
Claude Fable 5.1
claude-fable-5.1
×13–×14

Claude Fable 5.1 improves on Claude Fable 5 across the board, with the biggest gains in agentic coding, long-running agentic workflows, and knowledge work: long code refactors, front-end and visual code generation, and finance and analysis tasks in particular. It also tends to be more concise than Fable 5 in its plans and summaries. We recommend testing it as a direct upgrade wherever you use Fable 5 today, and alongside Opus 5 on reasoning-heavy tasks.

Context 1M tokens
MiniMaxonline
MiniMax M3
minimax-m3
×1.5

MiniMax-M3 is a multimodal foundation model from MiniMax. It supports text, image, and video inputs with text output, a 1M-token context window, and is suited for long-horizon agentic work, coding, and tool use. It is built on MiniMax Sparse Attention (MSA), which replaces full attention with KV-block selection to cut per-token compute at long context — roughly 1/20 the cost of the previous generation at 1M tokens, with substantially faster prefill and decode while retaining quality across most tasks. Trained as a native multimodal model on interleaved data and tuned for multi-turn, production-like collaboration via an interactive user-simulator framework, the model is oriented toward sustained, multi-step tasks rather than single-turn execution.

Context 1M tokens
Anthropiconline
Claude Haiku 4.5
claude-haiku-4-5
×1.6

Claude Haiku 4.5 is Anthropic’s fastest and most efficient model, delivering near-frontier intelligence at a fraction of the cost and latency of larger Claude models.

Context 200K tokens
Anthropiconline
Claude Fable 5
claude-fable-5
×10–×14

Claude Fable 5 is a Mythos-class model from Anthropic, built for autonomous knowledge work and coding.

Context 1M tokens
Anthropiconline
Claude Opus 4.6
claude-opus-4-6
×1.8

Opus 4.6 is Anthropic’s strongest model for coding and long-running professional tasks.

Context 1M tokens
Anthropiconline
Claude Opus 4.7
claude-opus-4-7
×1.8

Opus 4.7 is the next generation of Anthropic's Opus family, built for long-running, asynchronous agents.

Context 1M tokens
Geminionline
Gemini 3.1 Flash Lite
gemini-3.1-flash-lite
×1.5

Gemini 3.1 Flash Lite is Google’s GA high-efficiency multimodal model optimized for low-latency, high-volume workloads.

UnstableContext 1M tokens
Geminionline
Gemini 3.1 Pro Preview
gemini-3.1-pro-preview
×1.7–×1.8

Gemini 3.1 Pro Preview is Google’s frontier reasoning model, delivering enhanced software engineering performance, improved agentic reliability, and more efficient token usage across complex workflows. Building on the multimodal foundation of the Gemini 3 series, it combines high-precision reasoning across text, image, video, audio, and code with a 1M-token context window. Designed for advanced development and agentic systems, Gemini 3.1 Pro Preview improves long-horizon stability and tool orchestration while increasing token efficiency. It introduces a new medium thinking level to better balance cost, speed, and performance. The model excels in agentic coding, structured planning, multimodal analysis, and workflow automation, making it well-suited for autonomous agents, financial modeling, spreadsheet automation, and high-context enterprise tasks.

Context 1M tokens
Geminionline
Gemini 3.6 Flash
gemini-3.6-flash
×1.4–×1.7

Gemini 3.6 Flash is a high-efficiency model from Google for coding, agentic workflows, and web and app development. It is designed to produce polished outputs with fewer unnecessary edits and less hedging, while reducing token use and the number of model calls needed to complete a task.

Context 1.05M tokens
Geminionline
Gemini 3.7 Flash
gemini-3.7-flash
×1.4–×1.7

Gemini 3.7 Flash is a multimodal model from Google for fast agentic workflows, coding, and complex multi-step reasoning. It is designed for tasks that require responsive performance and reliable multi-step problem solving.

Context 1M tokens
OpenAIonline
Gemini Embedding 001
gemini-embedding-001
×1.35

gemini-embedding-001 provides a unified cutting edge experience across domains, including science, legal, finance, and coding. This embedding model has consistently held a top spot on the Massive Text Embedding Benchmark (MTEB) Multilingual leaderboard since the experimental launch in March.

EmbeddingsContext 20K tokens
Geminionline
Gemini Embedding 2
gemini-embedding-2
×1.4

Gemini Embedding 2 is Google's first multimodal embedding model. We currently support mapping text and images into a unified vector space for semantic search and retrieval-augmented generation (RAG). It supports input context up to 8,192 tokens and flexible output dimensions from 128 to 3,072 (recommended: 768, 1536, or 3,072). Designed for cross-modal similarity — you can embed a text query and retrieve the most relevant images, or vice versa — making it well-suited for multimodal search, recommendation, and document understanding pipelines.

EmbeddingsContext 8.2K tokens
Z-AIonline
GLM 5.2
glm-5.2
×2–×3

GLM 5.2 is a large-scale reasoning model from Z.ai. It supports text input and output with a 1M-token context window, and is suited for long-horizon agent workflows, project-level software engineering, and complex multi-step automation.

Context 1M tokens
Z-AIonline
GLM 5.3
glm-5.3
×2–×4

GLM 5.3 is the latest large-scale reasoning model from Z.ai. It supports text input and output with a 1M-token context window, and is built for long-horizon agent workflows, project-level software engineering, and complex multi-step automation.

Context 1M tokens
OpenAIonline
GPT 5.5
gpt-5.5
×1.8

GPT-5.5 is OpenAI’s frontier model designed for complex professional workloads, building on GPT-5.4 with stronger reasoning, higher reliability, and improved token efficiency on hard tasks.

Context 1.05M tokens
OpenAIonline
GPT Image 2
gpt-image-2
×1–×2

GPT Image 2 combines OpenAI's GPT-5.4 model with state-of-the-art image generation capabilities from GPT Image 2.

Image genEditing
OpenAIonline
GPT Image 2.5
gpt-image-2.5
×1

GPT Image 2.5 is an image generation and editing model from OpenAI, positioned as the precision-oriented tier of the GPT Image 2.5 series. It is suited to detailed creative work where editing accuracy matters more than generation speed, via the dedicated Images API.

Image genEditing
OpenAIonline
GPT-4o mini
gpt-4o-mini
×1.5

GPT-4o mini is OpenAI's newest model after GPT-4 Omni, supporting both text and image inputs with text outputs. As their most advanced small model, it is many multiples more affordable than other recent frontier models, and more than 60% cheaper than GPT-3.5 Turbo. It maintains SOTA intelligence, while being significantly more cost-effective.

Context 128K tokens
OpenAIonline
GPT-5.6 Luna
gpt-5.6-luna
×1.6

GPT-5.6 Luna is a fast, cost-efficient model in OpenAI's GPT-5.6 series. It is suited for high-volume, latency-sensitive tasks such as chat, classification, and lightweight agentic workflows, providing capable reasoning for its price tier.

Context 1M tokens
xAIonline
Grok 4.5
grok-4.5
×1.7

Grok 4.5 is SpaceXAI's smartest model with frontier performance on coding, knowledge work, and STEM.

Context 500K tokens
xAIonline
Grok 4.6
grok-4.6
×1.7

Grok 4.6 is SpaceXAI's smartest model with frontier performance on coding, knowledge work, and STEM.

Context 500K tokens
xAIonline
Grok Build 0.1
grok-build-0.1
×1.6

Grok Build 0.1 is SpaceXAI’s fast coding model trained specifically for agentic software engineering workflows. It supports text and image inputs with text output, and is optimized for interactive coding agents, tool use, and multi-step development tasks. The model powers SpaceXAI’s Grok Build CLI and features a 256K context window with no text output limit, making it well suited for long-horizon coding and automation workflows. Currently in early access.

Context 256K tokens
xAIonline
Grok Imagine Image 2.0
grok-imagine-image-2.0
×3

Grok Imagine Image 2.0 is an image generation and editing model from xAI. It is suited for creating images from text prompts and editing images from references, with low and medium quality modes.

Image genEditing
xAIonline
Grok Imagine Video 1.5
grok-imagine-video-1.5
×20–×72

Grok Imagine Video 1.5 is a video generation model from SpaceXAI. It creates videos from text prompts, with an optional starting image to guide the scene. It can direct subject and camera motion, pacing, atmosphere, and physical behavior while maintaining visual continuity, and can generate synchronized sound effects, ambience, and dialogue.

Video gen1080pWith audioWith a reference
MiniMaxonline
H3
hailuo-3
×35

MiniMax H3 — это облегченная модель генерации видео с открытыми весами от MiniMax. Она разработана для точного многомодального редактирования и контролируемой генерации контента, включая редактирование по инструкциям, рендеринг текста и брендов, а также перенос движения из видео в видео. Модель подходит для коммерческих творческих рабочих процессов в рекламе, электронной коммерции, играх и дизайне интерфейсов, с нативным аудиовизуальным выводом для генерации на основе референсов.

Video gen768pWith audioWith a referenceYour own frames
Tencentonline
Hy-MT2-1.8B
hy-mt2-1.8b
×1.4

Hy-MT2-1.8B is a compact 1.8B-parameter translation model from Tencent. It supports 33 language pairs and five Chinese dialect and minority-language pairs, with workflows for structured, delimiter-based, contextual, glossary-based, and style-guided translation.

Context 8.2K tokens
Tencentonline
Hy-MT2-30B-A3B
hy-mt2-30b-a3b
×1.8

Hy-MT2-30B-A3B is Tencent's flagship translation model in the Hy-MT2 family. It supports 33 language pairs and five Chinese dialect and minority-language pairs, with workflows for structured, delimiter-based, contextual, glossary-based, and style-guided translation. It uses 3B active parameters out of 30B total.

Context 8.2K tokens
Tencentonline
Hy-MT2-7B
hy-mt2-7b
×1.8

Hy-MT2-7B is a 7B-parameter translation model from Tencent. It supports 33 language pairs and five Chinese dialect and minority-language pairs, with workflows for structured, delimiter-based, contextual, glossary-based, and style-guided translation.

Context 8.2K tokens
Tencentonline
Hy3
hy3
×1.7–×2.1

Hy3 is a 295B-parameter Mixture-of-Experts model from Tencent (21B active, 192 experts with top-8 routing) built for reasoning, agentic workflows, and real-world production use. It supports a configurable reasoning effort: a direct no-think mode by default, plus low and high chain-of-thought modes for complex math, coding, and multi-step problems. With a 256K context window, Hy3 targets long-horizon tasks, including improved coreference resolution, multi-turn constraint tracking, and stable tool-calling that generalizes across agent scaffoldings. Tencent positions it as a reliable, cost-effective option across coding, document processing, financial analysis, game development, and frontend design, with a strong emphasis on grounded, anti-hallucination behavior that answers when grounded and flags when evidence is missing rather than fabricating.

Context 262.1K tokens
Tencentonline
Hy4 preview
hy4-preview
×1.5

Tencent: Hy4 preview is a mixture-of-experts model from Tencent, with 49B active parameters out of 770B total. It is designed for coding agents, complex tool-use workflows, and productivity tasks that require planning, context continuity, and sustained multi-step execution.

Context 1M tokens
MoonshotAIonline
Kimi K2.7 Code
kimi-k2-7-code
×3–×4

MoonshotAI: Kimi K2.7 Code is a coding-focused model in Moonshot AI's Kimi K2 family, built to complete end-to-end programming tasks reliably over long contexts.t

Context 262.1K tokens
Meituanonline
LongCat 2.0
longcat-2.0
×4

LongCat 2.0 is a sparse mixture-of-experts language model from Meituan, with 48B active parameters out of 1.6T total. It is suited for coding, repository-level changes, long-horizon problem solving, and agentic workflows.

Context 1M tokens
Inceptiononline
Mercury 2.5
mercury-2.5
×1.3

Mercury 2.5 is the fastest reasoning LLM, and the latest diffusion LLM (dLLM) from Inception. Instead of generating tokens sequentially, Mercury 2.5 produces and refines multiple tokens in parallel, achieving 1,107 tokens/sec on standard GPUs. It delivers a 10+ point jump in intelligence over Mercury 2, comparable quality to cost-optimized frontier models like GPT-5.6 Luna (Low), Gemini 3.5 Flash-Lite, and Claude Haiku 4.5. Mercury 2.5 supports tunable reasoning levels, parallel tool calls, and schema-aligned JSON output. It's built for production workloads where latency compounds: search agents, voice pipelines, and coding subagents.

Context 260K tokens
Xiaomionline
MiMo-V2.5-Pro
mimo-v2.5-pro
×1.7

MiMo-V2.5-Pro is Xiaomi’s flagship model, delivering strong performance in general agentic capabilities, complex software engineering, and long-horizon tasks, with top rankings on benchmarks such as ClawEval, GDPVal, and SWE-bench Pro. It can independently and autonomously complete professional tasks that would take human experts days or weeks, involving more than a thousand tool calls. Its context length of up to 1M makes it well suited for integration with a wide range of agent frameworks.

Context 1M tokens
Metaonline
Muse Image
muse-image
×1

Muse Image is an image generation model from Meta that generates and edits images from text and reference images. It supports text-to-image generation, targeted image editing, multi-image composition, reference-image conditioning for style and subject consistency, and precise text rendering within generated images. Iterative editing works by passing the previous output image back with a new instruction

Image gen
Metaonline
Muse Spark 1.2
muse-spark-1.2
×9

Muse Spark 1.2 is a reasoning model from Meta, designed for complex agentic tasks. It accepts text, images, video, audio, and PDF documents, returns text, and offers a 1M-token context window. The model is built to support multi-agent workflows, whether as either a main agent that plans and delegates or as a subagent executing in parallel. It works across multiple coding harnesses and supports structured output, parallel function calling, and configurable reasoning effort. In Meta’s testing, it performs well on multi-file refactors, extended debugging sessions, whole-repository generation, and tasks that stretch well past a single prompt.

Context 1.05M tokens
Metaonline
Muse Spark 1.3
muse-spark-1.3
×9

Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running agentic, multi-agent, and coding workflows. It is designed to keep track of information across extended tasks, work through conflicting inputs, and request clarification or confirmation when needed, with an emphasis on concise execution.

Context 1M tokens
Geminionline
Nano Banana 2
nano-banana-2
×1–×2

Gemini 3.1 Flash Image Preview, a.k.a. Nano Banana 2, is Google’s latest state of the art image generation and editing model, delivering Pro-level visual quality at Flash speed.

Image gen
Geminionline
Nano Banana Pro
nano-banana-pro
×2

Nano Banana Pro is Google’s most advanced image-generation and editing model, built on Gemini 3 Pro. It extends the original Nano Banana with significantly improved multimodal reasoning, real-world grounding, and high-fidelity visual synthesis. The model generates context-rich graphics, from infographics and diagrams to cinematic composites, and can incorporate real-time information via Search grounding.

Image gen
Geminionline
Omni
omni
×10

Omni is a multimodal video generation and editing model from Google DeepMind. It supports video creation from text, images, audio, and video references, as well as multi-turn editing through natural language. Omni is particularly strong at preserving characters, scene details, and visual style across edits, while using its understanding of physics and real-world context to produce coherent motion and scenes. It also supports first and last frame control, reference-to-video editing, and native audio generation.

Video gen720pWith audioWith a referenceYour own frames
Unbiasedonline
Pareto
pareto
×10

Pareto is a multimodal composite model built for research, coding, and agentic workflows, while delivering frontier-level performance across a broad range of general-purpose tasks.

Context 262.1K tokens
Qwenonline
Qwen 3.7 Max
qwen-3.7-max
×2.5–×3

Qwen3.7-Max is the flagship model in Alibaba's Qwen3.7 series. It supports text input and output and is designed for agent-centric workloads, with particular strengths in coding, office and productivity tasks, and long-horizon autonomous execution. The model offers notable gains in coding and agentic performance over prior Qwen generations and supports explicit prompt caching for efficient repeated context use.

Context 1M tokens
Qwenonline
Qwen 3.7 Plus
qwen-3.7-plus
×2–×4

Qwen3.7-Plus is a cost-effective model in Alibaba's Qwen3.7 series. It supports text and image input with text output, building on the series' text capabilities with a comprehensive upgrade to its vision-language abilities while retaining full-stack, agent-level intelligence for coding, tool use, and productivity workflows. Its distinguishing trait is multi-modal interactive hybrid agent capability: it can perceive real-world scenes, read screens and interact with GUIs, generate code from visual references, and perform end-to-end navigation within mobile apps.

Context 1M tokens
Qwenonline
Qwen 3.8 Flash
qwen-3.8-flash
×1.4–×2

Qwen3.8 Flash is a multimodal reasoning model from Alibaba. It is suited for coding assistance, agentic workflows, visual understanding, document and codebase analysis, desktop interaction, chart analysis, and long-video analysis.

Context 1M tokens
Qwenonline
Qwen 3.8 Max
qwen-3-8-max
×7–×10

Qwen 3.8 Max is Alibaba’s next-generation flagship model built for complex coding, analytical, and professional workflows. It excels at full-stack development, data analysis, office automation, and long-running multi-step tasks.

Context 1M tokens
ByteDanceonline
Seedance 2.0
seedance-2.0
×35

Seedance 2.0 is a video generation model from ByteDance. It supports text-to-video, image-to-video with first and last frame control, and multimodal reference-to-video. It is particularly strong at preserving character consistency, visual style, and camera movement from reference material.

Video gen720pWith audioWith a reference
ByteDanceonline
Seedance 2.0 Fast
seedance-2.0-fast
×40

Seedance 2.0 Fast is a video generation model from ByteDance. It supports text-to-video, image-to-video with first and last frame control, and multimodal reference-to-video. It prioritizes generation speed and lower cost over maximum output quality.

Video gen720pWith audioWith a reference
ByteDanceonline
Seedance 2.0 Mini
seedance-2.0-mini
×30

Seedance 2.0 Mini is a video generation model from ByteDance. It supports text-to-video, image-to-video with first and last frame control, and multimodal reference-to-video with image, video, and audio inputs. It supports 480p and 720p output for 4-15 second videos.

Video gen720pWith audioWith a reference
ByteDance Seedonline
Seedream 5.0 Lite
seedream-5.0-lite
×2

Seedream 5.0 Lite is an image generation model from ByteDance Seed. It is suited for professional visual creation that benefits from web-connected retrieval, complex-prompt comprehension, visual references, and broad knowledge coverage.

Image genEditing
ByteDance Seedonline
Seedream 5.0 Pro
seedream-5.0-pro
×3

Seedream 5.0 Pro is an image generation and editing model from ByteDance Seed. It is suited for commercial visual-production workflows that require precise editing control, lifelike scenes, and natural rendering.

Image genEditing
Upstageonline
Solar Pro 4
solar-pro-4
×1.4

Solar Pro 4 is Upstage's cost-efficient large language model, featuring a 524K context window. It is built for long-horizon tasks and agentic workflows, with strong capabilities in office productivity, document-intensive work, and coding.

Context 524.3K tokens
OpenAIonline
Text Embedding 3 Large
text-embedding-3-large
×1.2

text-embedding-3-large is OpenAI's most capable embedding model for both english and non-english tasks. Embeddings are a numerical representation of text that can be used to measure the relatedness between two pieces of text. Embeddings are useful for search, clustering, recommendations, anomaly detection, and classification tasks.

EmbeddingsContext 8.2K tokens
OpenAIonline
Text Embedding 3 Small
text-embedding-3-small
×1.0

text-embedding-3-small is OpenAI's improved, more performant version of the ada embedding model. Embeddings are a numerical representation of text that can be used to measure the relatedness between two pieces of text. Embeddings are useful for search, clustering, recommendations, anomaly detection, and classification tasks.

EmbeddingsContext 8.2K tokens
Cursoroffline
Composer 2.5
composer-2.5

An enhanced auto-agent tool in the code editor designed for end-to-end project-level development.

Context 1M tokens
Alibabaoffline
HappyHorse 1.1
happyhorse-1.1

HappyHorse 1.1 is a video generation model from Alibaba. It generates short videos from a text prompt, a single starting image, or a set of reference images, with output up to 1080p and durations of 3 to 15 seconds. It is suited for creative content, social media clips, and image-driven animation, and improves on the prior version with stronger prompt adherence, smoother motion, and more consistent characters across frames.

Video gen1080pWith audioWith a referenceYour own frames
ByteDanceoffline
Seedance 2.5
seedance-2.5

Seedance 2.5 is a video generation model from ByteDance. It is suited for long-form storytelling, multimodal reference-based generation, video editing, and video extension. It supports first-frame and first-and-last-frame control.

Video gen720pWith audioWith a reference

73 models in the catalog, 70 available right now, 20 model vendors, 8 for image generation, context up to 1.05M tokens

Models by vendor: