NVIDIA Nemotron 3 Ultra is an open frontier-reasoning and orchestration model from NVIDIA, with 55B active parameters out of 550B total (MoE). Built on a hybrid Transformer-Mamba mixture-of-experts architecture, it...
Models
Every model in the catalog with source-linked pricing, context limits, provider availability, and published benchmark results.
The Qwen3.5 27B native vision-language Dense model incorporates a linear attention mechanism, delivering fast response times while balancing inference speed and performance. Its overall capabilities are comparable to those of...
Claude Opus 4.1 is an updated version of Anthropic’s flagship model, offering improved performance in coding, reasoning, and agentic tasks. It achieves 74.5% on SWE-bench Verified and shows notable gains...
Claude Opus 4.1 is an updated version of Anthropic’s flagship model, offering improved performance in coding, reasoning, and agentic tasks. It achieves 74.5% on SWE-bench Verified and shows notable gains...
MiniMax-M2.5 is a SOTA large language model designed for real-world productivity. Trained in a diverse range of complex real-world digital working environments, M2.5 builds upon the coding expertise of M2.1...
MiniMax-M2.7 is a next-generation large language model designed for autonomous, real-world productivity and continuous improvement. Built to actively participate in its own evolution, M2.7 integrates advanced agentic capabilities through multi-agent...
Finance-enhanced model for financial research, multi-step investment workflows, and long-horizon planning and execution
Ling 3.0 Flash Fin is a finance-focused mixture-of-experts model from InclusionAI, built on Ling 3.0 Flash with 5.1B active parameters out of 124B total. It is designed for real-world investment...
Fast Gemini model balancing multimodal reasoning, tool use, and cost
Gemini 3.5 Flash Lite is a high-efficiency model from Google with upgraded agentic capabilities. It is suited for subagents that execute focused tasks within complex, multi-agent workflows.
GLM-4.7 is Z.ai’s latest flagship model, featuring upgrades in two key areas: enhanced programming capabilities and more stable multi-step reasoning/execution. It demonstrates significant improvements in executing complex agent tasks while...
Thinking Kimi model for slower research passes, planning, and hard technical questions
High-effort o3 tier for difficult technical reasoning and careful answers
Qwen3.5-9B is a multimodal foundation model from the Qwen3.5 family, designed to deliver strong reasoning, coding, and visual understanding in an efficient 9B-parameter architecture. It uses a unified vision-language design...
Open MiMo model for multimodal coding agents and long-context automation
Hybrid-reasoning DeepSeek model with thinking and non-thinking modes, sparse attention, and tool-use
The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. It delivers...
Qwen3.6 27B is a dense 27-billion-parameter language model from the Qwen Team at Alibaba, released in April 2026. It features hybrid multimodal capabilities — accepting text, image, and video inputs...
Qwen3-Max-Thinking is the flagship reasoning model in the Qwen3 series, designed for high-stakes cognitive tasks that require deep, multi-step reasoning. By significantly scaling model capacity and reinforcement learning compute, it...
MiniMax-M2.1 is a lightweight, state-of-the-art large language model optimized for coding, agentic workflows, and modern application development. With only 10 billion activated parameters, it delivers a major jump in real-world...
Claude Sonnet 4.5 is Anthropic’s most advanced Sonnet model to date, optimized for real-world agents and coding workflows. It delivers state-of-the-art performance on coding benchmarks such as SWE-bench Verified, with...
Claude Sonnet 4.5 is Anthropic’s most advanced Sonnet model to date, optimized for real-world agents and coding workflows. It delivers state-of-the-art performance on coding benchmarks such as SWE-bench Verified, with...
Cheapest GPT-5.4 lane for simple routing, extraction, and bulk automation
GPT-5.4 nano is the most lightweight and cost-efficient variant of the GPT-5.4 family, optimized for speed-critical and high-volume tasks. It supports text and image inputs and is designed for low-latency...
Small GPT-5 for responsive agents, coding help, and everyday automation
GPT-5 Mini is a compact version of GPT-5, designed to handle lighter-weight reasoning tasks. It provides the same instruction-following and safety-tuning benefits as GPT-5, but with reduced latency and cost....
Coding-optimized GPT model for repository edits, reviews, and agentic software work
Deliberate o-series reasoner for hard math, coding, and multi-step analysis
o3 is a well-rounded and powerful model across domains. It sets a new standard for math, science, coding, and visual reasoning tasks. It also excels at technical writing and instruction-following....
Hybrid-linear MoE reasoning model with 124B total and 5.1B active parameters for efficient agents
Newer StepFun flash model for faster agents, coding, and multimodal prompts
The Qwen3.5 Series 35B-A3B is a native vision-language model designed with a hybrid architecture that integrates linear attention mechanisms and a sparse mixture-of-experts model, achieving higher inference efficiency. Its overall...
Meituan LongCat-2.0, a reasoning model with tool calling and a 1M-token context window
Claude Sonnet 4 significantly enhances the capabilities of its predecessor, Sonnet 3.7, excelling in both coding and reasoning tasks with improved precision and controllability. Achieving state-of-the-art performance on SWE-bench (72.7%),...
MiniMax-M2 is a compact, high-efficiency large language model optimized for end-to-end coding and agentic workflows. With 10 billion activated parameters (230 billion total), it delivers near-frontier intelligence across general reasoning,...
Compared with GLM-4.5, this generation brings several key improvements: Longer context window: The context window has been expanded from 128K to 200K tokens, enabling the model to handle more complex...
Qwen3.6-35B-A3B is an open-weight multimodal model from Alibaba Cloud with 35 billion total parameters and 3 billion active parameters per token. It uses a hybrid sparse mixture-of-experts architecture combining Gated...
The Qwen3.5 122B-A10B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. In terms of...
Muse Glimmer is a 30-billion-parameter open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark for always-on local agents, tool use, coding, and image understanding.
StepFun flash lane for quick multimodal reasoning and coding assistance
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. Matching Claude Sonnet 4’s performance...
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. Matching Claude Sonnet 4’s performance...
Open Gemma instruction model for efficient chat and self-hosted deployments
Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind. Despite 25.2B total parameters, only 3.8B activate per token during inference — delivering near-31B quality at...
Fast o-series model for compact reasoning, coding, and tool use
OpenAI o4-mini is a compact reasoning model in the o-series, optimized for fast, cost-efficient performance while retaining strong multimodal and agentic capabilities. It supports tool use and demonstrates competitive reasoning...
DeepSeek-V3.2-Exp is an experimental large language model released by DeepSeek as an intermediate step between V3.1 and future architectures. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism...
Google's proven reasoning model for coding, math, and multimodal analysis
Gemini 2.5 Pro is Google’s state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks. It employs “thinking” capabilities, enabling it to reason through responses with enhanced accuracy...
OpenAI o3-mini-high is the same model as [o3-mini](/openai/o3-mini) with reasoning_effort set to high. o3-mini is a cost-efficient language model optimized for STEM reasoning tasks, particularly excelling in science, mathematics, and...
| Model | Creator | Score | Inputs | Context | Input | Output | Released | Compare |
|---|---|---|---|---|---|---|---|---|
| NVIDIA: Nemotron 3 Ultra (free)nvidia/nemotron-3-ultra-550b-a55b:free | 22.9 | 1M | Free | Free | — | |||
| Qwen: Qwen3.5-27Bqwen/qwen3.5-27b | 22.9 | 262.144K | $0.27 | $2.16 | — | |||
| Anthropic: Claude Opus 4.1anthropic/claude-opus-4.1 | 22.8 | 200K | $15 | $75 | — | |||
| Anthropic: Claude Opus 4.1 (batch)anthropic/claude-opus-4.1:batch | 22.8 | 200K | $7.5 | $37.5 | — | |||
| MiniMax: MiniMax M2.5minimax/minimax-m2.5 | 22.8 | 204.8K | $0.3 | $1.2 | — | |||
| MiniMax: MiniMax M2.7minimax/minimax-m2.7 | 22.8 | 204.8K | $0.3 | $1.2 | — | |||
| Ling 3.0 Flash Fininclusionai/ling-3.0-flash-fin | 22.6 | 262.144K | $0.075 | $0.22 | 2026-08-27 | |||
| inclusionAI: Ling 3.0 Flash Fin (free)inclusionai/ling-3.0-flash-fin:free | 22.6 | 262.144K | Free | Free | — | |||
| Gemini 3.5 Flash Litegoogle/gemini-3.5-flash-lite | 22.2 | 1.04858M | $0.3 | $2.5 | 2026-07-21 | |||
| Google: Gemini 3.5 Flash Lite (batch)google/gemini-3.5-flash-lite:batch | 22.2 | 1.04858M | $0.15 | $1.25 | — | |||
| Z.ai: GLM 4.7z-ai/glm-4.7 | 22.2 | 204.8K | $0.54 | $1.98 | — | |||
| Kimi K2 Thinkingmoonshotai/kimi-k2-thinking | 22.0 | 262.144K | $0.4 | $2.5 | 2025-11-06 | |||
| o3-proopenai/o3-pro | 21.9 | 200K | $20 | $80 | 2025-06-10 | |||
| Qwen: Qwen3.5-9B (batch)qwen/qwen3.5-9b:batch | 21.8 | 262.144K | $0.17 | $0.25 | — | |||
| MiMo-V2.5xiaomi/mimo-v2.5 | 21.8 | 1.04858M | $0.14 | $0.28 | 2026-04-22 | |||
| DeepSeek V3.2deepseek/deepseek-v3.2 | 21.5 | 128K | $0.209 | $0.31 | 2025-12-01 | |||
| Qwen: Qwen3.5 397B A17Bqwen/qwen3.5-397b-a17b | 21.4 | 262.144K | $0.5 | $3.6 | — | |||
| Qwen: Qwen3.6 27Bqwen/qwen3.6-27b | 21.4 | 262.144K | $0.32 | $3.2 | — | |||
| Qwen: Qwen3 Max Thinkingqwen/qwen3-max-thinking | 21.3 | 262.144K | $0.78 | $3.9 | — | |||
| MiniMax: MiniMax M2.1minimax/minimax-m2.1 | 20.9 | 204.8K | $0.3 | $1.2 | — | |||
| Anthropic: Claude Sonnet 4.5anthropic/claude-sonnet-4.5 | 20.7 | 1M | $3 | $15 | — | |||
| Anthropic: Claude Sonnet 4.5 (batch)anthropic/claude-sonnet-4.5:batch | 20.7 | 1M | $1.5 | $7.5 | — | |||
| GPT-5.4 nanoopenai/gpt-5.4-nano | 20.7 | 400K | $0.2 | $1.25 | 2026-03-17 | |||
| OpenAI: GPT-5.4 Nano (batch)openai/gpt-5.4-nano:batch | 20.7 | 400K | $0.1 | $0.625 | — | |||
| GPT-5 Miniopenai/gpt-5-mini | 20.6 | 400K | $0.25 | $2 | 2025-08-07 | |||
| OpenAI: GPT-5 Mini (batch)openai/gpt-5-mini:batch | 20.6 | 400K | $0.125 | $1 | — | |||
| GPT-5.1 Codex miniopenai/gpt-5.1-codex-mini | 20.4 | 400K | $0.22 | $1.8 | 2025-11-13 | |||
| o3openai/o3 | 20.2 | 200K | $2 | $8 | 2025-04-16 | |||
| OpenAI: o3 (batch)openai/o3:batch | 20.2 | 200K | $1 | $4 | — | |||
| Ling 3.0 Flashinclusionai/ling-3.0-flash | 20.1 | 262.144K | $0.021 | $0.063 | 2026-07-23 | |||
| Step 3.7 Flashstepfun/step-3.7-flash | 19.5 | 256K | $0.202 | $1.211 | 2026-05-29 | |||
| Qwen: Qwen3.5-35B-A3Bqwen/qwen3.5-35b-a3b | 19.3 | 262.144K | $0.14 | $1 | — | |||
| LongCat-2.0meituan/longcat-2.0 | 19.1 | 1M | $0.3 | $1.2 | 2026-06-30 | |||
| Anthropic: Claude Sonnet 4anthropic/claude-sonnet-4 | 18.9 | 200K | $3 | $15 | — | |||
| MiniMax: MiniMax M2minimax/minimax-m2 | 18.6 | 204.8K | $0.255 | $1.02 | — | |||
| Z.ai: GLM 4.6z-ai/glm-4.6 | 18.5 | 204.8K | $0.55 | $2.2 | — | |||
| Qwen: Qwen3.6 35B A3Bqwen/qwen3.6-35b-a3b | 18.2 | 262.144K | $0.1 | $0.95 | — | |||
| Qwen: Qwen3.5-122B-A10Bqwen/qwen3.5-122b-a10b | 17.7 | 262.144K | $0.4 | $3.2 | — | |||
| Muse Glimmer 30Bmeta/muse-glimmer-30b | 17.5 | 131.072K | $0.2 | $0.8 | 2026-08-10 | |||
| Step 3.5 Flashstepfun/step-3.5-flash | 17.0 | 256K | $0.105 | $0.314 | 2026-01-29 | |||
| Anthropic: Claude Haiku 4.5anthropic/claude-haiku-4.5 | 16.9 | 200K | $1 | $5 | — | |||
| Anthropic: Claude Haiku 4.5 (batch)anthropic/claude-haiku-4.5:batch | 16.9 | 200K | $0.5 | $2.5 | — | |||
| Gemma 4 26B A4B ITgoogle/gemma-4-26b-a4b-it | 16.7 | 262.144K | $0.042 | $0.22 | 2026-04-02 | |||
| Google: Gemma 4 26B A4B (free)google/gemma-4-26b-a4b-it:free | 16.7 | 262.144K | Free | Free | — | |||
| o4-miniopenai/o4-mini | 16.7 | 200K | $1.1 | $4.4 | 2025-04-16 | |||
| OpenAI: o4 Mini (batch)openai/o4-mini:batch | 16.7 | 200K | $0.55 | $2.2 | — | |||
| DeepSeek: DeepSeek V3.2 Expdeepseek/deepseek-v3.2-exp | 16.6 | 163.84K | $0.27 | $0.41 | — | |||
| Gemini 2.5 Progoogle/gemini-2.5-pro | 16.1 | 1.04858M | $1.25 | $10 | 2025-06-17 | |||
| Google: Gemini 2.5 Pro (batch)google/gemini-2.5-pro:batch | 16.1 | 1.04858M | $0.625 | $5 | — | |||
| OpenAI: o3 Mini High (batch)openai/o3-mini-high:batch | 15.7 | 200K | $0.55 | $2.2 | — |