Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function...
Models
Every model in the catalog with source-linked pricing, context limits, provider availability, and published benchmark results.
Largest Gemma 4 instruction model for open, self-hosted chat and reasoning
Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function...
Multimodal reasoning model for visual analysis, planning, and tool use
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...
Mistral Medium 3.1 is an updated version of Mistral Medium 3, which is a high-performance enterprise-grade language model designed to deliver frontier-level capabilities at significantly reduced operational cost. It balances...
Mistral Medium 3.1 is an updated version of Mistral Medium 3, which is a high-performance enterprise-grade language model designed to deliver frontier-level capabilities at significantly reduced operational cost. It balances...
Affordable GPT-4.1 lane for fast coding help and structured extraction
GPT-4.1 Mini is a mid-sized model delivering performance competitive with GPT-4o at substantially lower latency and cost. It retains a 1 million token context window and scores 45.1% on hard...
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...
Low-latency Gemini model for high-volume multimodal and agent workloads
Tiny GPT-4.1 option for classification, routing, and very high-volume tasks
For tasks that demand low latency, GPT‑4.1 nano is the fastest and cheapest model in the GPT-4.1 series. It delivers exceptional performance at a small size with its 1 million...
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...
The largest model in the Ministral 3 family, Ministral 3 14B offers frontier capabilities and performance comparable to its larger Mistral Small 3.2 24B counterpart. A powerful and efficient language...
Mistral Large 3 2512 is Mistral’s most capable model to date, featuring a sparse mixture-of-experts architecture with 41B active parameters (675B total), and released under the Apache 2.0 license.
Mistral Large 3 2512 is Mistral’s most capable model to date, featuring a sparse mixture-of-experts architecture with 41B active parameters (675B total), and released under the Apache 2.0 license.
Small omni GPT for cheap multimodal assistance and production-scale traffic
GPT-4o mini is OpenAI's newest model after [GPT-4 Omni](/models/openai/gpt-4o), supporting both text and image inputs with text outputs. As their most advanced small model, it is many multiples more affordable...
The smallest model in the Ministral 3 family, Ministral 3 3B is a powerful, efficient tiny language model with vision capabilities.
Mistral Small 4 is the next major release in the Mistral Small family, unifying the capabilities of several flagship Mistral models into a single system. It combines strong reasoning from...
Mistral Small 4 is the next major release in the Mistral Small family, unifying the capabilities of several flagship Mistral models into a single system. It combines strong reasoning from...
Llama 4 Maverick 17B Instruct (128E) is a high-capacity multimodal language model from Meta, built on a mixture-of-experts (MoE) architecture with 128 experts and 17 billion active parameters per forward...
A balanced model in the Ministral 3 family, Ministral 3 8B is a powerful, efficient tiny language model with vision capabilities.
A balanced model in the Ministral 3 family, Ministral 3 8B is a powerful, efficient tiny language model with vision capabilities.
Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input...
Open multimodal Gemma instruction model for multilingual text generation and image understanding
Largest open Gemma 3 instruction model for multilingual text generation and visual understanding
| Model | Creator | Score | Inputs | Context | Input | Output | Released | Compare |
|---|---|---|---|---|---|---|---|---|
| Google: Gemma 4 31B (batch)google/gemma-4-31b-it:batch | 6.7 | 262.144K | $0.39 | $0.97 | — | |||
| Gemma 4 31B ITgoogle/gemma-4-31b-it | 4.2 | 262.144K | $0.1 | $0.25 | 2026-04-02 | |||
| Google: Gemma 4 31B (free)google/gemma-4-31b-it:free | 4.2 | 262.144K | Free | Free | — | |||
| Nova 2 Liteamazon/nova-2-lite-v1 | 3.1 | 1M | $0.3 | $2.5 | 2025-12-02 | |||
| Gemma 4 26B A4B ITgoogle/gemma-4-26b-a4b-it | 2.9 | 262.144K | $0.042 | $0.22 | 2026-04-02 | |||
| Google: Gemma 4 26B A4B (free)google/gemma-4-26b-a4b-it:free | 2.9 | 262.144K | Free | Free | — | |||
| Mistral: Mistral Medium 3.1mistralai/mistral-medium-3.1 | 1.9 | 131.072K | $0.4 | $2 | — | |||
| Mistral: Mistral Medium 3.1 (batch)mistralai/mistral-medium-3.1:batch | 1.9 | 131.072K | $0.2 | $1 | — | |||
| GPT-4.1 miniopenai/gpt-4.1-mini | 1.8 | 1.04758M | $0.4 | $1.6 | 2025-04-14 | |||
| OpenAI: GPT-4.1 Mini (batch)openai/gpt-4.1-mini:batch | 1.8 | 1.04758M | $0.2 | $0.8 | — | |||
| Gemini 2.5 Progoogle/gemini-2.5-pro | 1.6 | 1.04858M | $1.25 | $10 | 2025-06-17 | |||
| Google: Gemini 2.5 Pro (batch)google/gemini-2.5-pro:batch | 1.6 | 1.04858M | $0.625 | $5 | — | |||
| Gemini 3.1 Flash Lite Previewgoogle/gemini-3.1-flash-lite-preview | 1.6 | 1.04858M | $0.25 | $1.5 | 2026-03-03 | |||
| GPT-4.1 nanoopenai/gpt-4.1-nano | 1.2 | 1.04758M | $0.1 | $0.4 | 2025-04-14 | |||
| OpenAI: GPT-4.1 Nano (batch)openai/gpt-4.1-nano:batch | 1.2 | 1.04758M | $0.05 | $0.2 | — | |||
| Qwen: Qwen3.5-9Bqwen/qwen3.5-9b | 1.2 | 262.144K | $0.17 | $0.25 | — | |||
| Mistral: Ministral 3 14B 2512mistralai/ministral-14b-2512 | 1.1 | 262.144K | $0.2 | $0.2 | — | |||
| Mistral: Mistral Large 3 2512mistralai/mistral-large-2512 | 1.0 | 262.144K | $0.5 | $1.5 | — | |||
| Mistral: Mistral Large 3 2512 (batch)mistralai/mistral-large-2512:batch | 1.0 | 262.144K | $0.25 | $0.75 | — | |||
| GPT-4o miniopenai/gpt-4o-mini | 1.0 | 128K | $0.15 | $0.6 | 2024-07-18 | |||
| OpenAI: GPT-4o-mini (batch)openai/gpt-4o-mini:batch | 1.0 | 128K | $0.075 | $0.3 | — | |||
| Mistral: Ministral 3 3B 2512mistralai/ministral-3b-2512 | 0.8 | 131.072K | $0.1 | $0.1 | — | |||
| Mistral: Mistral Small 4mistralai/mistral-small-2603 | 0.8 | 262.144K | $0.15 | $0.6 | — | |||
| Mistral: Mistral Small 4 (batch)mistralai/mistral-small-2603:batch | 0.8 | 262.144K | $0.075 | $0.3 | — | |||
| Meta: Llama 4 Maverickmeta-llama/llama-4-maverick | 0.6 | 128K | $0.188 | $0.652 | — | |||
| Mistral: Ministral 3 8B 2512mistralai/ministral-8b-2512 | 0.6 | 262.144K | $0.15 | $0.15 | — | |||
| Mistral: Ministral 3 8B 2512 (batch)mistralai/ministral-8b-2512:batch | 0.6 | 262.144K | $0.075 | $0.075 | — | |||
| Meta: Llama 4 Scoutmeta-llama/llama-4-scout | 0.5 | 327.68K | $0.1 | $0.3 | — | |||
| Gemma 3 12B ITgoogle/gemma-3-12b-it | 0.1 | 131.072K | $0.04 | $0.12 | 2025-03-12 | |||
| Gemma 3 27B ITgoogle/gemma-3-27b-it | 0.1 | 131.072K | $0.08 | $0.45 | 2025-03-12 |